Satellite/Submarine Arctic Sea Ice Remote Sensing in 2004 and 2007

NASA Astrophysics Data System (ADS)

Hughes, N. E.; Wadhams, P.; Rodrigues, J.

2007-12-01

After an interlude of 8 years the U.K. Royal Navy returned to the Arctic Ocean with an under-ice mission by the submarine shape HMS Tireless in April 2004. A full environmental monitoring programme in which U.K. civilian scientists were allowed to participate was integrated into the mission. This was subsequently followed by a second expedition, in March 2007, which allowed further measurements to be acquired. These have so far been the only opportunities for civilian scientists to utilise navy submarines in the Arctic since the demise of the U.S. SCICEX programme in 2000. This paper presents some of the data collected on these new missions and uses it for validation of sea ice information derived from coincident acquisitions by modern satellite sensors such as the ESA Envisat ASAR and NASA MODIS. In both the 2004 and 2007 expeditions shape Tireless took a track north of Greenland along the latitude 85° N. This was similar to the route used for an earlier submarine-aircraft combined survey in April 1987 with which our results shall be compared. In all three missions the submarine was equipped with a standard upward-looking echosounder and sidescan for ice observations and a full range of satellite-borne, or airborne in the case of the earlier mission, microwave and optical sensors were available for validation. In this study we concentrate on the submarine track north of Greenland from the Marginal Ice Zone (MIZ) in Fram Strait through to the Lincoln Sea around 65° W. This transect encompasses a wide range of differing sea ice conditions, from the highly mobile mixture of first year and multi year ice being transported on the trans-polar drift through to the highly deformed ice north of Greenland and Ellesmere Island. The combination of submarine measurements of ice thickness and satellite/aircraft top-side measurements gives an accurate indication of how changes in the ice regime are taking place and allows the potential development of multi-sensor data fusion algorithms for improved sea ice classification and estimation of thickness.

Interferometric side scan sonar and data fusion

NASA Astrophysics Data System (ADS)

Sintes, Christophe R.; Solaiman, Basel

2000-04-01

This paper concerns the possibilities of sea bottom imaging and altitude determining of each imaged point. The performances of new side scan sonars which are able to image the sea bottom with a high definition and are able to evaluate the relief with the same definition derive from an interferometric multisensor system. The drawbacks concern the precision of the numerical altitude model. One way to improve the measurements precision is to merge all the information issued from the multi-sensors system. This leads to increase the Signal to Noise Ratio (SNR) and the robustness of the used method. The aim of this paper is to clearly demonstrate the ability to derive benefits of all information issued from the three arrays side scan sonar by merging: (1) the three phase signals obtained at the output of the sensors, (2) this same set of data after the application of different processing methods, and (3) the a priori relief contextual information. The key idea the proposed fusion technique is to exploit the strength and the weaknesses of each data element in the fusion of process so that the global SNR will be improved as well as the robustness to hostile noisy environments.

How will we ensure the long-term sea ice data record continues?

NASA Astrophysics Data System (ADS)

Stroeve, J. C.; Kaleschke, L.

2017-12-01

The multi-channel satellite passive microwave record has been of enormous benefit to the science community and society at large since the late 1970s. Starting with the launch of the Nimbus-7 Scanning Multi-Channel Microwave Radiometer (SMMR) in October 1978, and continuing with the launch of a series of Special Sensor Microwave Imagers (SSM/Is) in June 1987 by the Defense Meteorological Satellite Program (DMSP), places previously difficult to monitor year-round, such as the polar regions, came to light. Together these sensors have provided nearly 4 decades of climate data records on the state of sea ice cover over the ocean and snow on land. This data has also been used to map melt extent on the large ice sheets, timing of snow melt onset over land and sea ice. Application also extend well beyond the polar regions, mapping important climate variables, such as soil moisture content, oceanic wind speed, rainfall, water vapor, cloud liquid water and total precipitable water. Today the current SSMIS operational satellite (F18) is 7 years old and there is no follow-on mission planned by the DMSP. With the end of the SSMI family of Sensors, will the polar regions once again be in the dark? Other sensors that may contribute to the long-term data record include the JAXA AMSR2 (5 years old as of May 2017), the Chinese Fen-Yung-3 and the Russian Meteor-N2. Scatterometry and L-band radiometry from SMOS and NASA's SMOS may also provide some potential means of extending the sea ice extent data record, as well as future sensors by the DoD, JAXA and ESA. However, this will require considerable effort to intercalibrate the different sensors to ensure consistency in the long-term data record. Differences in measurement approach, frequency and spatial resolution make this a non-trivial matter. The passive microwave sea ice extent data record is one of the longest and most consistent climate data records available. It provides daily monitoring of one of the most striking changes in our climate system, the loss of the Arctic sea ice cover. A series of replacement sensors is urgently needed, preferably at higher spatial resolution to better delineate the ice edge for marine applications such as ship routing.

Study on the multi-sensors monitoring and information fusion technology of dangerous cargo container

NASA Astrophysics Data System (ADS)

Xu, Shibo; Zhang, Shuhui; Cao, Wensheng

2017-10-01

In this paper, monitoring system of dangerous cargo container based on multi-sensors is presented. In order to improve monitoring accuracy, multi-sensors will be applied inside of dangerous cargo container. Multi-sensors information fusion solution of monitoring dangerous cargo container is put forward, and information pre-processing, the fusion algorithm of homogenous sensors and information fusion based on BP neural network are illustrated, applying multi-sensors in the field of container monitoring has some novelty.

Multi-Sensor Registration of Earth Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Cole-Rhodes, Arlene; Eastman, Roger; Johnson, Kisha; Morisette, Jeffrey; Netanyahu, Nathan S.; Stone, Harold S.; Zavorin, Ilya; Zukor, Dorothy (Technical Monitor)

2001-01-01

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

A New Study of Sea Spray Optical Properties from Multi-Sensor Spaceborne Observations

NASA Technical Reports Server (NTRS)

Dawson, K. W.; Meskhidze, N.; Josset, D.; Gasso, S.

2014-01-01

Retrievals of aerosol optical depth (AOD) from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite sensor require the assumption of an extinction-to-backscatter ratio, also known as the lidar ratio. This paper evaluates a new method to calculate lidar ratio of sea spray aerosol using two independent sources: the AOD from Synergized Optical Depth of Aerosols (SODA) and the integrated attenuated backscatter from CALIOP. The method applied in this study allows particulate lidar ratio to be calculated for individual CALIOP retrievals of single aerosol layer columns over the ocean. Analyses are carried out using CALIOP level 2, 5km sea spray aerosol layer products and collocated SODA nighttime data from December 2007 to December 2009. The global mean lidar ratio for sea spray aerosols was found to be 26 sr, roughly 30 higher than the one prescribed by CALIOP. Data analysis also showed considerable spatiotemporal variability in calculated lidar ratio over different parts of the remote oceans. The calculated aerosol lidar ratios are shown to be inversely related to the mean ocean surface wind speed: increase in ocean surface wind speed (U10) from 0 to 15 ms-1 reduces the mean lidar ratios for sea spray particles from 32 sr (for 0 U10 4 ms-1) to 22 sr (for U10 15 ms-1). Such changes in the lidar ratio are expected to have a corresponding effect on sea spray AOD. The outcomes of this study are relevant for future improvements of the SODA and CALIOP operational product and could lead to more accurate retrievals of sea spray AOD.

Doppler Navigation System with a Non-Stabilized Antenna as a Sea-Surface Wind Sensor.

PubMed

Nekrasov, Alexey; Khachaturian, Alena; Veremyev, Vladimir; Bogachev, Mikhail

2017-06-09

We propose a concept of the utilization of an aircraft Doppler Navigation System (DNS) as a sea-surface wind sensor complementary to its normal functionality. The DNS with an antenna, which is non-stabilized physically to the local horizontal with x -configured beams, is considered. We consider the wind measurements by the DNS configured in the multi-beam scatterometer mode for a rectilinear flight scenario. The system feasibility and the efficiency of the proposed wind algorithm retrieval are supported by computer simulations. Finally, the associated limitations of the proposed approach are considered.

Doppler Navigation System with a Non-Stabilized Antenna as a Sea-Surface Wind Sensor

PubMed Central

Nekrasov, Alexey; Khachaturian, Alena; Veremyev, Vladimir; Bogachev, Mikhail

2017-01-01

We propose a concept of the utilization of an aircraft Doppler Navigation System (DNS) as a sea-surface wind sensor complementary to its normal functionality. The DNS with an antenna, which is non-stabilized physically to the local horizontal with x-configured beams, is considered. We consider the wind measurements by the DNS configured in the multi-beam scatterometer mode for a rectilinear flight scenario. The system feasibility and the efficiency of the proposed wind algorithm retrieval are supported by computer simulations. Finally, the associated limitations of the proposed approach are considered. PMID:28598374

Hyperspectral Features of Oil-Polluted Sea Ice and the Response to the Contamination Area Fraction

PubMed Central

Li, Ying; Liu, Chengyu; Xie, Feng

2018-01-01

Researchers have studied oil spills in open waters using remote sensors, but few have focused on extracting reflectance features of oil pollution on sea ice. An experiment was conducted on natural sea ice in Bohai Bay, China, to obtain the spectral reflectance of oil-contaminated sea ice. The spectral absorption index (SAI), spectral peak height (SPH), and wavelet detail coefficient (DWT d5) were calculated using stepwise multiple linear regression. The reflectances of some false targets were measured and analysed. The simulated false targets were sediment, iron ore fines, coal dust, and the melt pool. The measured reflectances were resampled using five common sensors (GF-2, Landsat8-OLI, Sentinel3-OLCI, MODIS, and AVIRIS). Some significant spectral features could discriminate between oil-polluted and clean sea ice. The indices correlated well with the oil area fractions. All of the adjusted R2 values exceeded 0.9. The SPH model1, based on spectral features at 507–670 and 1627–1746 nm, displayed the best fitting. The resampled data indicated that these multi-spectral and hyper-spectral sensors could be used to detect crude oil on the sea ice if the effect of noise and spatial resolution are neglected. The spectral features and their identified changes may provide reference on sensor design and band selection. PMID:29342945

A glimpse beneath Antarctic sea ice: observation of platelet-layer thickness and ice-volume fraction with multi-frequency EM

NASA Astrophysics Data System (ADS)

Hendricks, S.; Hoppmann, M.; Hunkeler, P. A.; Kalscheuer, T.; Gerdes, R.

2015-12-01

In Antarctica, ice crystals (platelets) form and grow in supercooled waters below ice shelves. These platelets rise and accumulate beneath nearby sea ice to form a several meter thick sub-ice platelet layer. This special ice type is a unique habitat, influences sea-ice mass and energy balance, and its volume can be interpreted as an indicator for ice - ocean interactions. Although progress has been made in determining and understanding its spatio-temporal variability based on point measurements, an investigation of this phenomenon on a larger scale remains a challenge due to logistical constraints and a lack of suitable methodology. In the present study, we applied a lateral constrained Marquardt-Levenberg inversion to a unique multi-frequency electromagnetic (EM) induction sounding dataset obtained on the ice-shelf influenced fast-ice regime of Atka Bay, eastern Weddell Sea. We adapted the inversion algorithm to incorporate a sensor specific signal bias, and confirmed the reliability of the algorithm by performing a sensitivity study using synthetic data. We inverted the field data for sea-ice and sub-ice platelet-layer thickness and electrical conductivity, and calculated ice-volume fractions from platelet-layer conductivities using Archie's Law. The thickness results agreed well with drill-hole validation datasets within the uncertainty range, and the ice-volume fraction also yielded plausible results. Our findings imply that multi-frequency EM induction sounding is a suitable approach to efficiently map sea-ice and platelet-layer properties. However, we emphasize that the successful application of this technique requires a break with traditional EM sensor calibration strategies due to the need of absolute calibration with respect to a physical forward model.

Research on infrared dim-point target detection and tracking under sea-sky-line complex background

NASA Astrophysics Data System (ADS)

Dong, Yu-xing; Li, Yan; Zhang, Hai-bo

2011-08-01

Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system, the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties .There are some traditional point target detection algorithms, such as adaptive background prediction detecting method. When background has dispersion-decreasing structure, the traditional target detection algorithms would be more useful. But when the background has large gray gradient, such as sea-sky-line, sea waves etc .The bigger false-alarm rate will be taken in these local area .It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature ,in our opinion , from the perspective of mathematics, the detection of dim-point targets in image is about singular function analysis .And from the perspective image processing analysis , the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection, its essence is a separation of target and background of different singularity characteristics .The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore, the purpose of the image preprocessing is to reduce the effects from noise, also to raise the SNR of image, and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics , the median filter is used to eliminate noise, improve signal-to-noise ratio, then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line ,so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background.

Radar and optical remote sensing in offshore domain to detect, characterize, and quantify ocean surface oil slicks

NASA Astrophysics Data System (ADS)

Angelliaume, S.; Ceamanos, X.; Viallefont-Robinet, F.; Baqué, R.; Déliot, Ph.; Miegebielle, V.

2017-10-01

Radar and optical sensors are operationally used by authorities or petroleum companies for detecting and characterizing maritime pollution. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as the oil real fraction, which is critical for both exploration purposes and efficient cleanup operations. Today state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI, the airborne system developed by ONERA, during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this data set lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the electromagnetic spectrum. Specific processing techniques have been developed in order to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows to estimate slick surface properties such as the spatial abundance of oil and the relative concentration of hydrocarbons on the sea surface.

The effects of mineral aerosol deposits on the BRDF (bidirectional reflectance distribution function) of sea ice for the calibration of satellite remote sensing products: an experimental and modelling study.

NASA Astrophysics Data System (ADS)

Lamare, Maxim; Hedley, John; King, Martin

2016-04-01

Knowledge of the albedo in the cryosphere is essential to monitor a range of climatic processes that have an impact on a global scale. Optical Earth Observation satellites are ideal for the synoptic observation of expansive and inaccessible areas, providing large datasets used to derive essential products, such as albedo. The application of remote sensing to investigate climate processes requires the combination of data from different sensors. However, although there is significant value in the analysis of data from individual sensors, global observing systems require accurate knowledge of sensor-to-sensor biases. Therefore, the inter-calibration of sensors used for climate studies is essential to avoid inconsistencies, which may mask climate effects. CEOS (Committee on Earth Observing Satellites) has established a number of natural Earth targets to serve as international reference standards, amongst which sea ice has great potential. The reflectance of natural surfaces is not isotropic and reflectance varies with the illumination and viewing geometries, consequently impacting satellite observations. Furthermore, variations in the physical properties (sea ice type, thickness) and the light absorbing impurities deposited in the sea ice have a strong impact on reflectance. Thus, the characterisation of the bi-directional reflectance distribution function (BRDF) of sea ice is a fundamental step toward the inter-calibration of optical satellite sensors. This study provides a characterisation of the effects of mineral aerosol and black carbon deposits on the BRDF of three different sea ice types. BRDF measurements were performed on bare sea ice grown in an experimental ice tank, using a state-of-the-art laboratory goniometer. The sea ice was "poisoned" with concentrations of mineral dust and black carbon varying between 100 and 5 000 ng g-1 deposited uniformly in a 5 cm surface layer. Using measurements from the experimental facility, novel information about sea ice BRDF as a function of sea ice type, thickness and light-absorbing impurities was derived using a radiative-transfer model (PlanarRad). This extensive characterisation of the multi angular reflectance of sea ice reveals the importance of BRDF for the validation and calibration of Earth Observation satellite sensor data.

OSOAA: A Vector Radiative Transfer Model of Coupled Atmosphere-Ocean System for a Rough Sea Surface Application to the Estimates of the Directional Variations of the Water Leaving Reflectance to Better Process Multi-angular Satellite Sensors Data Over the Ocean

NASA Technical Reports Server (NTRS)

Chami, Malik; LaFrance, Bruno; Fougnie, Bertrand; Chowdhary, Jacek; Harmel, Tristan; Waquet, Fabien

2015-01-01

In this study, we present a radiative transfer model, so-called OSOAA, that is able to predict the radiance and degree of polarization within the coupled atmosphere-ocean system in the presence of a rough sea surface. The OSOAA model solves the radiative transfer equation using the successive orders of scattering method. Comparisons with another operational radiative transfer model showed a satisfactory agreement within 0.8%. The OSOAA model has been designed with a graphical user interface to make it user friendly for the community. The radiance and degree of polarization are provided at any level, from the top of atmosphere to the ocean bottom. An application of the OSOAA model is carried out to quantify the directional variations of the water leaving reflectance and degree of polarization for phytoplankton and mineral-like dominated waters. The difference between the water leaving reflectance at a given geometry and that obtained for the nadir direction could reach 40%, thus questioning the Lambertian assumption of the sea surface that is used by inverse satellite algorithms dedicated to multi-angular sensors. It is shown as well that the directional features of the water leaving reflectance are weakly dependent on wind speed. The quantification of the directional variations of the water leaving reflectance obtained in this study should help to correctly exploit the satellite data that will be acquired by the current or forthcoming multi-angular satellite sensors.

Multi-sensor Oceanographic Correlations for Pacific Hake Acoustic Survey Improvement

NASA Astrophysics Data System (ADS)

Brozen, M.; Hillyer, N.; Holt, B.; Armstrong, E. M.

2010-12-01

North Pacific hake (Merluccius productus), the most abundant groundfish along the Pacific coast of northwestern America, are an essential source of income for the coastal region from southern California to British Columbia, Canada. However, hake abundance and distribution are highly variable among years, exhibiting variance in both the north-south and east-west distribution as seen in the results from biannual acoustic surveys. This project is part of a larger undertaking, ultimately focused on the prediction of hake distribution to improve the distribution of survey effort and precision of stock assessments in the future. Four remotely sensed oceanographic variables are examined as a first step in improving our understanding the relationship between the intensity of coastal upwelling and other ocean dynamics, and the north-south summer hake distribution. Sea surface height, wind vectors, chlorophyll - a concentrations, and sea surface temperature were acquired from several satellites, including AVHRR, SeaWifs, TOPEX/Poseidon, Jason-1, Jason-2, SSM/I, ASMR-E, and QuikScat. Data were aligned to the same spatial and temporal resolution, and these re-gridded data were then analyzed using empirical orthogonal functions (EOFs). EOFs were used as a spatio-temporally compact representation of the data and to reduce the co-variability of the multiple time series in the dataset. The EOF results were plotted and acoustic survey results were overlaid to understand differences between regions. Although this pilot project used data from only a single year (2007), it demonstrated a methodology for reducing dimensionality of linearly related satellite variables that can used in future applications, and provided insight into multi-dimensional ocean characteristics important for hake distribution.

A Method for Improving the Pose Accuracy of a Robot Manipulator Based on Multi-Sensor Combined Measurement and Data Fusion

PubMed Central

Liu, Bailing; Zhang, Fumin; Qu, Xinghua

2015-01-01

An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to the higher accuracy of the multi-sensor, two efficient data fusion approaches, the Kalman filter (KF) and multi-sensor optimal information fusion algorithm (MOIFA), are used to fuse the position and orientation of the manipulator. The simulation and experimental results show that the pose accuracy of the robot manipulator is improved dramatically by 38%∼78% with the multi-sensor data fusion. Comparing with reported pose accuracy improvement methods, the primary advantage of this method is that it does not require the complex solution of the kinematics parameter equations, increase of the motion constraints and the complicated procedures of the traditional vision-based methods. It makes the robot processing more autonomous and accurate. To improve the reliability and accuracy of the pose measurements of MCMS, the visual sensor repeatability is experimentally studied. An optimal range of 1 × 0.8 × 1 ∼ 2 × 0.8 × 1 m in the field of view (FOV) is indicated by the experimental results. PMID:25850067

Development of High Fidelity Mobility Simulation of an Autonomous Vehicle in an Off-Road Scenario Using Integrated Sensor, Controller, and Multi-Body Dynamics

DTIC Science & Technology

2011-08-01

VEHICLE IN AN OFF-ROAD SCENARIO USING INTEGRATED SENSOR, CONTROLLER, AND MULTI-BODY DYNAMICS Paramsothy Jayakumar , PhD William Smith US Army...environment for a control system, mechanical system dynamics , and sensor simulation for an improved assessment of the vehicle system performance...improve vehicle dynamic performance; we must also evaluate and improve the sensor suite employed on the vehicle, and the controller used to operate

ASTER First Views of Red Sea, Ethiopia - Thermal-Infrared TIR Image monochrome

NASA Image and Video Library

2000-03-11

ASTER succeeded in acquiring this image at night, which is something Visible/Near Infrared VNIR) and Shortwave Infrared (SWIR) sensors cannot do. The scene covers the Red Sea coastline to an inland area of Ethiopia. White pixels represent areas with higher temperature material on the surface, while dark pixels indicate lower temperatures. This image shows ASTER's ability as a highly sensitive, temperature-discerning instrument and the first spaceborne TIR multi-band sensor in history. The size of image: 60 km x 60 km approx., ground resolution 90 m x 90 m approximately. http://photojournal.jpl.nasa.gov/catalog/PIA02452

Operational Monitoring and Forecasting in Regional Seas: the Aegean Sea example

NASA Astrophysics Data System (ADS)

Nittis, K.; Perivoliotis, L.; Zervakis, V.; Papadopoulos, A.; Tziavos, C.

2003-04-01

The increasing economic activities in the coastal zone and the associated pressure on the marine environment have raised the interest on monitoring systems able to provide supporting information for its effective management and protection. Such an integrated monitoring, forecasting and information system is being developed during the past years in the Aegean Sea. Its main component is the POSEIDON network that provides real-time data for meteorological and surface oceanographic parameters (waves, currents, hydrological and biochemical data) from 11 fixed oceanographic buoys. The numerical forecasting system is composed by an ETA atmospheric model, a WAM wave model and a POM hydrodynamic model that provide every day 72 hours forecasts. The system is operational since May 2000 and its products are published through Internet while a sub-set is also available through cellular telephony. New type of observing platforms will be available in the near future through a number of EU funded research projects. The Mediterranean Moored Multi-sensor Array (M3A) that was developed for the needs of the Mediterranean Forecasting System and was tested during 2000-2001 will be operational in 2004 during the MFSTEP project. The M3A system incorporates sensors for optical and chemical measurements (Oxygen, Turbidity, Chlorophyll-a, Nutrients and PAR) in the euphotic zone (0-100m) together with sensors for physical parameters (Temperature, Salinity, Current speed and direction) at the 0-500m layer. A Ferry-Box system will also operate during 2004 in the southern Aegean Sea, providing surface data for physical and bio-chemical properties. The ongoing modeling efforts include coupling with larger scale circulation models of the Mediterranean, high-resolution downscaling to coastal areas of the Aegean Sea and development of multi-variate data assimilation methods.

Field Performance of ISFET based Deep Ocean pH Sensors

NASA Astrophysics Data System (ADS)

Branham, C. W.; Murphy, D. J.

2017-12-01

Historically, ocean pH time series data was acquired from infrequent shipboard grab samples and measured using labor intensive spectrophotometry methods. However, with the introduction of robust and stable ISFET pH sensors for use in ocean applications a paradigm shift in the methods used to acquire long-term pH time series data has occurred. Sea-Bird Scientific played a critical role in the adoption this new technology by commercializing the SeaFET pH sensor and float pH Sensor developed by the MBARI chemical sensor group. Sea-Bird Scientific continues to advance this technology through a concerted effort to improve pH sensor accuracy and reliability by characterizing their performance in the laboratory and field. This presentation will focus on calibration of the ISFET pH sensor, evaluate its analytical performance, and validate performance using recent field data.

Estimating suspended sediment concentrations in turbid coastal waters of the Santa Barbara Channel with SeaWiFS

USGS Publications Warehouse

Warrick, J.A.; Mertes, L.A.K.; Siegel, D.A.; Mackenzie, C.

2004-01-01

A technique is presented for estimating suspended sediment concentrations of turbid coastal waters with remotely sensed multi-spectral data. The method improves upon many standard techniques, since it incorporates analyses of multiple wavelength bands (four for Sea-viewing Wide Field of view Sensor (SeaWiFS)) and a nonlinear calibration, which produce highly accurate results (expected errors are approximately ±10%). Further, potential errors produced by erroneous atmospheric calibration in excessively turbid waters and influences of dissolved organic materials, chlorophyll pigments and atmospheric aerosols are limited by a dark pixel subtraction and removal of the violet to blue wavelength bands. Results are presented for the Santa Barbara Channel, California where suspended sediment concentrations ranged from 0–200+ mg l−1 (±20 mg l−1) immediately after large river runoff events. The largest plumes were observed 10–30 km off the coast and occurred immediately following large El Niño winter floods.

Satellite-Derived Sea Surface Temperature: Workshop 1

NASA Technical Reports Server (NTRS)

Njoku, E. G.

1983-01-01

Satellite measurements of sea surface temperature are now possible using a variety of sensors. The present accuracies of these methods are in the range of 0.5 to 2.0 C. This makes them potentially useful for synoptic studies of ocean currents and for global monitoring of climatological anomalies. To improve confidence in the satellite data, objective evaluations of sensor accuracies are necessary, and the conditions under which these accuracies degrade need to be understood. The Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite was studied. Sea surface temperatures, derived from November 1979 SMMR data, were compared globally against ship measurements and climatology, using facilities of the JPL Pilot Ocean Data System. Methods for improved data analysis and plans for additional workshops to incorporate data from other sensors were discussed.

Hyperspectral and Radar Airborne Imagery over Controlled Release of Oil at Sea.

PubMed

Angelliaume, Sébastien; Ceamanos, Xavier; Viallefont-Robinet, Françoise; Baqué, Rémi; Déliot, Philippe; Miegebielle, Véronique

2017-08-02

Remote sensing techniques are commonly used by Oil and Gas companies to monitor hydrocarbon on the ocean surface. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as thickness and composition of the detected oil, which is critical for both exploration purposes and efficient cleanup operations. Today, state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI (Système Expérimental de Télédection Hyperfréquence Imageur), the airborne system developed by ONERA (the French Aerospace Lab), during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this dataset lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the EM spectrum. Specific processing techniques have been developed to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows estimating slick surface properties such as the age of the emulsion released at sea, the spatial abundance of oil and the relative concentration of hydrocarbons remaining on the sea surface.

Hyperspectral and Radar Airborne Imagery over Controlled Release of Oil at Sea

PubMed Central

Angelliaume, Sébastien; Ceamanos, Xavier; Viallefont-Robinet, Françoise; Baqué, Rémi; Déliot, Philippe

2017-01-01

Remote sensing techniques are commonly used by Oil and Gas companies to monitor hydrocarbon on the ocean surface. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as thickness and composition of the detected oil, which is critical for both exploration purposes and efficient cleanup operations. Today, state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI (Système Expérimental de Télédection Hyperfréquence Imageur), the airborne system developed by ONERA (the French Aerospace Lab), during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this dataset lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the EM spectrum. Specific processing techniques have been developed to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows estimating slick surface properties such as the age of the emulsion released at sea, the spatial abundance of oil and the relative concentration of hydrocarbons remaining on the sea surface. PMID:28767059

Airborne geophysics for mesoscale observations of polar sea ice in a changing climate

NASA Astrophysics Data System (ADS)

Hendricks, S.; Haas, C.; Krumpen, T.; Eicken, H.; Mahoney, A. R.

2016-12-01

Sea ice thickness is an important geophysical parameter with a significant impact on various processes of the polar energy balance. It is classified as Essential Climate Variable (ECV), however the direct observations of the large ice-covered oceans are limited due to the harsh environmental conditions and logistical constraints. Sea-ice thickness retrieval by the means of satellite remote sensing is an active field of research, but current observational capabilities are not able to capture the small scale variability of sea ice thickness and its evolution in the presence of surface melt. We present an airborne observation system based on a towed electromagnetic induction sensor that delivers long range measurements of sea ice thickness for a wide range of sea ice conditions. The purpose-built sensor equipment can be utilized from helicopters and polar research aircraft in multi-role science missions. While airborne EM induction sounding is used in sea ice research for decades, the future challenge is the development of unmanned aerial vehicle (UAV) platform that meet the requirements for low-level EM sea ice surveys in terms of range and altitude of operations. The use of UAV's could enable repeated sea ice surveys during the the polar night, when manned operations are too dangerous and the observational data base is presently very sparse.

A multi-sensor remote sensing approach for measuring primary production from space

NASA Technical Reports Server (NTRS)

Gautier, Catherine

1989-01-01

It is proposed to develop a multi-sensor remote sensing method for computing marine primary productivity from space, based on the capability to measure the primary ocean variables which regulate photosynthesis. The three variables and the sensors which measure them are: (1) downwelling photosynthetically available irradiance, measured by the VISSR sensor on the GOES satellite, (2) sea-surface temperature from AVHRR on NOAA series satellites, and (3) chlorophyll-like pigment concentration from the Nimbus-7/CZCS sensor. These and other measured variables would be combined within empirical or analytical models to compute primary productivity. With this proposed capability of mapping primary productivity on a regional scale, we could begin realizing a more precise and accurate global assessment of its magnitude and variability. Applications would include supplementation and expansion on the horizontal scale of ship-acquired biological data, which is more accurate and which supplies the vertical components of the field, monitoring oceanic response to increased atmospheric carbon dioxide levels, correlation with observed sedimentation patterns and processes, and fisheries management.

Autonomous Observational Platforms for Ocean Studies: Operation, Advantages of Sensor Technology and Data Management

NASA Astrophysics Data System (ADS)

Atamanchuk, D.; Lai, J.; Vining, M.; Kehoe, D.; Siddall, G.; Send, U.; Wallace, D.

2016-02-01

Ocean Science and Technology research group (CERC.OCEAN) at Dalhousie University focuses on new approaches in design and development of autonomous platforms to study biogeochemical and ecological changes in the world's oceans. The principal research regions included the Labrador Sea, the Northwest Atlantic between Halifax and Bermuda, and the coastal areas of Atlantic Canada. The need for improved constraints on the ocean's present and future carbon cycle is of high relevance for the Northwest Atlantic, which is recognized as a largest sink of carbon dioxide(CO2) through air-sea exchange and subsequent transport to deeper layers of the global ocean. With the use of novel sensor technology integrated into the designed platforms we are achieving a superior spatial and temporal resolution of observations. SeaCycler - a surface piercing mooring - was designed to endure year-long measurements in harsh conditions of the open ocean, like Labrador Sea, while making daily profiles of the upper 150m of the water column. Significant research efforts within CERC.OCEAN are dedicated for improving sensors' data outcome. This includes testing, calibration of the sensors, QC and postprocessing to assure reliable and trustworthy measurements. Examples and implication of the data from SeaCycler, and other platforms including buoys, and automonous Volunteer Observing Ship (VOS) flow-through system will be presented.

SSL: Signal Similarity-Based Localization for Ocean Sensor Networks.

PubMed

Chen, Pengpeng; Ma, Honglu; Gao, Shouwan; Huang, Yan

2015-11-24

Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes' positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes' positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes' relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks.

Development of an Operational Multi-sensor and Multi-channel Aerosol Assimilation Package

DTIC Science & Technology

2011-08-18

2010, EGU General Assembly 2010. Shi, Y., J. Zhang, J. S. Reid, E. Hyer, Evaluation of MISR Aerosol Optical Depth Product for Aerosol Data...empirical correction procedures for generating data-assimilation-friendly over-water MODIS aerosol products. This study has been published (Shi et al...type as large r\\ values are generally related to fine mode aerosols, such as sulfate and smoke aerosols, and small r\\ values typically indicate sea

Annual Systems Engineering Conference (9th): Focusing on Improving Performance of Defense Systems Programs. Volume 3. Wednesday

DTIC Science & Technology

2006-10-26

tte r M r. D ea n C ar ic o TR AC K 1 Sy st em s En gi ne er in g Ef fe ct iv en es s M r. Al B ro...FS S) T oo ls - PG M M Ca se S tu dy M r. D ou gl as S to rs ve d Pa tte rn L ib ra ry fo r Us e in W ea po ns S ys te m E ng in ee...Sensors Sensors Sensors Sensors Air, Land or Sea Undersea or from the Sea (C3) (C2)( ) Sensors Sensors

COCONet enhancements to circum-Caribbean tsunami warning, tidal, and sea-level monitoring: update on tide gauge installations

NASA Astrophysics Data System (ADS)

Dausz, K.; Dittmann, S. T.; Feaux, K.; von Hillebrandt-Andrade, C.; Mattioli, G. S.; Normandeau, J.

2014-12-01

The Continually Operating Caribbean GPS Observational Network (COCONet) is a National Science Foundation (NSF) funded multi-hazard geodetic and meteorological network distributed throughout the Caribbean, which provides infrastructure and capacity building for a broad range of earth science questions. The network is a multi-national collaboration consisting of 46 newly constructed continuous Global Positioning Systems (cGPS) and 21 refurbished existing GPS stations, all co-located with meteorological sensors. One recommendation of the COCONet working group was to improve the vertical reference frame for long-term sea level monitoring. A COCONet supplement was awarded by the NSF to further address this particular objective through the co-location of GPS and tide gauges. This COCOnet infrastructure, along with the new tide gauges, will have broad scientific implications for hazards mitigation, solid earth, and atmospheric science research. UNAVCO engineers have meet with members of the Caribbean tide gauge community to establish target locations and design station layout. Allocated NSF funds allow for the construction of two complete new tide gauge systems each with two complimentary cGPS. Following the recommendations of NOAA and the sea level monitoring community, the two "new" locales will be Port Royal, Jamaica and Puerto Morelos, Mexico. Both locations had previously existing, but currently non-operational tide gauges. UNAVCO engineers will install a Sutron Radar Level Recorder and a backup pressure sensor tide gauge with GOES satellite telemetry. Tide data will be freely available by the Intergovernmental Oceanographic Commission (www.ioc-sealevelmonitoring.org). The NSF supplement also provided funds for adding cGPS to two additional locations where currently functioning tide gauge systems exist. Proposed locations for this additional infrastructure are Barahona, Dominican Republic and Bocas del Toro, Panama. All four locations will feature two standard COCONet cGPS systems consisting of a Trimble Choke Ring GNSS antenna, Trimble NetR9 GPS receiver, and a Vaisala meteorological sensor. All GPS data will be collected, processed and distributed via standard COCONet archiving and processing along with raw meteorological data at coconet.unavco.org.

Multi-frequency SAR, SSM/I and AVHRR derived geophysical information of the marginal ice zone

NASA Technical Reports Server (NTRS)

Shuchman, R. A.; Onstott, R. G.; Wackerman, C. C.; Russel, C. A.; Sutherland, L. L.; Johannessen, O. M.; Johannessen, J. A.; Sandven, S.; Gloerson, P.

1991-01-01

A description is given of the fusion of synthetic aperture radar (SAR), special sensor microwave imager (SSM/I), and NOAA Advanced Very High Resolution Radiometer (AVHRR) data to study arctic processes. These data were collected during the SIZEX/CEAREX experiments that occurred in the Greenland Sea in March of 1989. Detailed comparisons between the SAR, AVHRR, and SSM/I indicated: (1) The ice edge position was in agreement to within 25 km, (2) The SSM/I SAR total ice concentration compared favorably, however, the SSM/I significantly underpredicted the multiyear fraction, (3) Combining high resolution SAR with SSM/I can potentially map open water and new ice features in the marginal ice zone (MIZ) which cannot be mapped by the single sensors, and (4) The combination of all three sensors provides accurate ice information as well as sea surface temperature and wind speeds.

Aerosol Climate Time Series in ESA Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, Thomas; de Leeuw, Gerrit; Pinnock, Simon

2016-04-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve algorithms for the retrieval of aerosol information from European sensors. Meanwhile, full mission time series of 2 GCOS-required aerosol parameters are completely validated and released: Aerosol Optical Depth (AOD) from dual view ATSR-2 / AATSR radiometers (3 algorithms, 1995 - 2012), and stratospheric extinction profiles from star occultation GOMOS spectrometer (2002 - 2012). Additionally, a 35-year multi-sensor time series of the qualitative Absorbing Aerosol Index (AAI) together with sensitivity information and an AAI model simulator is available. Complementary aerosol properties requested by GCOS are in a "round robin" phase, where various algorithms are inter-compared: fine mode AOD, mineral dust AOD (from the thermal IASI spectrometer, but also from ATSR instruments and the POLDER sensor), absorption information and aerosol layer height. As a quasi-reference for validation in few selected regions with sparse ground-based observations the multi-pixel GRASP algorithm for the POLDER instrument is used. Validation of first dataset versions (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account for a reprocessing. The datasets contain pixel level uncertainty estimates which were also validated and improved in the reprocessing. For the three ATSR algorithms the use of an ensemble method was tested. The paper will summarize and discuss the status of dataset reprocessing and validation. The focus will be on the ATSR, GOMOS and IASI datasets. Pixel level uncertainties validation will be summarized and discussed including unknown components and their potential usefulness and limitations. Opportunities for time series extension with successor instruments of the Sentinel family will be described and the complementarity of the different satellite aerosol products (e.g. dust vs. total AOD, ensembles from different algorithms for the same sensor) will be discussed.

Airborne net-centric multi-INT sensor control, display, fusion, and exploitation systems

NASA Astrophysics Data System (ADS)

Linne von Berg, Dale C.; Lee, John N.; Kruer, Melvin R.; Duncan, Michael D.; Olchowski, Fred M.; Allman, Eric; Howard, Grant

2004-08-01

The NRL Optical Sciences Division has initiated a multi-year effort to develop and demonstrate an airborne net-centric suite of multi-intelligence (multi-INT) sensors and exploitation systems for real-time target detection and targeting product dissemination. The goal of this Net-centric Multi-Intelligence Fusion Targeting Initiative (NCMIFTI) is to develop an airborne real-time intelligence gathering and targeting system that can be used to detect concealed, camouflaged, and mobile targets. The multi-INT sensor suite will include high-resolution visible/infrared (EO/IR) dual-band cameras, hyperspectral imaging (HSI) sensors in the visible-to-near infrared, short-wave and long-wave infrared (VNIR/SWIR/LWIR) bands, Synthetic Aperture Radar (SAR), electronics intelligence sensors (ELINT), and off-board networked sensors. Other sensors are also being considered for inclusion in the suite to address unique target detection needs. Integrating a suite of multi-INT sensors on a single platform should optimize real-time fusion of the on-board sensor streams, thereby improving the detection probability and reducing the false alarms that occur in reconnaissance systems that use single-sensor types on separate platforms, or that use independent target detection algorithms on multiple sensors. In addition to the integration and fusion of the multi-INT sensors, the effort is establishing an open-systems net-centric architecture that will provide a modular "plug and play" capability for additional sensors and system components and provide distributed connectivity to multiple sites for remote system control and exploitation.

Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network

PubMed Central

Lin, Kai; Wang, Di; Hu, Long

2016-01-01

With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC). The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S) evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods. PMID:27376302

Variation of Arctic's Sea-ice Albedo between 2000 and 2016 by fusion of MISR and MODIS data

NASA Astrophysics Data System (ADS)

Muller, Jan-Peter; Kharbouche, Said

2017-04-01

Many research studies have demonstrated that sea-ice plays a key role in climate change and global warming. Most of these studies are based either on ground in-situ data or on remotely sensed data. The latter data are provided mainly by active (SAR and LiDAR) sensors such as Cryosat2, ERS1/2, ENVISAT, Radarsat1/2, ICESat as well as passive sensors such as SSM/I. Nevertheless, the contribution of such active optical sensors data is limited to parameters such as thickness and sea-ice concentration from which albedo may be inferred. The creation of high quality albedo for sea-ice using optical satellites is confronted with two main obstacles: 1) the Arctic is a very cloudy region and, high quality albedo requires multi-angle observations over a relatively short period; 2) cloud masking over sea-ice is a very difficult task, especially for sensor with low spectral resolution. To overcome the above two obstacles, we discuss in a separate report the generation of this fused daily, weekly, fortnightly and monthly product at 1km and 5km resolution on a polar stereographic grid [1]. The limited swath (380km) of MISR means that not all of the Arctic is covered on a daily basis so composites on different time-steps were produced. The results show that sea-ice albedo has been in continuous decline since 2000 with thinner sea-ice and greater leads and open water as well as more ponding at earlier times in the year. The implications of these results are discussed in terms of the sea-ice climate feedback. Animated visualisations of the albedo patterns each year, the decline in average and the increase in standard deviation in albedo for every single day for all 17 years will be shown to demonstrate the effects of climate change over sea-ice albedo. References [1] Kharbouche & Muller, Production of Arctic sea-ice albedo by fusion of MISR and MODIS data. This conference. Acknowledgements This work was supported by www.QA4ECV.eu, a project of European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 607405.

Energy Efficient Real-Time Scheduling Using DPM on Mobile Sensors with a Uniform Multi-Cores

PubMed Central

Kim, Youngmin; Lee, Chan-Gun

2017-01-01

In wireless sensor networks (WSNs), sensor nodes are deployed for collecting and analyzing data. These nodes use limited energy batteries for easy deployment and low cost. The use of limited energy batteries is closely related to the lifetime of the sensor nodes when using wireless sensor networks. Efficient-energy management is important to extending the lifetime of the sensor nodes. Most effort for improving power efficiency in tiny sensor nodes has focused mainly on reducing the power consumed during data transmission. However, recent emergence of sensor nodes equipped with multi-cores strongly requires attention to be given to the problem of reducing power consumption in multi-cores. In this paper, we propose an energy efficient scheduling method for sensor nodes supporting a uniform multi-cores. We extend the proposed T-Ler plane based scheduling for global optimal scheduling of a uniform multi-cores and multi-processors to enable power management using dynamic power management. In the proposed approach, processor selection for a scheduling and mapping method between the tasks and processors is proposed to efficiently utilize dynamic power management. Experiments show the effectiveness of the proposed approach compared to other existing methods. PMID:29240695

Improved particle swarm optimization algorithm for android medical care IOT using modified parameters.

PubMed

Sung, Wen-Tsai; Chiang, Yen-Chun

2012-12-01

This study examines wireless sensor network with real-time remote identification using the Android study of things (HCIOT) platform in community healthcare. An improved particle swarm optimization (PSO) method is proposed to efficiently enhance physiological multi-sensors data fusion measurement precision in the Internet of Things (IOT) system. Improved PSO (IPSO) includes: inertia weight factor design, shrinkage factor adjustment to allow improved PSO algorithm data fusion performance. The Android platform is employed to build multi-physiological signal processing and timely medical care of things analysis. Wireless sensor network signal transmission and Internet links allow community or family members to have timely medical care network services.

An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph

PubMed Central

Zeng, Qinghua; Chen, Weina; Liu, Jianye; Wang, Huizhe

2017-01-01

An integrated navigation system coupled with additional sensors can be used in the Micro Unmanned Aerial Vehicle (MUAV) applications because the multi-sensor information is redundant and complementary, which can markedly improve the system accuracy. How to deal with the information gathered from different sensors efficiently is an important problem. The fact that different sensors provide measurements asynchronously may complicate the processing of these measurements. In addition, the output signals of some sensors appear to have a non-linear character. In order to incorporate these measurements and calculate a navigation solution in real time, the multi-sensor fusion algorithm based on factor graph is proposed. The global optimum solution is factorized according to the chain structure of the factor graph, which allows for a more general form of the conditional probability density. It can convert the fusion matter into connecting factors defined by these measurements to the graph without considering the relationship between the sensor update frequency and the fusion period. An experimental MUAV system has been built and some experiments have been performed to prove the effectiveness of the proposed method. PMID:28335570

An Improved Multi-Sensor Fusion Navigation Algorithm Based on the Factor Graph.

PubMed

Zeng, Qinghua; Chen, Weina; Liu, Jianye; Wang, Huizhe

2017-03-21

An integrated navigation system coupled with additional sensors can be used in the Micro Unmanned Aerial Vehicle (MUAV) applications because the multi-sensor information is redundant and complementary, which can markedly improve the system accuracy. How to deal with the information gathered from different sensors efficiently is an important problem. The fact that different sensors provide measurements asynchronously may complicate the processing of these measurements. In addition, the output signals of some sensors appear to have a non-linear character. In order to incorporate these measurements and calculate a navigation solution in real time, the multi-sensor fusion algorithm based on factor graph is proposed. The global optimum solution is factorized according to the chain structure of the factor graph, which allows for a more general form of the conditional probability density. It can convert the fusion matter into connecting factors defined by these measurements to the graph without considering the relationship between the sensor update frequency and the fusion period. An experimental MUAV system has been built and some experiments have been performed to prove the effectiveness of the proposed method.

Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

Improved Sensitivity Spontaneous Raman Scattering Multi-Gas Sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buric, Michael P.; Chen, Kevin P.; Falk, Joel

2009-01-01

We report a backward-wave spontaneous-Raman multi-gas sensor employing a hollow-core photonic-bandgap-fiber to contain gasses and increase interaction length. Silica Raman noise and detection speed are reduced using a digital spatial filter and a cladding seal.

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association

PubMed Central

Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-01-01

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets’ state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems. PMID:29113085

Centralized Multi-Sensor Square Root Cubature Joint Probabilistic Data Association.

PubMed

Liu, Yu; Liu, Jun; Li, Gang; Qi, Lin; Li, Yaowen; He, You

2017-11-05

This paper focuses on the tracking problem of multiple targets with multiple sensors in a nonlinear cluttered environment. To avoid Jacobian matrix computation and scaling parameter adjustment, improve numerical stability, and acquire more accurate estimated results for centralized nonlinear tracking, a novel centralized multi-sensor square root cubature joint probabilistic data association algorithm (CMSCJPDA) is proposed. Firstly, the multi-sensor tracking problem is decomposed into several single-sensor multi-target tracking problems, which are sequentially processed during the estimation. Then, in each sensor, the assignment of its measurements to target tracks is accomplished on the basis of joint probabilistic data association (JPDA), and a weighted probability fusion method with square root version of a cubature Kalman filter (SRCKF) is utilized to estimate the targets' state. With the measurements in all sensors processed CMSCJPDA is derived and the global estimated state is achieved. Experimental results show that CMSCJPDA is superior to the state-of-the-art algorithms in the aspects of tracking accuracy, numerical stability, and computational cost, which provides a new idea to solve multi-sensor tracking problems.

SeaWiFS calibration and validation plan, volume 3

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Mcclain, Charles R.; Esaias, Wayne E.; Barnes, William; Guenther, Bruce; Endres, Daniel; Mitchell, B. Greg; Barnes, Robert

1992-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) will be the first ocean-color satellite since the Nimbus-7 Coastal Zone Color Scanner (CZCS), which ceased operation in 1986. Unlike the CZCS, which was designed as a proof-of-concept experiment, SeaWiFS will provide routine global coverage every 2 days and is designed to provide estimates of photosynthetic concentrations of sufficient accuracy for use in quantitative studies of the ocean's primary productivity and biogeochemistry. A review of the CZCS mission is included that describes that data set's limitations and provides justification for a comprehensive SeaWiFS calibration and validation program. To accomplish the SeaWiFS scientific objectives, the sensor's calibration must be constantly monitored, and robust atmospheric corrections and bio-optical algorithms must be developed. The plan incorporates a multi-faceted approach to sensor calibration using a combination of vicarious (based on in situ observations) and onboard calibration techniques. Because of budget constraints and the limited availability of ship resources, the development of the operational algorithms (atmospheric and bio-optical) will rely heavily on collaborations with the Earth Observing System (EOS), the Moderate Resolution Imaging Spectrometer (MODIS) oceans team, and projects sponsored by other agencies, e.g., the U.S. Navy and the National Science Foundation (NSF). Other elements of the plan include the routine quality control of input ancillary data (e.g., surface wind, surface pressure, ozone concentration, etc.) used in the processing and verification of the level-0 (raw) data to level-1 (calibrated radiances), level-2 (derived products), and level-3 (gridded and averaged derived data) products.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.

PubMed

Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan

2018-02-02

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

PubMed Central

2018-01-01

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. PMID:29393884

Laser Altimetry Sampling Strategies over Sea Ice

NASA Technical Reports Server (NTRS)

Farrell, Sinead L.; Markus, Thorsten; Kwok, Ron; Connor, Laurence

2011-01-01

With the conclusion of the science phase of the Ice, Cloud and land Elevation Satellite (ICESat) mission in late 2009, and the planned launch of ICESat-2 in late 2015, NASA has recently established the IceBridge program to provide continuity between missions. A major goal of IceBridge is to obtain a sea-ice thickness time series via airborne surveys over the Arctic and Southern Oceans. Typically two laser altimeters, the Airborne Topographic Mapper (ATM) and the Land, Vegetation and Ice Sensor (LVIS), are utilized during IceBridge flights. Using laser altimetry simulations of conventional analogue systems such as ICESat, LVIS and ATM, with the multi-beam system proposed for ICESat-2, we investigate differences in measurements gathered at varying spatial resolutions and the impact on sea-ice freeboard. We assess the ability of each system to reproduce the elevation distributions of two seaice models and discuss potential biases in lead detection and sea-surface elevation, arising from variable footprint size and spacing. The conventional systems accurately reproduce mean freeboard over 25km length scales, while ICESat-2 offers considerable improvements over its predecessor ICESat. In particular, its dense along-track sampling of the surface will allow flexibility in the algorithmic approaches taken to optimize the signal-to-noise ratio for accurate and precise freeboard retrieval.

Satellite-Derived Sea Surface Temperature: Workshop-2

NASA Technical Reports Server (NTRS)

Njoku, E. G.

1984-01-01

Global accuracies and error characteristics of presently orbiting satellite sensors are examined. The workshops are intended to lead to a better understanding of present capabilities for sea surface temperature measurement and to improve measurement concepts for the future. Data from the Advanced Very High Resolution Radiometer AVHRR and Scanning Multichannel Microwave Radiometer is emphasized. Some data from the High Resolution Infrared Sounder HIRS and AVHRR are also examined. Comparisons of satellite data with ship and eXpendable BathyThermograph XBT measurement show standard deviations in the range 0.5 to 1.3 C with biases of less than 0.4 C, depending on the sensor, ocean region, and spatial/temporal averaging. The Sea Surface Temperature SST anomaly maps show good agreement in some cases, but a number of sensor related problems are identified.

PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter.

PubMed

Li, Xiaohua; Li, Yaan; Yu, Jing; Chen, Xiao; Dai, Miao

2015-11-06

Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low.

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Petrenko, M.; Ichoku, C.

2013-01-01

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.

Net community production from autonomous oxygen observations in the Sargasso Sea

NASA Astrophysics Data System (ADS)

Feen, M.; Estapa, M. L.

2016-02-01

Optical sensors on autonomous floats provide high-resolution profiles of oxygen concentration over time. Improved spatiotemporal resolution in our measurements of oxygen will allow for better estimates of net community production and a greater understanding of the biological pump. Two autonomous profiling floats (NAVIS BGCi, Sea-Bird) equipped with SBE-63 optodes to measure dissolved oxygen were deployed in the Sargasso Sea on a series of five Bermuda Atlantic Time-series Study (BATS) cruises from July 2013 to April 2014. In situ calibration of the oxygen sensors to Winkler titration bottle samples at BATS did not show systematic drift in the oxygen sensors over time. Calibrations were applied to determine oxygen concentrations in profiles collected in the Sargasso Sea at 1.5 to 2.5 day intervals over a year. Oxygen concentrations were used to quantify sub-mixed layer net community production. Changes in production rates from this study were compared with upper water column biology and particle flux measurements obtained independently from optical sensors on the profiling floats, allowing us to examine processes controlling carbon export into the deep ocean.

Shallow water bathymetry correction using sea bottom classification with multispectral satellite imagery

NASA Astrophysics Data System (ADS)

Kazama, Yoriko; Yamamoto, Tomonori

2017-10-01

Bathymetry at shallow water especially shallower than 15m is an important area for environmental monitoring and national defense. Because the depth of shallow water is changeable by the sediment deposition and the ocean waves, the periodic monitoring at shoe area is needed. Utilization of satellite images are well matched for widely and repeatedly monitoring at sea area. Sea bottom terrain model using by remote sensing data have been developed and these methods based on the radiative transfer model of the sun irradiance which is affected by the atmosphere, water, and sea bottom. We adopted that general method of the sea depth extraction to the satellite imagery, WorldView-2; which has very fine spatial resolution (50cm/pix) and eight bands at visible to near-infrared wavelengths. From high-spatial resolution satellite images, there is possibility to know the coral reefs and the rock area's detail terrain model which offers important information for the amphibious landing. In addition, the WorldView-2 satellite sensor has the band at near the ultraviolet wavelength that is transmitted through the water. On the other hand, the previous study showed that the estimation error by the satellite imagery was related to the sea bottom materials such as sand, coral reef, sea alga, and rocks. Therefore, in this study, we focused on sea bottom materials, and tried to improve the depth estimation accuracy. First, we classified the sea bottom materials by the SVM method, which used the depth data acquired by multi-beam sonar as supervised data. Then correction values in the depth estimation equation were calculated applying the classification results. As a result, the classification accuracy of sea bottom materials was 93%, and the depth estimation error using the correction by the classification result was within 1.2m.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation.

PubMed

Tkach, Itshak; Jevtić, Aleksandar; Nof, Shimon Y; Edan, Yael

2018-03-02

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors' performance, tasks' priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems.

Navigation Algorithms for the SeaWiFS Mission

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Patt, Frederick S.; McClain, Charles R. (Technical Monitor)

2002-01-01

The navigation algorithms for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) were designed to meet the requirement of 1-pixel accuracy-a standard deviation (sigma) of 2. The objective has been to extract the best possible accuracy from the spacecraft telemetry and avoid the need for costly manual renavigation or geometric rectification. The requirement is addressed by postprocessing of both the Global Positioning System (GPS) receiver and Attitude Control System (ACS) data in the spacecraft telemetry stream. The navigation algorithms described are separated into four areas: orbit processing, attitude sensor processing, attitude determination, and final navigation processing. There has been substantial modification during the mission of the attitude determination and attitude sensor processing algorithms. For the former, the basic approach was completely changed during the first year of the mission, from a single-frame deterministic method to a Kalman smoother. This was done for several reasons: a) to improve the overall accuracy of the attitude determination, particularly near the sub-solar point; b) to reduce discontinuities; c) to support the single-ACS-string spacecraft operation that was started after the first mission year, which causes gaps in attitude sensor coverage; and d) to handle data quality problems (which became evident after launch) in the direct-broadcast data. The changes to the attitude sensor processing algorithms primarily involved the development of a model for the Earth horizon height, also needed for single-string operation; the incorporation of improved sensor calibration data; and improved data quality checking and smoothing to handle the data quality issues. The attitude sensor alignments have also been revised multiple times, generally in conjunction with the other changes. The orbit and final navigation processing algorithms have remained largely unchanged during the mission, aside from refinements to data quality checking. Although further improvements are certainly possible, future evolution of the algorithms is expected to be limited to refinements of the methods presented here, and no substantial changes are anticipated.

Oil Spill AISA+ Hyperspectral Data Detection Based on Different Sea Surface Glint Suppression Methods

NASA Astrophysics Data System (ADS)

Yang, J.; Ren, G.; Ma, Y.; Dong, L.; Wan, J.

2018-04-01

The marine oil spill is a sudden event, and the airborne hyperspectral means to detect the oil spill is an important part of the rapid response. Sun glint, the specular reflection of sun light from water surface to sensor, is inevitable due to the limitation of observation geometry, which makes so much bright glint in image that it is difficult to extract oil spill feature information from the remote sensing data. This paper takes AISA+ airborne hyperspectral oil spill image as data source, using multi-scale wavelet transform, enhanced Lee filter, enhanced Frost filter and mean filter method for sea surface glint suppression of images. And then the classical SVM method is used for the oil spill information detection, and oil spill information distribution map obtained by human-computer interactive interpretation is used to verify the accuracy of oil spill detection. The results show that the above methods can effectively suppress the sea surface glints and improve the accuracy of oil spill detection. The enhanced Lee filter method has the highest detection accuracy of 88.28 %, which is 12.2 % higher than that of the original image.

Seafloor image survey of Juk-byeon port in Uljin, South Korea, using side scan sonar with a fixed long frame

NASA Astrophysics Data System (ADS)

Kim, W. H.; Park, C.; Lee, M.; Park, H. Y.; Kim, C.

2015-12-01

A side scan sonar launches ultrasonic wave from both sides of the transducer. And it restores the image by receiving signals. It measures the strength of how "loud" the return echo is, and paints a picture. Hard areas of the sea floor like rocks reflect more return signal than softer areas like sand. We conducted seafloor image survey from 4, Mar. 2013 using R/V Jangmok2 (35ton), side scan sonar 4125 (Edge Tech corporation). The side scan sonar system (4125) is a dual frequency system of 400/900kHz. Seafloor image survey is commonly used to tow the sensor in the rear side of vessel. However, we fixed the tow-fish on right side of the vessel in the seawater with a long frame. The mounted side scan sonar survey was useful in shallow water like the port having many obstacles. And we conducted submarine topography using multi-beam echo sounder EM3001 (Kongs-berg corporation). Multi-beam echo sounder is a device for observing and recording the submarine topography using sound. We mounted the EM3001 on right side of the vessel. Multi-beam echo sounder transducer commonly to mount at right angles to the surface of water. However, we tilted 20-degrees of transducer for long range with 85-degrees measurement on the right side of the vessel. We were equipped with a motion sensor, DGPS(Differential Global Positioning System), and SV(Sound velocity) sensor for the vessel's motion compensation, vessel's position, and the velocity of sound of seawater. The surveys showed the sediment, waste materials, and a lot of discarded tires accumulated in the port. The maximum depth was 12m in the port. Such multi-beam echo sounder survey and side scan sonar survey will facilitate the management and the improvement of environment of port.

Hybrid optical acoustic seafloor mapping

NASA Astrophysics Data System (ADS)

Inglis, Gabrielle

The oceanographic research and industrial communities have a persistent demand for detailed three dimensional sea floor maps which convey both shape and texture. Such data products are used for archeology, geology, ship inspection, biology, and habitat classification. There are a variety of sensing modalities and processing techniques available to produce these maps and each have their own potential benefits and related challenges. Multibeam sonar and stereo vision are such two sensors with complementary strengths making them ideally suited for data fusion. Data fusion approaches however, have seen only limited application to underwater mapping and there are no established methods for creating hybrid, 3D reconstructions from two underwater sensing modalities. This thesis develops a processing pipeline to synthesize hybrid maps from multi-modal survey data. It is helpful to think of this processing pipeline as having two distinct phases: Navigation Refinement and Map Construction. This thesis extends existing work in underwater navigation refinement by incorporating methods which increase measurement consistency between both multibeam and camera. The result is a self consistent 3D point cloud comprised of camera and multibeam measurements. In map construction phase, a subset of the multi-modal point cloud retaining the best characteristics of each sensor is selected to be part of the final map. To quantify the desired traits of a map several characteristics of a useful map are distilled into specific criteria. The different ways that hybrid maps can address these criteria provides justification for producing them as an alternative to current methodologies. The processing pipeline implements multi-modal data fusion and outlier rejection with emphasis on different aspects of map fidelity. The resulting point cloud is evaluated in terms of how well it addresses the map criteria. The final hybrid maps retain the strengths of both sensors and show significant improvement over the single modality maps and naively assembled multi-modal maps.

A Modified Distributed Bees Algorithm for Multi-Sensor Task Allocation †

PubMed Central

Nof, Shimon Y.; Edan, Yael

2018-01-01

Multi-sensor systems can play an important role in monitoring tasks and detecting targets. However, real-time allocation of heterogeneous sensors to dynamic targets/tasks that are unknown a priori in their locations and priorities is a challenge. This paper presents a Modified Distributed Bees Algorithm (MDBA) that is developed to allocate stationary heterogeneous sensors to upcoming unknown tasks using a decentralized, swarm intelligence approach to minimize the task detection times. Sensors are allocated to tasks based on sensors’ performance, tasks’ priorities, and the distances of the sensors from the locations where the tasks are being executed. The algorithm was compared to a Distributed Bees Algorithm (DBA), a Bees System, and two common multi-sensor algorithms, market-based and greedy-based algorithms, which were fitted for the specific task. Simulation analyses revealed that MDBA achieved statistically significant improved performance by 7% with respect to DBA as the second-best algorithm, and by 19% with respect to Greedy algorithm, which was the worst, thus indicating its fitness to provide solutions for heterogeneous multi-sensor systems. PMID:29498683

Path homogeneity along a horizontal line-of-sight path during the FESTER experiment: first results

NASA Astrophysics Data System (ADS)

Gunter, W. H.; Maritz, B.; Koago, M.; Wainman, C. K.; Gardener, M. E.; February, F.; van Eijk, A. M. J.

2016-10-01

The First European South African Experiment (FESTER) was conducted over about a 10 month period at the Institute of Maritime Technology (IMT) in False Bay, South Africa. One of the important goals was the establishment of the air-sea temperature difference (ASTD) homogeneity along the main propagation link atmospheric path since it is a basic assumption for most of the atmospheric turbulence models (caused by refractive index variations). The ASTD was measured from a small scientific work boat (called Sea Lab) moving along a straight in- and outbound track along the main propagation link path. The air temperature on-board was measured using standard weather sensors, while the sea surface temperature was measured using a long wavelength infrared radiometer, which was compared to the bulk sea temperature half a meter below the sea surface. This was obtained by an under water temperature sensor mounted on a `surfboard' that was towed alongside Sea Lab. Vertical water temperature profiles were also measured along the main propagation path in order to determine the depth of the surface mixed layer and thermocline using a Conductivity Temperature Depth profiler (CTD). First results investigated the ASTD variation along the horizontal line-of-sight path used by the principal electro-optic transmission link monitoring equipment (i.e. scintillometer and multi-spectral radiometer-transmissometer system).

Multi-Satellite Synergy for Aerosol Analysis in the Asian Monsoon Region

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Petrenko, Maksym

2012-01-01

Atmospheric aerosols represent one of the greatest uncertainties in environmental and climate research, particularly in tropical monsoon regions such as the Southeast Asian regions, where significant contributions from a variety of aerosol sources and types is complicated by unstable atmospheric dynamics. Although aerosols are now routinely retrieved from multiple satellite Sensors, in trying to answer important science questions about aerosol distribution, properties, and impacts, researchers often rely on retrievals from only one or two sensors, thereby running the risk of incurring biases due to sensor/algorithm peculiarities. We are conducting detailed studies of aerosol retrieval uncertainties from various satellite sensors (including Terra-/ Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, SeaWiFS, and Calipso-CALIOP), based on the collocation of these data products over AERONET and other important ground stations, within the online Multi-sensor Aerosol Products Sampling System (MAPSS) framework that was developed recently. Such analyses are aimed at developing a synthesis of results that can be utilized in building reliable unified aerosol information and climate data records from multiple satellite measurements. In this presentation, we will show preliminary results of. an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors, particularly focused on the Asian Monsoon region, along with some comparisons from the African Monsoon region.

A glimpse beneath Antarctic sea ice: observation of platelet-layer thickness and ice-volume fraction with multifrequency EM

NASA Astrophysics Data System (ADS)

Hoppmann, Mario; Hunkeler, Priska A.; Hendricks, Stefan; Kalscheuer, Thomas; Gerdes, Rüdiger

2016-04-01

In Antarctica, ice crystals (platelets) form and grow in supercooled waters below ice shelves. These platelets rise, accumulate beneath nearby sea ice, and subsequently form a several meter thick, porous sub-ice platelet layer. This special ice type is a unique habitat, influences sea-ice mass and energy balance, and its volume can be interpreted as an indicator of the health of an ice shelf. Although progress has been made in determining and understanding its spatio-temporal variability based on point measurements, an investigation of this phenomenon on a larger scale remains a challenge due to logistical constraints and a lack of suitable methodology. In the present study, we applied a lateral constrained Marquardt-Levenberg inversion to a unique multi-frequency electromagnetic (EM) induction sounding dataset obtained on the ice-shelf influenced fast-ice regime of Atka Bay, eastern Weddell Sea. We adapted the inversion algorithm to incorporate a sensor specific signal bias, and confirmed the reliability of the algorithm by performing a sensitivity study using synthetic data. We inverted the field data for sea-ice and platelet-layer thickness and electrical conductivity, and calculated ice-volume fractions within the platelet layer using Archie's Law. The thickness results agreed well with drillhole validation datasets within the uncertainty range, and the ice-volume fraction yielded results comparable to other studies. Both parameters together enable an estimation of the total ice volume within the platelet layer, which was found to be comparable to the volume of landfast sea ice in this region, and corresponded to more than a quarter of the annual basal melt volume of the nearby Ekström Ice Shelf. Our findings show that multi-frequency EM induction sounding is a suitable approach to efficiently map sea-ice and platelet-layer properties, with important implications for research into ocean/ice-shelf/sea-ice interactions. However, a successful application of this technique requires a break with traditional EM sensor calibration strategies due to the need of absolute calibration with respect to a physical forward model.

Multi-Sensor Characterization of the Boreal Forest: Initial Findings

NASA Technical Reports Server (NTRS)

Reith, Ernest; Roberts, Dar A.; Prentiss, Dylan

2001-01-01

Results are presented in an initial apriori knowledge approach toward using complementary multi-sensor multi-temporal imagery in characterizing vegetated landscapes over a site in the Boreal Ecosystem-Atmosphere Study (BOREAS). Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data were segmented using multiple endmember spectral mixture analysis and binary decision tree approaches. Individual date/sensor land cover maps had overall accuracies between 55.0% - 69.8%. The best eight land cover layers from all dates and sensors correctly characterized 79.3% of the cover types. An overlay approach was used to create a final land cover map. An overall accuracy of 71.3% was achieved in this multi-sensor approach, a 1.5% improvement over our most accurate single scene technique, but 8% less than the original input. Black spruce was evaluated to be particularly undermapped in the final map possibly because it was also contained within jack pine and muskeg land coverages.

Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes.

PubMed

Prasad, Dilip K; Agarwal, Krishna

2016-03-22

We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds). The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS), moderate-resolution imaging spectroradiometer (MODIS), sea-viewing wide field-of-view sensor (SeaWiFS), coastal zone color scanner (CZCS), ocean and land colour instrument (OLCI), and visible infrared imaging radiometer suite (VIIRS) sensors. Results are also shown for CIMEL's SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included.

The multi-channel infrared sea truth radiometric calibrator (MISTRC)

USGS Publications Warehouse

Suarez, M.J.; Emery, W. J.; Wick, G.A.

1997-01-01

A new multichannel infrared sea truth radiometer has been designed and built to improve validation of satellite-determined sea surface temperature. Horizontal grid polarized filters installed on the shortwave channels are very effective in reducing reflected solar radiation and in improving the noise characteristics. The system uses a continuous (every other cycle) seawater calibration technique. An analysis of the data from its first deployment is presented and recommendations are made for further improving the experimental method.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Sea ice type dynamics in the Arctic based on Sentinel-1 Data

NASA Astrophysics Data System (ADS)

Babiker, Mohamed; Korosov, Anton; Park, Jeong-Won

2017-04-01

Sea ice observation from satellites has been carried out for more than four decades and is one of the most important applications of EO data in operational monitoring as well as in climate change studies. Several sensors and retrieval methods have been developed and successfully utilized to measure sea ice area, concentration, drift, type, thickness, etc [e.g. Breivik et al., 2009]. Today operational sea ice monitoring and analysis is fully dependent on use of satellite data. However, new and improved satellite systems, such as multi-polarisation Synthetic Apperture Radar (SAR), require further studies to develop more advanced and automated sea ice monitoring methods. In addition, the unprecedented volume of data available from recently launched Sentinel missions provides both challenges and opportunities for studying sea ice dynamics. In this study we investigate sea ice type dynamics in the Fram strait based on Sentinel-1 A, B SAR data. Series of images for the winter season are classified into 4 ice types (young ice, first year ice, multiyear ice and leads) using the new algorithm developed by us for sea ice classification, which is based on segmentation, GLCM calculation, Haralick texture feature extraction, unsupervised and supervised classifications and Support Vector Machine (SVM) [Zakhvatkina et al., 2016; Korosov et al., 2016]. This algorithm is further improved by applying thermal and scalloping noise removal [Park et al. 2016]. Sea ice drift is retrieved from the same series of Sentinel-1 images using the newly developed algorithm based on combination of feature tracking and pattern matching [Mukenhuber et al., 2016]. Time series of these two products (sea ice type and sea ice drift) are combined in order to study sea ice deformation processes at small scales. Zones of sea ice convergence and divergence identified from sea ice drift are compared with ridges and leads identified from texture features. That allows more specific interpretation of SAR imagery and more accurate automatic classification. In addition, the map of four ice types calculated using the texture features from one SAR image is propagated forward using the sea ice drift vectors. The propagated ice type is compared with ice type derived from the next image. The comparison identifies changes in ice type which occurred during drift and allows to reduce uncertainties in sea ice type calculation.

Integrated multi-sensor package (IMSP) for unmanned vehicle operations

NASA Astrophysics Data System (ADS)

Crow, Eddie C.; Reichard, Karl; Rogan, Chris; Callen, Jeff; Seifert, Elwood

2007-10-01

This paper describes recent efforts to develop integrated multi-sensor payloads for small robotic platforms for improved operator situational awareness and ultimately for greater robot autonomy. The focus is on enhancements to perception through integration of electro-optic, acoustic, and other sensors for navigation and inspection. The goals are to provide easier control and operation of the robot through fusion of multiple sensor outputs, to improve interoperability of the sensor payload package across multiple platforms through the use of open standards and architectures, and to reduce integration costs by embedded sensor data processing and fusion within the sensor payload package. The solutions investigated in this project to be discussed include: improved capture, processing and display of sensor data from multiple, non-commensurate sensors; an extensible architecture to support plug and play of integrated sensor packages; built-in health, power and system status monitoring using embedded diagnostics/prognostics; sensor payload integration into standard product forms for optimized size, weight and power; and the use of the open Joint Architecture for Unmanned Systems (JAUS)/ Society of Automotive Engineers (SAE) AS-4 interoperability standard. This project is in its first of three years. This paper will discuss the applicability of each of the solutions in terms of its projected impact to reducing operational time for the robot and teleoperator.

Timely detection and monitoring of oil leakage by satellite optical data.

NASA Astrophysics Data System (ADS)

Grimaldi, C. S. L.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

2009-04-01

Sea oil pollution can derive from different sources. Accidental release of oil into the oceans caused by "human errors" (tankers collisions and/or shipwrecks) or natural hazards (hurricanes, landslides, earthquakes) have remarkable ecological impact on maritime and coastal environments. Katrina Hurricane, for example, hitting oil and gas infrastructures off USA coasts caused the destruction of more than 100 platforms and the release into the sea of more than 10,000 gallons of crude oil. In order to reduce the environmental impact of such kind of technological hazards, timely detection and continuously updated information are fundamental. Satellite remote sensing can give a significant contribution in such a direction. Nowadays, SAR (Synthetic Aperture Radar) technology has been recognized as the most efficient for oil spill detection and mapping, thanks to the high spatial resolution and all-time/weather capability of the present operational sensors. Anyway, due to their current revisiting cycles, SAR systems cannot be profitably used for a rapid detection and for a continuous and near real-time monitoring of these phenomena. Until COSMO-Skymed SAR constellation, that will be able to improve SAR observational frequency, will not be fully operational, passive optical sensors on board meteorological satellites, thanks to their high temporal resolution, may represent a suitable alternative for early detection and continuous monitoring of oil spills, provided that adequate and reliable data analysis techniques exist. Recently, an innovative technique for oil spill detection and monitoring, based on the general Robust Satellite Techniques (RST) approach, has been proposed. It exploits the multi-temporal analysis of optical data acquired by both AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) sensors in order to detect, automatically and timely, the presence of oil spill over the sea surface, trying to minimize the "false-detections" possibly caused by spurious effects (e.g. clouds). In this paper, preliminary results obtained applying the proposed methodology to different test-cases are shown and discussed.

ASTER's First Views of Red Sea, Ethiopia - Thermal-Infrared (TIR) Image (monochrome)

NASA Technical Reports Server (NTRS)

2000-01-01

ASTER succeeded in acquiring this image at night, which is something Visible/Near Infrared VNIR) and Shortwave Infrared (SWIR) sensors cannot do. The scene covers the Red Sea coastline to an inland area of Ethiopia. White pixels represent areas with higher temperature material on the surface, while dark pixels indicate lower temperatures. This image shows ASTER's ability as a highly sensitive, temperature-discerning instrument and the first spaceborne TIR multi-band sensor in history.

The size of image: 60 km x 60 km approx., ground resolution 90 m x 90 m approximately.

The ASTER instrument was built in Japan for the Ministry of International Trade and Industry. A joint United States/Japan Science Team is responsible for instrument design, calibration, and data validation. ASTER is flying on the Terra satellite, which is managed by NASA's Goddard Space Flight Center, Greenbelt, MD.

Differential multi-MOSFET nuclear radiation sensor

NASA Technical Reports Server (NTRS)

Deoliveira, W. A.

1977-01-01

Circuit allows minimization of thermal-drift errors, low power consumption, operation over wide dynamic range, improved sensitivity and stability with metaloxide-semiconductor field-effect transistor sensors.

What is going on up there? - The Chukchi Sea Ecosystem Mooring

NASA Astrophysics Data System (ADS)

Janzen, C.; McCammon, M.; Danielson, S. L.; Winsor, P.; Hopcroft, R. R.; Lalande, C.; Stafford, K.; Hauri, C.; McDonnell, A. M. P.

2016-02-01

As Arctic regions are projected to strongly reflect the impacts of a changing climate, an effort is underway to make sustained, year-round measurements of concurrent physical and biogeochemical parameters in the Arctic. Deploying highly instrumented year-round moorings in the water is no simple feat, given harsh Arctic conditions that include the presence of sea ice and deep ice keels during much of the year. Enter the late-breaking ecosystem mooring located in the northeast Chukchi Sea. This mooring complements established biophysical moorings elsewhere in the northern Bering and Chukchi seas, including those maintained by NOAA-PMEL (M8), UW-APL (Bering Strait) and JAMSTEC moorings. (southern Chukchi and Barrow Canyon). The mooring described here is located on the southern flank of Hanna Shoal and provides a multi-disciplinary approach to year-round observations within a biological hotspot. The Chukchi Ecosystem Mooring is equipped with a sensor suite aimed to monitor and document the state of ocean acidification, nutrient and carbon cycles, particles, waves, currents and physical properties, and even passive and active acoustic monitoring for zooplankton, fish, and marine mammals. Having the simultaneous interdisciplinary measurements provides data valuable to an ecosystem-based approach to research and resource management. The fully outfitted observatory is providing an unprecedented view into the mechanistic workings of the Chukchi Shelf Ecosystem. The first mooring was deployed in September 2014 and recovered in August 2015. The August 2015 deployment consisted of three moorings, each with incremental sensor packages to complete the ecosystem sensor suite. The mooring construction and instrumentation are described in detail, including introduction to the advances in sensor technologies that enable such deployments. Year one data recovery summaries and plots are provided to demonstrate the capabilities.

Naval sensor data database (NSDD)

NASA Astrophysics Data System (ADS)

Robertson, Candace J.; Tubridy, Lisa H.

1999-08-01

The Naval Sensor Data database (NSDD) is a multi-year effort to archive, catalogue, and disseminate data from all types of sensors to the mine warfare, signal and image processing, and sensor development communities. The purpose is to improve and accelerate research and technology. Providing performers with the data required to develop and validate improvements in hardware, simulation, and processing will foster advances in sensor and system performance. The NSDD will provide a centralized source of sensor data in its associated ground truth, which will support an improved understanding will be benefited in the areas of signal processing, computer-aided detection and classification, data compression, data fusion, and geo-referencing, as well as sensor and sensor system design.

Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

PubMed Central

Zhang, Shaowei; Yu, Jiancheng; Zhang, Aiqun; Yang, Lei; Shu, Yeqiang

2012-01-01

The micro-scale and meso-scale ocean dynamic processes which are nonlinear and have large variability, have a significant impact on the fisheries, natural resources, and marine climatology. A rapid, refined and sophisticated observation system is therefore needed in marine scientific research. The maneuverability and controllability of mobile sensor platforms make them a preferred choice to establish ocean observing networks, compared to the static sensor observing platform. In this study, marine vehicles are utilized as the nodes of mobile sensor networks for coverage sampling of a regional ocean area and ocean feature tracking. A synoptic analysis about marine vehicle dynamic control, multi vehicles mission assignment and path planning methods, and ocean feature tracking and observing techniques is given. Combined with the observation plan in the South China Sea, we provide an overview of the mobile sensor networks established with marine vehicles, and the corresponding simulation results. PMID:22368475

High resolution hybrid optical and acoustic sea floor maps (Invited)

NASA Astrophysics Data System (ADS)

Roman, C.; Inglis, G.

2013-12-01

This abstract presents a method for creating hybrid optical and acoustic sea floor reconstructions at centimeter scale grid resolutions with robotic vehicles. Multibeam sonar and stereo vision are two common sensing modalities with complementary strengths that are well suited for data fusion. We have recently developed an automated two stage pipeline to create such maps. The steps can be broken down as navigation refinement and map construction. During navigation refinement a graph-based optimization algorithm is used to align 3D point clouds created with both the multibeam sonar and stereo cameras. The process combats the typical growth in navigation error that has a detrimental affect on map fidelity and typically introduces artifacts at small grid sizes. During this process we are able to automatically register local point clouds created by each sensor to themselves and to each other where they overlap in a survey pattern. The process also estimates the sensor offsets, such as heading, pitch and roll, that describe how each sensor is mounted to the vehicle. The end results of the navigation step is a refined vehicle trajectory that ensures the points clouds from each sensor are consistently aligned, and the individual sensor offsets. In the mapping step, grid cells in the map are selectively populated by choosing data points from each sensor in an automated manner. The selection process is designed to pick points that preserve the best characteristics of each sensor and honor some specific map quality criteria to reduce outliers and ghosting. In general, the algorithm selects dense 3D stereo points in areas of high texture and point density. In areas where the stereo vision is poor, such as in a scene with low contrast or texture, multibeam sonar points are inserted in the map. This process is automated and results in a hybrid map populated with data from both sensors. Additional cross modality checks are made to reject outliers in a robust manner. The final hybrid map retains the strengths of both sensors and shows improvement over the single modality maps and a naively assembled multi-modal map where all the data points are included and averaged. Results will be presented from marine geological and archaeological applications using a 1350 kHz BlueView multibeam sonar and 1.3 megapixel digital still cameras.

A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements.

PubMed

Tannous, Halim; Istrate, Dan; Benlarbi-Delai, Aziz; Sarrazin, Julien; Gamet, Didier; Ho Ba Tho, Marie Christine; Dao, Tien Tuan

2016-11-15

Exergames have been proposed as a potential tool to improve the current practice of musculoskeletal rehabilitation. Inertial or optical motion capture sensors are commonly used to track the subject's movements. However, the use of these motion capture tools suffers from the lack of accuracy in estimating joint angles, which could lead to wrong data interpretation. In this study, we proposed a real time quaternion-based fusion scheme, based on the extended Kalman filter, between inertial and visual motion capture sensors, to improve the estimation accuracy of joint angles. The fusion outcome was compared to angles measured using a goniometer. The fusion output shows a better estimation, when compared to inertial measurement units and Kinect outputs. We noted a smaller error (3.96°) compared to the one obtained using inertial sensors (5.04°). The proposed multi-sensor fusion system is therefore accurate enough to be applied, in future works, to our serious game for musculoskeletal rehabilitation.

Reduction of Magnetic Noise Associated with Ocean Waves by Sage-Husa Adaptive Kalman Filter in Towed Overhauser Marine Magnetic Sensor

NASA Astrophysics Data System (ADS)

GE, J.; Dong, H.; Liu, H.; Luo, W.

2016-12-01

In the extreme sea conditions and deep-sea detection, the towed Overhauser marine magnetic sensor is easily affected by the magnetic noise associated with ocean waves. We demonstrate the reduction of the magnetic noise by Sage-Husa adaptive Kalman filter. Based on Weaver's model, we analyze the induced magnetic field variations associated with the different ocean depths, wave periods and amplitudes in details. Furthermore, we take advantage of the classic Kalman filter to reduce the magnetic noise and improve the signal to noise ratio of the magnetic anomaly data. In the practical marine magnetic surveys, the extreme sea conditions can change priori statistics of the noise, and may decrease the effect of Kalman filtering estimation. To solve this problem, an improved Sage-Husa adaptive filtering algorithm is used to reduce the dependence on the prior statistics. In addition, we implement a towed Overhauser marine magnetometer (Figure 1) to test the proposed method, and it consists of a towfish, an Overhauser total field sensor, a console, and other condition monitoring sensors. Over all, the comparisons of simulation experiments with and without the filter show that the power spectral density of the magnetic noise is reduced to 0.1 nT/Hz1/2@1Hz from 1 nT/Hz1/2@1Hz. The contrasts between the Sage-Husa filter and the classic Kalman filter (Figure 2) show the filtering accuracy and adaptive capacity are improved.

Advances in Multi-Sensor Information Fusion: Theory and Applications 2017.

PubMed

Jin, Xue-Bo; Sun, Shuli; Wei, Hong; Yang, Feng-Bao

2018-04-11

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications.

Multi-channel distributed coordinated function over single radio in wireless sensor networks.

PubMed

Campbell, Carlene E-A; Loo, Kok-Keong Jonathan; Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

2011-01-01

Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band.

Multi-Channel Distributed Coordinated Function over Single Radio in Wireless Sensor Networks

PubMed Central

Campbell, Carlene E.-A.; Loo, Kok-Keong (Jonathan); Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

2011-01-01

Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band. PMID:22346614

A Three-Dimensional Target Depth-Resolution Method with a Single-Vector Sensor

PubMed Central

Zhao, Anbang; Bi, Xuejie; Hui, Juan; Zeng, Caigao; Ma, Lin

2018-01-01

This paper mainly studies and verifies the target number category-resolution method in multi-target cases and the target depth-resolution method of aerial targets. Firstly, target depth resolution is performed by using the sign distribution of the reactive component of the vertical complex acoustic intensity; the target category and the number resolution in multi-target cases is realized with a combination of the bearing-time recording information; and the corresponding simulation verification is carried out. The algorithm proposed in this paper can distinguish between the single-target multi-line spectrum case and the multi-target multi-line spectrum case. This paper presents an improved azimuth-estimation method for multi-target cases, which makes the estimation results more accurate. Using the Monte Carlo simulation, the feasibility of the proposed target number and category-resolution algorithm in multi-target cases is verified. In addition, by studying the field characteristics of the aerial and surface targets, the simulation results verify that there is only amplitude difference between the aerial target field and the surface target field under the same environmental parameters, and an aerial target can be treated as a special case of a surface target; the aerial target category resolution can then be realized based on the sign distribution of the reactive component of the vertical acoustic intensity so as to realize three-dimensional target depth resolution. By processing data from a sea experiment, the feasibility of the proposed aerial target three-dimensional depth-resolution algorithm is verified. PMID:29649173

A Three-Dimensional Target Depth-Resolution Method with a Single-Vector Sensor.

PubMed

Zhao, Anbang; Bi, Xuejie; Hui, Juan; Zeng, Caigao; Ma, Lin

2018-04-12

This paper mainly studies and verifies the target number category-resolution method in multi-target cases and the target depth-resolution method of aerial targets. Firstly, target depth resolution is performed by using the sign distribution of the reactive component of the vertical complex acoustic intensity; the target category and the number resolution in multi-target cases is realized with a combination of the bearing-time recording information; and the corresponding simulation verification is carried out. The algorithm proposed in this paper can distinguish between the single-target multi-line spectrum case and the multi-target multi-line spectrum case. This paper presents an improved azimuth-estimation method for multi-target cases, which makes the estimation results more accurate. Using the Monte Carlo simulation, the feasibility of the proposed target number and category-resolution algorithm in multi-target cases is verified. In addition, by studying the field characteristics of the aerial and surface targets, the simulation results verify that there is only amplitude difference between the aerial target field and the surface target field under the same environmental parameters, and an aerial target can be treated as a special case of a surface target; the aerial target category resolution can then be realized based on the sign distribution of the reactive component of the vertical acoustic intensity so as to realize three-dimensional target depth resolution. By processing data from a sea experiment, the feasibility of the proposed aerial target three-dimensional depth-resolution algorithm is verified.

Spinning projectile's attitude measurement with LW infrared radiation under sea-sky background

NASA Astrophysics Data System (ADS)

Xu, Miaomiao; Bu, Xiongzhu; Yu, Jing; He, Zilu

2018-05-01

With the further development of infrared radiation research in sea-sky background and the requirement of spinning projectile's attitude measurement, the sea-sky infrared radiation field is used to carry out spinning projectile's attitude angle instead of inertial sensors. Firstly, the generation mechanism of sea-sky infrared radiation is analysed. The mathematical model of sea-sky infrared radiation is deduced in LW (long wave) infrared 8 ∼ 14 μm band by calculating the sea surface and sky infrared radiation. Secondly, according to the movement characteristics of spinning projectile, the attitude measurement model of infrared sensors on projectile's three axis is established. And the feasibility of the model is analysed by simulation. Finally, the projectile's attitude calculation algorithm is designed to improve the attitude angle estimation accuracy. The results of semi-physical experiments show that the segmented interactive algorithm estimation error of pitch and roll angle is within ±1.5°. The attitude measurement method is effective and feasible, and provides accurate measurement basis for the guidance of spinning projectile.

A Radiosonde Using a Humidity Sensor Array with a Platinum Resistance Heater and Multi-Sensor Data Fusion

PubMed Central

Shi, Yunbo; Luo, Yi; Zhao, Wenjie; Shang, Chunxue; Wang, Yadong; Chen, Yinsheng

2013-01-01

This paper describes the design and implementation of a radiosonde which can measure the meteorological temperature, humidity, pressure, and other atmospheric data. The system is composed of a CPU, microwave module, temperature sensor, pressure sensor and humidity sensor array. In order to effectively solve the humidity sensor condensation problem due to the low temperatures in the high altitude environment, a capacitive humidity sensor including four humidity sensors to collect meteorological humidity and a platinum resistance heater was developed using micro-electro-mechanical-system (MEMS) technology. A platinum resistance wire with 99.999% purity and 0.023 mm in diameter was used to obtain the meteorological temperature. A multi-sensor data fusion technique was applied to process the atmospheric data. Static and dynamic experimental results show that the designed humidity sensor with platinum resistance heater can effectively tackle the sensor condensation problem, shorten response times and enhance sensitivity. The humidity sensor array can improve measurement accuracy and obtain a reliable initial meteorological humidity data, while the multi-sensor data fusion technique eliminates the uncertainty in the measurement. The radiosonde can accurately reflect the meteorological changes. PMID:23857263

A radiosonde using a humidity sensor array with a platinum resistance heater and multi-sensor data fusion.

PubMed

Shi, Yunbo; Luo, Yi; Zhao, Wenjie; Shang, Chunxue; Wang, Yadong; Chen, Yinsheng

2013-07-12

This paper describes the design and implementation of a radiosonde which can measure the meteorological temperature, humidity, pressure, and other atmospheric data. The system is composed of a CPU, microwave module, temperature sensor, pressure sensor and humidity sensor array. In order to effectively solve the humidity sensor condensation problem due to the low temperatures in the high altitude environment, a capacitive humidity sensor including four humidity sensors to collect meteorological humidity and a platinum resistance heater was developed using micro-electro-mechanical-system (MEMS) technology. A platinum resistance wire with 99.999% purity and 0.023 mm in diameter was used to obtain the meteorological temperature. A multi-sensor data fusion technique was applied to process the atmospheric data. Static and dynamic experimental results show that the designed humidity sensor with platinum resistance heater can effectively tackle the sensor condensation problem, shorten response times and enhance sensitivity. The humidity sensor array can improve measurement accuracy and obtain a reliable initial meteorological humidity data, while the multi-sensor data fusion technique eliminates the uncertainty in the measurement. The radiosonde can accurately reflect the meteorological changes.

An enhanced data visualization method for diesel engine malfunction classification using multi-sensor signals.

PubMed

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-10-21

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine.

An Enhanced Data Visualization Method for Diesel Engine Malfunction Classification Using Multi-Sensor Signals

PubMed Central

Li, Yiqing; Wang, Yu; Zi, Yanyang; Zhang, Mingquan

2015-01-01

The various multi-sensor signal features from a diesel engine constitute a complex high-dimensional dataset. The non-linear dimensionality reduction method, t-distributed stochastic neighbor embedding (t-SNE), provides an effective way to implement data visualization for complex high-dimensional data. However, irrelevant features can deteriorate the performance of data visualization, and thus, should be eliminated a priori. This paper proposes a feature subset score based t-SNE (FSS-t-SNE) data visualization method to deal with the high-dimensional data that are collected from multi-sensor signals. In this method, the optimal feature subset is constructed by a feature subset score criterion. Then the high-dimensional data are visualized in 2-dimension space. According to the UCI dataset test, FSS-t-SNE can effectively improve the classification accuracy. An experiment was performed with a large power marine diesel engine to validate the proposed method for diesel engine malfunction classification. Multi-sensor signals were collected by a cylinder vibration sensor and a cylinder pressure sensor. Compared with other conventional data visualization methods, the proposed method shows good visualization performance and high classification accuracy in multi-malfunction classification of a diesel engine. PMID:26506347

MOBY, A Radiometric Buoy for Performance Monitoring and Vicarious Calibration of Satellite Ocean Color Sensors: Measurement and Data Analysis Protocols. Chapter 2

NASA Technical Reports Server (NTRS)

Clark, Dennis K.; Yarbrough, Mark A.; Feinholz, Mike; Flora, Stephanie; Broenkow, William; Kim, Yong Sung; Johnson, B. Carol; Brown, Steven W.; Yuen, Marilyn; Mueller, James L.

2003-01-01

The Marine Optical Buoy (MOBY) is the centerpiece of the primary ocean measurement site for calibration of satellite ocean color sensors based on independent in situ measurements. Since late 1996, the time series of normalized water-leaving radiances L(sub WN)(lambda) determined from the array of radiometric sensors attached to MOBY are the primary basis for the on-orbit calibrations of the USA Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Japanese Ocean Color and Temperature Sensor (OCTS), the French Polarization Detection Environmental Radiometer (POLDER), the German Modular Optoelectronic Scanner on the Indian Research Satellite (IRS1-MOS), and the USA Moderate Resolution Imaging Spectrometer (MODIS). The MOBY vicarious calibration L(sub WN)(lambda) reference is an essential element in the international effort to develop a global, multi-year time series of consistently calibrated ocean color products using data from a wide variety of independent satellite sensors. A longstanding goal of the SeaWiFS and MODIS (Ocean) Science Teams is to determine satellite-derived L(sub WN)(labda) with a relative combined standard uncertainty of 5 %. Other satellite ocean color projects and the Sensor Intercomparison for Marine Biology and Interdisciplinary Oceanic Studies (SIMBIOS) project have also adopted this goal, at least implicitly. Because water-leaving radiance contributes at most 10 % of the total radiance measured by a satellite sensor above the atmosphere, a 5 % uncertainty in L(sub WN)(lambda) implies a 0.5 % uncertainty in the above-atmosphere radiance measurements. This level of uncertainty can only be approached using vicarious-calibration approaches as described below. In practice, this means that the satellite radiance responsivity is adjusted to achieve the best agreement, in a least-squares sense, for the L(sub WN)(lambda) results determined using the satellite and the independent optical sensors (e.g. MOBY). The end result of this approach is to implicitly absorb unquantified, but systematic, errors in the atmospheric correction, incident solar flux, and satellite sensor calibration into a single correction factor to produce consistency with the in situ data.

Testing and evaluation of tactical electro-optical sensors

NASA Astrophysics Data System (ADS)

Middlebrook, Christopher T.; Smith, John G.

2002-07-01

As integrated electro-optical sensor payloads (multi- sensors) comprised of infrared imagers, visible imagers, and lasers advance in performance, the tests and testing methods must also advance in order to fully evaluate them. Future operational requirements will require integrated sensor payloads to perform missions at further ranges and with increased targeting accuracy. In order to meet these requirements sensors will require advanced imaging algorithms, advanced tracking capability, high-powered lasers, and high-resolution imagers. To meet the U.S. Navy's testing requirements of such multi-sensors, the test and evaluation group in the Night Vision and Chemical Biological Warfare Department at NAVSEA Crane is developing automated testing methods, and improved tests to evaluate imaging algorithms, and procuring advanced testing hardware to measure high resolution imagers and line of sight stabilization of targeting systems. This paper addresses: descriptions of the multi-sensor payloads tested, testing methods used and under development, and the different types of testing hardware and specific payload tests that are being developed and used at NAVSEA Crane.

Radiative Transfer Modeling to Estimate the Impact of CDOM on Light Absorption within Changing Arctic Sea Ice

NASA Astrophysics Data System (ADS)

Carns, R.; Light, B.; Frey, K. E.

2016-12-01

First-year sea ice differs from multi-year sea ice in several ways that can influence its optical properties. It is thinner than multi-year ice, which tends to increase light transmission. Also, first-year ice retains higher brine volumes in comparison to more heavily drained multi-year ice, in isolated pockets and channels. During melt season, patterns of pond formation on first-year sea ice differ from those on multi-year ice. As first-year sea ice comprises an increasingly large fraction of Arctic sea ice, it becomes more important to understand how much sunlight reaches the ecosystems within the ice, and how those changing ecosystems can feed back into the transmission of light. Colored dissolved organic matter (CDOM) and chlorophyll within the ice can absorb light, heating the ice and reducing transmission to the ocean below. Light also encourages algal growth within the ice while degrading CDOM, creating complex feedbacks. We use radiative transfer models to determine the overall effect of colored dissolved organic matter on the light regime within sea ice, both on the overall amount of energy transmitted and on the spectral distribution of energy. Using models allows us to estimate the impact of varying CDOM levels on a wide range of sea ice types, improving our ability to respond to conditions in a rapidly changing Arctic and predict important phenomena such as algal blooms.

NGS2: a focal plane array upgrade for the GeMS multiple tip-tilt wavefront sensor

NASA Astrophysics Data System (ADS)

Rigaut, François; Price, Ian; d'Orgeville, Céline; Bennet, Francis; Herrald, Nick; Paulin, Nicolas; Uhlendorf, Kristina; Garrel, Vincent; Sivo, Gaetano; Montes, Vanessa; Trujillo, Chad

2016-07-01

NGS2 is an upgrade for the multi-natural guide star tip-tilt & plate scale wavefront sensor for GeMS (Gemini Multi-Conjugate Adaptive Optics system). It uses a single Nüvü HNü-512 Electron-Multiplied CCD array that spans the entire GeMS wavefront sensor focal plane. Multiple small regions-of-interest are used to enable frame rates up to 800Hz. This set up will improve the optical throughput with respect to the current wavefront sensor, as well as streamline acquisition and allow for distortion compensation.

REMOTE SENSING IN OCEANOGRAPHY.

DTIC Science & Technology

remote sensing from satellites. Sensing of oceanographic variables from aircraft began with the photographing of waves and ice. Since then remote measurement of sea surface temperatures and wave heights have become routine. Sensors tested for oceanographic applications include multi-band color cameras, radar scatterometers, infrared spectrometers and scanners, passive microwave radiometers, and radar imagers. Remote sensing has found its greatest application in providing rapid coverage of large oceanographic areas for synoptic and analysis and

Analysis of evolution of meddies in the North Atlantic using float experiments and multi - sensor data

NASA Astrophysics Data System (ADS)

Jo, Y.; Yan, X.; Zheng, Q.; Klemas, V. V.; Liu, W.

2002-05-01

We analyzed the interactions of Mediterranean eddies (meddies) in the North Atlantic with large - and meso - scale dynamic processes. The study focuses on the baroclinic instability due to the surface wind forcing, topographical Rossby wave (TRW) and the meddies' signals in multi-sensor data. The Hilbert - Huang's Energy - Frequency - Time spectrum was employed to estimate the dominant frequency. The major power peak of the surface wind forcing and sea surface height anomaly occurs every 33 months and relates to horizontal translation of the southwestward meddies. This frequency is quite close to M\\x81ler and Siedler's (1992) zonal variability with periods of 3 - 4 years. The subsequent power peaks in the vertical displacement of the meddies are at 5 day and 10 day intervals as derived from AMUSE and SEMAPHORE experiments (1993 - 1995). These 5 and 10 day periods may be caused by the intrusion of dense Mediterranean water. The contributions of the rotation speed, thermal expansion, and vertical fluctuation in the meddies' signals were estimated using the data taken by the AMUSE and the SEMAPHORE experiments. Consequently, mean monthly climatological meddies' signals from the multi-sensor analysis and float measurements show that the meddies mean kinetic energy is related to topographic scales.

Human Activity Recognition from Smart-Phone Sensor Data using a Multi-Class Ensemble Learning in Home Monitoring.

PubMed

Ghose, Soumya; Mitra, Jhimli; Karunanithi, Mohan; Dowling, Jason

2015-01-01

Home monitoring of chronically ill or elderly patient can reduce frequent hospitalisations and hence provide improved quality of care at a reduced cost to the community, therefore reducing the burden on the healthcare system. Activity recognition of such patients is of high importance in such a design. In this work, a system for automatic human physical activity recognition from smart-phone inertial sensors data is proposed. An ensemble of decision trees framework is adopted to train and predict the multi-class human activity system. A comparison of our proposed method with a multi-class traditional support vector machine shows significant improvement in activity recognition accuracies.

Aerosol Climate Time Series Evaluation In ESA Aerosol_cci

NASA Astrophysics Data System (ADS)

Popp, T.; de Leeuw, G.; Pinnock, S.

2015-12-01

Within the ESA Climate Change Initiative (CCI) Aerosol_cci (2010 - 2017) conducts intensive work to improve algorithms for the retrieval of aerosol information from European sensors. By the end of 2015 full mission time series of 2 GCOS-required aerosol parameters are completely validated and released: Aerosol Optical Depth (AOD) from dual view ATSR-2 / AATSR radiometers (3 algorithms, 1995 - 2012), and stratospheric extinction profiles from star occultation GOMOS spectrometer (2002 - 2012). Additionally, a 35-year multi-sensor time series of the qualitative Absorbing Aerosol Index (AAI) together with sensitivity information and an AAI model simulator is available. Complementary aerosol properties requested by GCOS are in a "round robin" phase, where various algorithms are inter-compared: fine mode AOD, mineral dust AOD (from the thermal IASI spectrometer), absorption information and aerosol layer height. As a quasi-reference for validation in few selected regions with sparse ground-based observations the multi-pixel GRASP algorithm for the POLDER instrument is used. Validation of first dataset versions (vs. AERONET, MAN) and inter-comparison to other satellite datasets (MODIS, MISR, SeaWIFS) proved the high quality of the available datasets comparable to other satellite retrievals and revealed needs for algorithm improvement (for example for higher AOD values) which were taken into account for a reprocessing. The datasets contain pixel level uncertainty estimates which are also validated. The paper will summarize and discuss the results of major reprocessing and validation conducted in 2015. The focus will be on the ATSR, GOMOS and IASI datasets. Pixel level uncertainties validation will be summarized and discussed including unknown components and their potential usefulness and limitations. Opportunities for time series extension with successor instruments of the Sentinel family will be described and the complementarity of the different satellite aerosol products (e.g. dust vs. total AOD, ensembles from different algorithms for the same sensor) will be discussed.

Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

NASA Astrophysics Data System (ADS)

Zheng, Yan

2015-03-01

Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

Design of self-contained sensor for monitoring of deep-sea offshore platform

NASA Astrophysics Data System (ADS)

Song, Yang; Yu, Yan; Zhang, Chunwei; Dong, Weijie; Ou, Jinping

2013-04-01

Offshore platform, which is the base of the production and living in the sea, is the most important infrastructure for developing oil and gas resources. At present, there are almost 6500 offshore platforms servicing in the 53 countries' sea areas around the world, creating great wealth for the world. In general, offshore platforms may work for 20 years, however, offshore platforms are expensive, complex, bulky, and so many of them are on extended active duty. Because of offshore platforms servicing in the harsh marine environment for a long time, the marine environment have a great impact on the offshore platforms. Besides, with the impact and erosion of seawater, and material aging, the offshore platform is possible to be in unexpected situations when a badly sudden situation happens. Therefore, it is of great significance to monitor the marine environment and offshore platforms. The self-contained sensor for deep-sea offshore platform with its unique design, can not only effectively extend the working time of the sensor with the capability of converting vibration energy to electrical energy, but also simultaneously collect the data of acceleration, inclination, temperature and humidity of the deep sea, so that we can achieve the purpose of monitoring offshore platforms through analyzing the collected data. The self-contained sensor for monitoring of deep-sea offshore platform includes sensing unit, data collecting and storage unit, the energy supply unit. The sensing unit with multi-variables, consists of an accelerometer LIS344ALH, an inclinometer SCA103T and a temperature and humidity sensor SHT11; the data collecting and storage unit includes the MSP430 low-power MCU, large capacity memory, clock circuit and the communication interface, the communication interface includes USB interface, serial ports and wireless interface; in addition, the energy supply unit, converting vibration to electrical energy to power the overall system, includes the electromagnetic generator, voltage multiplier circuit and a super capacitor which can withstand virtually unlimited number of charge-discharge cycles. When the seawater impacts on offshore platforms to produce vibration, electromagnetic generator converts vibration to electrical energy, its output(~ 1 V 50 Hz AC) is stepped up and rectified by a voltage multiplier circuit, and the energy is stored in a super capacitor. It is controlled by the MSP430 that monitors the voltage level on the super capacitor. The super capacitor charges the Li-ion battery when the voltage on the super capacitor reaches a threshold, then the whole process of energy supply is completed. The self-contained sensor for deep-sea offshore platform has good application prospects and practical value with small size, low power, being easy to install, converting vibration energy to supply power and high detection accuracy.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-11-06

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-01-01

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture. PMID:27827971

Multi-tiered sensing and data processing for monitoring ship structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrar, Charles; Salvino, Liming; Lynch, Jerome

2009-01-01

A comprehensive structural health monitoring (SHM) system is a critical mechanism to ensure hull integrity and evaluate structural performance over the life of a ship, especially for lightweight high-speed ships. One of the most important functions of a SHM system is to provide real-time performance guidance and reduce the risk of structural damage during operations at sea. This is done by continuous feedback from onboard sensors providing measurements of seaway loads and structural responses. Applications of SHM should also include diagnostic capabilities such as identifying the presence of damage, assessing the location and extent of damage when it does occurmore » in order to plan for future inspection and maintenance. The development of such SHM systems is extremely challenging because of the physical size of these structures, the widely varying and often extreme operational and environmental conditions associated with the missions of high performance ships, the lack of data from known damage conditions, the limited sensing that was not designed specifically for SHM, the management of the vast amounts of data, and the need for continued, real-time data processing. This paper will discuss some of these challenges and several outstanding issues that need to be addressed in the context of applying various SHM approaches to sea trials data measured on an aluminum high-speed catamaran, the HSV-2 Swift. A multi-tiered approach for sensing and data processing will be discussed as potential SHM architecture for future shipboard application. This approach will involve application of low cost and dense sensor arrays such as wireless communications in selected areas of the ship hull in addition to conventional sensors measuring global structural response of the ship. A recent wireless hull monitoring demo on FSF-I SeaFighter will be discussed as an example to show how this proposed architecture is a viable approach for long-term and real-time hull monitoring.« less

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

PubMed Central

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-01-01

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. PMID:27294931

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety.

PubMed

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-06-09

Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.

Remote sensing of chlorophyll in the Baltic Sea at basin scale from 1997 to 2012 using merged multi-sensor data

NASA Astrophysics Data System (ADS)

Pitarch, Jaime; Volpe, Gianluca; Colella, Simone; Krasemann, Hajo; Santoleri, Rosalia

2016-03-01

A 15-year (1997-2012) time series of chlorophyll a (Chl a) in the Baltic Sea, based on merged multi-sensor satellite data was analysed. Several available Chl a algorithms were sea-truthed against the largest in situ publicly available Chl a data set ever used for calibration and validation over the Baltic region. To account for the known biogeochemical heterogeneity of the Baltic, matchups were calculated for three separate areas: (1) the Skagerrak and Kattegat, (2) the central Baltic, including the Baltic Proper and the gulfs of Riga and Finland, and (3) the Gulf of Bothnia. Similarly, within the operational context of the Copernicus Marine Environment Monitoring Service (CMEMS) the three areas were also considered as a whole in the analysis. In general, statistics showed low linearity. However, a bootstrapping-like assessment did provide the means for removing the bias from the satellite observations, which were then used to compute basin average time series. Resulting climatologies confirmed that the three regions display completely different Chl a seasonal dynamics. The Gulf of Bothnia displays a single Chl a peak during spring, whereas in the Skagerrak and Kattegat the dynamics are less regular and composed of highs and lows during winter, progressing towards a small bloom in spring and a minimum in summer. In the central Baltic, Chl a follows a dynamics of a mild spring bloom followed by a much stronger bloom in summer. Surface temperature data are able to explain a variable fraction of the intensity of the summer bloom in the central Baltic.<

Understanding and quantifying greenhouse gases (GHG) emissions: the UK GHG Emissions and Feedback Programme

NASA Astrophysics Data System (ADS)

Matthiesen, Stephan; Palmer, Paul; Watson, Andrew; Williams, Mathew

2016-04-01

We give an overview over the structure, objectives, and methods of the UK-based Greenhouse Gases Emissions and Feedback Programme. The overarching objective of this research programme is to deliver improved GHG inventories and predictions for the UK, and for the globe at a regional scale. To address this objective, the Programme has developed a comprehensive, multi-year and interlinked measurement and data analysis programme, focussing on the major GHGs carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). The Programme integrates three UK research consortia with complementary objectives, focussing on observation and modelling in the atmosphere, the oceans, and the terrestrial biosphere: GAUGE (Greenhouse gAs Uk and Global Emissions) will produce robust estimates of the UK GHG budget, using new and existing atmospheric measurement networks and modelling activities at a range of scales. It integrates inter-calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology. The GREENHOUSE (Generating Regional Emissions Estimates with a Novel Hierarchy of Observations and Upscaled Simulation Experiments) project aims to understand the spatio-temporal patterns of biogenic GHG emissions in the UK's landscape of managed and semi-managed ecosystems. It uses existing UK field data and several targeted new measurement campaigns to build regional GHG inventories and improve the capabilities of land surface models. RAGNARoCC (Radiatively active gases from the North Atlantic Region and Climate Change) is an oceanographic project to investigate the air-sea fluxes of GHGs in the North Atlantic region. Through dedicated research cruises as well as data collection from ships of opportunity, it develops a comprehensive budget of natural and anthropogenic components of the carbon cycle in the North Atlantic and a better understanding of why the air-sea fluxes of CO2 vary regionally, seasonally and multi-annually. Integration activities link these three projects to foster knowledge exchange across different scales, methods and sub-disciplines, both within the Programme and with the wider research community. The three projects are integrated to improve our understanding of greenhouse gases across domains and scales. The observational components lay the foundation of new measurement infrastructure that will deliver beyond the lifetime of this Programme. Through the development of robust methods to reduce uncertainties in GHG emissions estimates, the Programme supports regulatory efforts to monitor emissions trends and the efficacy of reduction strategies.

Passive microwave remote sensing for sea ice research

NASA Technical Reports Server (NTRS)

1984-01-01

Techniques for gathering data by remote sensors on satellites utilized for sea ice research are summarized. Measurement of brightness temperatures by a passive microwave imager converted to maps of total sea ice concentration and to the areal fractions covered by first year and multiyear ice are described. Several ancillary observations, especially by means of automatic data buoys and submarines equipped with upward looking sonars, are needed to improve the validation and interpretation of satellite data. The design and performance characteristics of the Navy's Special Sensor Microwave Imager, expected to be in orbit in late 1985, are described. It is recommended that data from that instrument be processed to a form suitable for research applications and archived in a readily accessible form. The sea ice data products required for research purposes are described and recommendations for their archival and distribution to the scientific community are presented.

SeaWiFS Postlaunch Technical Report Series. Volume 2; AMT-5 Cruise Report

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Aiken, James; Cummings, Denise G.; Gibb, Stuart W.; Rees, Nigel W.; Woodd-Walker, Rachel; Woodward, E. Malcolm S.; Woolfenden, James; Berthon, Jean-Francois;

Improved simulation of Antarctic sea ice due to the radiative effects of falling snow

NASA Astrophysics Data System (ADS)

Li, J.-L. F.; Richardson, Mark; Hong, Yulan; Lee, Wei-Liang; Wang, Yi-Hui; Yu, Jia-Yuh; Fetzer, Eric; Stephens, Graeme; Liu, Yinghui

2017-08-01

Southern Ocean sea-ice cover exerts critical control on local albedo and Antarctic precipitation, but simulated Antarctic sea-ice concentration commonly disagrees with observations. Here we show that the radiative effects of precipitating ice (falling snow) contribute substantially to this discrepancy. Many models exclude these radiative effects, so they underestimate both shortwave albedo and downward longwave radiation. Using two simulations with the climate model CESM1, we show that including falling-snow radiative effects improves the simulations relative to cloud properties from CloudSat-CALIPSO, radiation from CERES-EBAF and sea-ice concentration from passive microwave sensors. From 50-70°S, the simulated sea-ice-area bias is reduced by 2.12 × 106 km2 (55%) in winter and by 1.17 × 106 km2 (39%) in summer, mainly because increased wintertime longwave heating restricts sea-ice growth and so reduces summer albedo. Improved Antarctic sea-ice simulations will increase confidence in projected Antarctic sea level contributions and changes in global warming driven by long-term changes in Southern Ocean feedbacks.

A Low Power, Parallel Wearable Multi-Sensor System for Human Activity Evaluation.

PubMed

Li, Yuecheng; Jia, Wenyan; Yu, Tianjian; Luan, Bo; Mao, Zhi-Hong; Zhang, Hong; Sun, Mingui

2015-04-01

In this paper, the design of a low power heterogeneous wearable multi-sensor system, built with Zynq System-on-Chip (SoC), for human activity evaluation is presented. The powerful data processing capability and flexibility of this SoC represent significant improvements over our previous ARM based system designs. The new system captures and compresses multiple color images and sensor data simultaneously. Several strategies are adopted to minimize power consumption. Our wearable system provides a new tool for the evaluation of human activity, including diet, physical activity and lifestyle.

Introduction: Special issue on advances in topobathymetric mapping, models, and applications

USGS Publications Warehouse

Gesch, Dean B.; Brock, John C.; Parrish, Christopher E.; Rogers, Jeffrey N.; Wright, C. Wayne

2016-01-01

Detailed knowledge of near-shore topography and bathymetry is required for many geospatial data applications in the coastal environment. New data sources and processing methods are facilitating development of seamless, regional-scale topobathymetric digital elevation models. These elevation models integrate disparate multi-sensor, multi-temporal topographic and bathymetric datasets to provide a coherent base layer for coastal science applications such as wetlands mapping and monitoring, sea-level rise assessment, benthic habitat mapping, erosion monitoring, and storm impact assessment. The focus of this special issue is on recent advances in the source data, data processing and integration methods, and applications of topobathymetric datasets.

Ocean Drifters Get the Facts

NASA Technical Reports Server (NTRS)

2001-01-01

With the help of Small Business Innovation Research (SBIR) funding from NASA's Goddard Space Flight Center, of Greenbelt, Maryland, Clearwater Instrumentation, of Watertown, Massachusetts, created the ClearSat-Autonomous Drifting Ocean Station (ADOS). The multi-sensor array ocean drifting station was developed to support observations of Earth by NASA satellites. It is a low-cost device for gathering an assortment of data necessary to the integration of present and future satellite measurements of biological and physical processes. Clearwater Instrumentation developed its ADOS technology based on Goddard's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) project, but on a scale that is practical for commercial use. ADOS is used for the in situ measuring of ocean surface layer properties such as ocean color, surface thermal structure, and surface winds. Thus far, multiple ADOS units have been sold to The Scripps Institution of Oceanography, where they are being applied in the field of academic science research. Fisheries can also benefit, because ADOS can locate prime cultivation conditions for this fast-growing industry.

At-sea demonstration of RF sensor tasking using XML over a worldwide network

NASA Astrophysics Data System (ADS)

Kellogg, Robert L.; Lee, Tom; Dumas, Diane; Raggo, Barbara

2003-07-01

As part of an At-Sea Demonstration for Space and Naval Warfare Command (SPAWAR, PMW-189), a prototype RF sensor for signal acquisition and direction finding queried and received tasking via a secure worldwide Automated Data Network System (ADNS). Using extended mark-up language (XML) constructs, both mission and signal tasking were available for push and pull Battlespace management. XML tasking was received by the USS Cape St George (CG-71) during an exercise along the Gulf Coast of the US from a test facility at SPAWAR, San Diego, CA. Although only one ship was used in the demonstration, the intent of the software initiative was to show that a network of different RF sensors on different platforms with different capabilitis could be tasked by a common web agent. A sensor software agent interpreted the XML task to match the sensor's capability. Future improvements will focus on enlarging the domain of mission tasking and incorporate report management.

Statistical Analyses of High-Resolution Aircraft and Satellite Observations of Sea Ice: Applications for Improving Model Simulations

NASA Astrophysics Data System (ADS)

Farrell, S. L.; Kurtz, N. T.; Richter-Menge, J.; Harbeck, J. P.; Onana, V.

2012-12-01

Satellite-derived estimates of ice thickness and observations of ice extent over the last decade point to a downward trend in the basin-scale ice volume of the Arctic Ocean. This loss has broad-ranging impacts on the regional climate and ecosystems, as well as implications for regional infrastructure, marine navigation, national security, and resource exploration. New observational datasets at small spatial and temporal scales are now required to improve our understanding of physical processes occurring within the ice pack and advance parameterizations in the next generation of numerical sea-ice models. High-resolution airborne and satellite observations of the sea ice are now available at meter-scale resolution or better that provide new details on the properties and morphology of the ice pack across basin scales. For example the NASA IceBridge airborne campaign routinely surveys the sea ice of the Arctic and Southern Oceans with an advanced sensor suite including laser and radar altimeters and digital cameras that together provide high-resolution measurements of sea ice freeboard, thickness, snow depth and lead distribution. Here we present statistical analyses of the ice pack primarily derived from the following IceBridge instruments: the Digital Mapping System (DMS), a nadir-looking, high-resolution digital camera; the Airborne Topographic Mapper, a scanning lidar; and the University of Kansas snow radar, a novel instrument designed to estimate snow depth on sea ice. Together these instruments provide data from which a wide range of sea ice properties may be derived. We provide statistics on lead distribution and spacing, lead width and area, floe size and distance between floes, as well as ridge height, frequency and distribution. The goals of this study are to (i) identify unique statistics that can be used to describe the characteristics of specific ice regions, for example first-year/multi-year ice, diffuse ice edge/consolidated ice pack, and convergent/divergent ice zones, (ii) provide datasets that support enhanced parameterizations in numerical models as well as model initialization and validation, (iii) parameters of interest to Arctic stakeholders for marine navigation and ice engineering studies, and (iv) statistics that support algorithm development for the next-generation of airborne and satellite altimeters, including NASA's ICESat-2 mission. We describe the potential contribution our results can make towards the improvement of coupled ice-ocean numerical models, and discuss how data synthesis and integration with high-resolution models may improve our understanding of sea ice variability and our capabilities in predicting the future state of the ice pack.

Multi-Sensor Aerosol Products Sampling System

NASA Technical Reports Server (NTRS)

Petrenko, M.; Ichoku, C.; Leptoukh, G.

2011-01-01

Global and local properties of atmospheric aerosols have been extensively observed and measured using both spaceborne and ground-based instruments, especially during the last decade. Unique properties retrieved by the different instruments contribute to an unprecedented availability of the most complete set of complimentary aerosol measurements ever acquired. However, some of these measurements remain underutilized, largely due to the complexities involved in analyzing them synergistically. To characterize the inconsistencies and bridge the gap that exists between the sensors, we have established a Multi-sensor Aerosol Products Sampling System (MAPSS), which consistently samples and generates the spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of aerosol products from multiple spacebome sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Samples of satellite aerosol products are extracted over Aerosol Robotic Network (AERONET) locations as well as over other locations of interest such as those with available ground-based aerosol observations. In this way, MAPSS enables a direct cross-characterization and data integration between Level-2 aerosol observations from multiple sensors. In addition, the available well-characterized co-located ground-based data provides the basis for the integrated validation of these products. This paper explains the sampling methodology and concepts used in MAPSS, and demonstrates specific examples of using MAPSS for an integrated analysis of multiple aerosol products.

Monitoring hypoxia: approaches to addressing a complex phenomenon in the Black Sea

NASA Astrophysics Data System (ADS)

Friedrich, Jana; Janssen, Felix; He, Yunchang; Holtappels, Moritz; Konovalov, Sergey; Prien, Ralf; Rehder, Gregor; Stanev, Emil

2014-05-01

In this contribution we present an overview of results and share experiences from monitoring and assessing various hypoxia phenomena in the Black Sea. The focus is on approaches and technologies for monitoring of, e.g., mesoscale seasonal patterns in water column oxygenation, multi-decadal trends in oxycline boundary shifts, fast oxygen fluctuations at the pelagic redoxcline and the sediment-water interface, and seasonal changes in bottom-water oxygen. The various temporal scales (from hours to decades) and spatial patterns (from local to basin-scale) in water column oxygenation were addressed using state-of-the-art technologies, e.g., a free-falling pump CTD, a profiling instrumentation platform, ARGO floats equipped with oxygen optodes, static moorings equipped with oxygen optodes, and long-term monitoring programs based on standard CTD casts. Examples from four study sites in the Black Sea and one in the Baltic Sea are presented. Oxygen sensor equipped ARGO type profiling floats proved to be powerful tools to resolve seasonal changes in water column oxygenation and emphasize the importance of mesoscale processes for oxygen distribution in the Black Sea basin. Existing multi-decadal time-series monitoring data based on standard CTD measurements revealed the imprint of climate change and eutrophication on long-term oxygen distributions in the central Black Sea and hence, highlight the importance of maintaining long-term commitments to oxygen monitoring programs. Monitoring data from the last 90 years reflect the rising of the upper boundary of the suboxic zone in the 1970s and 1980s due to eutrophication, and again in the 1990s and 2000s due to NAO forcing, while eutrophication relaxed. Such long time series data allow separating out the effects that climatic forcing and eutrophication exert on oxygen depletion i.e., in the Black Sea. A free-falling pump-CTD provided high-resolution profiles of oxygen and reduced compounds in the Bosporus outflow to the Black Sea, and proved highly suitable to resolve oxygen intrusions into highly stratified systems and hence, to identify and localize processes in complex redoxclines. We also present an example of novel technology applied in the Baltic Sea, which would be highly suitable for the Black Sea. The time series recordings of the profiling instrumentation platform GODESS in the Gotland Basin allowed a thorough characterization of oscillating redoxclines as temporally dynamic, three-dimensional systems. Stand-alone static moorings equipped with optical oxygen sensors, current meters, and turbidity sensors allowed to resolve fast oxygen fluctuations at the sediment-water interface due to, e.g., internal waves and Ekman pumping on the Crimean shelf and identified the formation of seasonal (summer) hypoxia as an highly dynamic process on the north-western Black Sea shelf. This comprehensive study within the EU-FP7 project HYPOX ("In situ monitoring of oxygen depletion in hypoxic ecosystems of coastal and open seas, and land-locked water bodies", www.hypox.net) was able to address many aspects of hypoxia, e.g., in the Black Sea, and revealed the vital need for dedicated oxygen monitoring programs to adequately address the risk of hypoxia formation and ecosystem response. The challenge in any kind of monitoring is to choose the appropriate approach and technology that is suited to resolve the temporal and spatial scales on which the phenomenon occurs.

Multi-Channel Capacitive Sensor Arrays

PubMed Central

Wang, Bingnan; Long, Jiang; Teo, Koon Hoo

2016-01-01

In this paper, multi-channel capacitive sensor arrays based on microstrip band-stop filters are studied. The sensor arrays can be used to detect the proximity of objects at different positions and directions. Each capacitive sensing structure in the array is connected to an inductive element to form resonance at different frequencies. The resonances are designed to be isolated in the frequency spectrum, such that the change in one channel does not affect resonances at other channels. The inductive element associated with each capacitive sensor can be surface-mounted inductors, integrated microstrip inductors or metamaterial-inspired structures. We show that by using metamaterial split-ring structures coupled to a microstrip line, the quality factor of each resonance can be greatly improved compared to conventional surface-mounted or microstrip meander inductors. With such a microstrip-coupled split-ring design, more sensing elements can be integrated in the same frequency spectrum, and the sensitivity can be greatly improved. PMID:26821023

Sea ice-atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates

NASA Technical Reports Server (NTRS)

Steffen, K.; Schweiger, A.; Maslanik, J.; Key, J.; Weaver, R.; Barry, R.

1990-01-01

The application of multi-spectral satellite data to estimate polar surface energy fluxes is addressed. To what accuracy and over which geographic areas large scale energy budgets can be estimated are investigated based upon a combination of available remote sensing and climatological data sets. The general approach was to: (1) formulate parameterization schemes for the appropriate sea ice energy budget terms based upon the remotely sensed and/or in-situ data sets; (2) conduct sensitivity analyses using as input both natural variability (observed data in regional case studies) and theoretical variability based upon energy flux model concepts; (3) assess the applicability of these parameterization schemes to both regional and basin wide energy balance estimates using remote sensing data sets; and (4) assemble multi-spectral, multi-sensor data sets for at least two regions of the Arctic Basin and possibly one region of the Antarctic. The type of data needed for a basin-wide assessment is described and the temporal coverage of these data sets are determined by data availability and need as defined by parameterization scheme. The titles of the subjects are as follows: (1) Heat flux calculations from SSM/I and LANDSAT data in the Bering Sea; (2) Energy flux estimation using passive microwave data; (3) Fetch and stability sensitivity estimates of turbulent heat flux; and (4) Surface temperature algorithm.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks.

PubMed

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-09-25

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude.

A Cluster-Based Dual-Adaptive Topology Control Approach in Wireless Sensor Networks

PubMed Central

Gui, Jinsong; Zhou, Kai; Xiong, Naixue

2016-01-01

Multi-Input Multi-Output (MIMO) can improve wireless network performance. Sensors are usually single-antenna devices due to the high hardware complexity and cost, so several sensors are used to form virtual MIMO array, which is a desirable approach to efficiently take advantage of MIMO gains. Also, in large Wireless Sensor Networks (WSNs), clustering can improve the network scalability, which is an effective topology control approach. The existing virtual MIMO-based clustering schemes do not either fully explore the benefits of MIMO or adaptively determine the clustering ranges. Also, clustering mechanism needs to be further improved to enhance the cluster structure life. In this paper, we propose an improved clustering scheme for virtual MIMO-based topology construction (ICV-MIMO), which can determine adaptively not only the inter-cluster transmission modes but also the clustering ranges. Through the rational division of cluster head function and the optimization of cluster head selection criteria and information exchange process, the ICV-MIMO scheme effectively reduces the network energy consumption and improves the lifetime of the cluster structure when compared with the existing typical virtual MIMO-based scheme. Moreover, the message overhead and time complexity are still in the same order of magnitude. PMID:27681731

BreedVision--a multi-sensor platform for non-destructive field-based phenotyping in plant breeding.

PubMed

Busemeyer, Lucas; Mentrup, Daniel; Möller, Kim; Wunder, Erik; Alheit, Katharina; Hahn, Volker; Maurer, Hans Peter; Reif, Jochen C; Würschum, Tobias; Müller, Joachim; Rahe, Florian; Ruckelshausen, Arno

2013-02-27

To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies.

BreedVision — A Multi-Sensor Platform for Non-Destructive Field-Based Phenotyping in Plant Breeding

PubMed Central

Busemeyer, Lucas; Mentrup, Daniel; Möller, Kim; Wunder, Erik; Alheit, Katharina; Hahn, Volker; Maurer, Hans Peter; Reif, Jochen C.; Würschum, Tobias; Müller, Joachim; Rahe, Florian; Ruckelshausen, Arno

2013-01-01

To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies. PMID:23447014

Decoupling Principle Analysis and Development of a Parallel Three-Dimensional Force Sensor

PubMed Central

Zhao, Yanzhi; Jiao, Leihao; Weng, Dacheng; Zhang, Dan; Zheng, Rencheng

2016-01-01

In the development of the multi-dimensional force sensor, dimension coupling is the ubiquitous factor restricting the improvement of the measurement accuracy. To effectively reduce the influence of dimension coupling on the parallel multi-dimensional force sensor, a novel parallel three-dimensional force sensor is proposed using a mechanical decoupling principle, and the influence of the friction on dimension coupling is effectively reduced by making the friction rolling instead of sliding friction. In this paper, the mathematical model is established by combining with the structure model of the parallel three-dimensional force sensor, and the modeling and analysis of mechanical decoupling are carried out. The coupling degree (ε) of the designed sensor is defined and calculated, and the calculation results show that the mechanical decoupling parallel structure of the sensor possesses good decoupling performance. A prototype of the parallel three-dimensional force sensor was developed, and FEM analysis was carried out. The load calibration and data acquisition experiment system are built, and then calibration experiments were done. According to the calibration experiments, the measurement accuracy is less than 2.86% and the coupling accuracy is less than 3.02%. The experimental results show that the sensor system possesses high measuring accuracy, which provides a basis for the applied research of the parallel multi-dimensional force sensor. PMID:27649194

Evaluation of Long-Term Cloud-Resolving Model Simulations Using Satellite Radiance Observations and Multi-Frequency Satellite Simulators

NASA Technical Reports Server (NTRS)

Matsui, Toshihisa; Zeng, Xiping; Tao, Wei-Kuo; Masunaga, Hirohiko; Olson, William S.; Lang, Stephen

2008-01-01

This paper proposes a methodology known as the Tropical Rainfall Measuring Mission (TRMM) Triple-Sensor Three-step Evaluation Framework (T3EF) for the systematic evaluation of precipitating cloud types and microphysics in a cloud-resolving model (CRM). T3EF utilizes multi-frequency satellite simulators and novel statistics of multi-frequency radiance and backscattering signals observed from the TRMM satellite. Specifically, T3EF compares CRM and satellite observations in the form of combined probability distributions of precipitation radar (PR) reflectivity, polarization-corrected microwave brightness temperature (Tb), and infrared Tb to evaluate the candidate CRM. T3EF is used to evaluate the Goddard Cumulus Ensemble (GCE) model for cases involving the South China Sea Monsoon Experiment (SCSMEX) and Kwajalein Experiment (KWAJEX). This evaluation reveals that the GCE properly captures the satellite-measured frequencies of different precipitating cloud types in the SCSMEX case but underestimates the frequencies of deep convective and deep stratiform types in the KWAJEX case. Moreover, the GCE tends to simulate excessively large and abundant frozen condensates in deep convective clouds as inferred from the overestimated GCE-simulated radar reflectivities and microwave Tb depressions. Unveiling the detailed errors in the GCE s performance provides the best direction for model improvements.

Relevance between SV and components based on water quality inspection by gas plumes

NASA Astrophysics Data System (ADS)

Nakanishi, A.; Aoyama, C.; Fukuoka, H.; Tajima, H.; Kumagai, H.; Takahashi, A.

2017-12-01

Gas and hydrate seeping from the seafloor into ocean water can be monitored on board, as images on echogram (acoustic equipment display inboard) by utilizing acoustic measurement equipment such as multi-beam sonars. Colors and shades of these images displayed on the monitor vary depending on the acoustic impedance. Backscattering strength (hereinafter referred as SV) depends on the type and density of plume components. Therefore, plume components should not be determined only by examining volume scattering density. By standardizing the relevance between gas plume SV and the components, types of plume components can be presumed just by calculating plume SV based on multi-beam data.Data from the following explorations will be utilized to perform the analysis of metal sensor, CTD measurement, and sampling. July, 2017 KAIYO-MARU2 (KAIYO ENGINEERING CO., LTD) @ Sea of Japan July, 2017 SIHNYO MARU (Tokyo University of Marine Science and Technology) @ Sea of Japan. And Chemical data obtained through YK16-07 cruise is also to be discussed.

Geospatial analysis of creeks evolution in the Indus Delta, Pakistan using multi sensor satellite data

NASA Astrophysics Data System (ADS)

Ijaz, Muhammad Wajid; Mahar, Rasool Bux; Siyal, Altaf Ali; Anjum, Muhammad Naveed

2018-01-01

Sea level rise (SLR) in response to looming climate change is being considered as a major impediment to coastal areas. Acute wave activities and tidal propagations of semi-diurnal to mixed type are impairing the morphology of the Indus Delta in Pakistan. In this study a synthetic approach has been adopted using multi sensor satellite and ground data in order to integrate the individual effect of topography, oceanic activities and vegetative canopy for deduction of a synergic impact over the morphology of the Indus Delta creeks system from 1972 to 2017. Geomorphologic anomalies in the planform of fourteen major creeks were explored. Spatiotemporal variations suggested that a substantial amount of the delta alluvium had been engulfed by the Arabian Sea. On average, the creeks located on the right side of the Indus River were relatively less wide (3.9 km) than those of on the left side (5.2 km). Zonal statistics calculated with topographic position index (TPI) enabled to understand the tide induced inundation extents. The mangrove canopy on the right side was found greater, which is why tidal basins on that side experienced less erosive activities. Thus, it could be maintained that the coastal sedimentary processes may be monitored effectively with the remotely sensed data and temporal pattern of changes can be quantified for future planning and mitigation of adverse effects.

Design and research of sun sensor based on technology of optical fiber

NASA Astrophysics Data System (ADS)

Li, Ye; Zhou, Wang; Li, Dan

2010-08-01

A kind of sun sensor is designed based on the optical fiber. This project consists of three parts: optical head, photoelectric sensor and signal processing unit. The innovation of this design lies in the improvement of traditional sun sensor, where multi-fibers, used as a leader, are symmetrically distributed on the surface of a spacecraft. To determine the attitude of a spacecraft, the sun sensor should measure the direction of the sun. Because the fiber length can be adjusted according to the fact, photoelectric sensor can be placed deeply inside a spacecraft to protect the photoelectric sensor against the damage by the high-energy particles from outer space. The processing unit calculates the difference value of sun energy imported by each pair of opposite optical fiber so as to obtain the angle and the orientation between the spacecraft and the sun. This sun sensor can suit multi-field of view, both small and large. It improves the accuracy of small field of view and increases the precision of locating a spacecraft. This paper briefly introduces the design of processing unit. This sun sensor is applicable to detect the attitude of a spacecraft. In addition, it can also be used in solar tracking system of PV technology.

Integrative Multi-Spectral Sensor Device for Far-Infrared and Visible Light Fusion

NASA Astrophysics Data System (ADS)

Qiao, Tiezhu; Chen, Lulu; Pang, Yusong; Yan, Gaowei

2018-06-01

Infrared and visible light image fusion technology is a hot spot in the research of multi-sensor fusion technology in recent years. Existing infrared and visible light fusion technologies need to register before fusion because of using two cameras. However, the application effect of the registration technology has yet to be improved. Hence, a novel integrative multi-spectral sensor device is proposed for infrared and visible light fusion, and by using the beam splitter prism, the coaxial light incident from the same lens is projected to the infrared charge coupled device (CCD) and visible light CCD, respectively. In this paper, the imaging mechanism of the proposed sensor device is studied with the process of the signals acquisition and fusion. The simulation experiment, which involves the entire process of the optic system, signal acquisition, and signal fusion, is constructed based on imaging effect model. Additionally, the quality evaluation index is adopted to analyze the simulation result. The experimental results demonstrate that the proposed sensor device is effective and feasible.

Wireless sensors and sensor networks for homeland security applications.

PubMed

Potyrailo, Radislav A; Nagraj, Nandini; Surman, Cheryl; Boudries, Hacene; Lai, Hanh; Slocik, Joseph M; Kelley-Loughnane, Nancy; Naik, Rajesh R

2012-11-01

New sensor technologies for homeland security applications must meet the key requirements of sensitivity to detect agents below risk levels, selectivity to provide minimal false-alarm rates, and response speed to operate in high throughput environments, such as airports, sea ports, and other public places. Chemical detection using existing sensor systems is facing a major challenge of selectivity. In this review, we provide a brief summary of chemical threats of homeland security importance; focus in detail on modern concepts in chemical sensing; examine the origins of the most significant unmet needs in existing chemical sensors; and, analyze opportunities, specific requirements, and challenges for wireless chemical sensors and wireless sensor networks (WSNs). We further review a new approach for selective chemical sensing that involves the combination of a sensing material that has different response mechanisms to different species of interest, with a transducer that has a multi-variable signal-transduction ability. This new selective chemical-sensing approach was realized using an attractive ubiquitous platform of battery-free passive radio-frequency identification (RFID) tags adapted for chemical sensing. We illustrate the performance of RFID sensors developed in measurements of toxic industrial materials, humidity-independent detection of toxic vapors, and detection of chemical-agent simulants, explosives, and strong oxidizers.

A Novel of Multi-wall Carbon Nanotubes/Chitosan Electrochemical Sensor for Determination of Cupric ion

NASA Astrophysics Data System (ADS)

Tan, Funeng; Li, Lei

2018-03-01

A multi-wall carbon nanotubes/Chitosan electrochemical sensor had been fabricated by dropping CHS/MWNT solution directly onto the GC surface. The sensor was charactered by cyclic voltammetry and AC impedance with K3Fe(CN)6 as a electrochemical probe; Cyclic voltammograms(CV) and electrochemical impedance spectroscopy(EIS) indicated that the active area and electrochemical behavior of the sensor increased and improved significantly after the electrode was modified by carbon nanotubes dispersed by the chitosan. The sensor showed good electrocatalytic activity of K3Fe(CN)6. Also, from the cyclic voltammograms, we can see the process was diffusion controlled on the bare electrode and kinetics and diffusion controlled on the modified electrode. Finally Cu2+ responsed sensitively at the sensor which supplied a new method for the detection of Cu2+.

Performance of an improved thermal neutron activation detector for buried bulk explosives

NASA Astrophysics Data System (ADS)

McFee, J. E.; Faust, A. A.; Andrews, H. R.; Clifford, E. T. H.; Mosquera, C. M.

2013-06-01

First generation thermal neutron activation (TNA) sensors, employing an isotopic source and NaI(Tl) gamma ray detectors, were deployed by Canadian Forces in 2002 as confirmation sensors on multi-sensor landmine detection systems. The second generation TNA detector is being developed with a number of improvements aimed at increasing sensitivity and facilitating ease of operation. Among these are an electronic neutron generator to increase sensitivity for deeper and horizontally displaced explosives; LaBr3(Ce) scintillators, to improve time response and energy resolution; improved thermal and electronic stability; improved sensor head geometry to minimize spatial response nonuniformity; and more robust data processing. The sensor is described, with emphasis on the improvements. Experiments to characterize the performance of the second generation TNA in detecting buried landmines and improvised explosive devices (IEDs) hidden in culverts are described. Performance results, including comparisons between the performance of the first and second generation systems are presented.

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

PubMed Central

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-01-01

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization. PMID:26343660

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines.

PubMed

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-08-27

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

Improving ISR Radar Utilization (How I quit blaming the user and made the radar easier to use).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin Walter

In modern multi - sensor multi - mode Intelligence, Surveillance, and Reconnaissance ( ISR ) platforms, the plethora of options available to a sensor/payload operator are quite large, leading to an over - worked operator often down - selecting to favorite sensors an d modes. For example, Full Motion Video (FMV) is justifiably a favorite sensor at the expense of radar modes, even if radar modes can offer unique and advantageous information. The challenge is then to increase the utilization of the radar modes in a man ner attractive to the sensor/payload operator. We propose that this is best accomplishedmore » by combining sensor modes and displays into 'super - modes'. - 4 - Acknowledgements This report is the result of a n unfunded research and development activity . Sandia Natio nal Laboratories is a multi - program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE - AC04 - 94AL850 00.« less

Heterogeneous regional signal control : final report.

DOT National Transportation Integrated Search

2017-03-12

The goal of this project is to develop a comprehensive framework with a set of models to improve multi-modal traffic signal control, by incorporating advanced floating sensor data (e.g. GPS data, etc.) and traditional fixed sensor data (e.g. loop det...

Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems.

PubMed

Gao, Lei; Bourke, A K; Nelson, John

2014-06-01

Physical activity has a positive impact on people's well-being and it had been shown to decrease the occurrence of chronic diseases in the older adult population. To date, a substantial amount of research studies exist, which focus on activity recognition using inertial sensors. Many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers to improve the overall recognition accuracy. In addition, the implementation of the advanced feature extraction algorithms and the complex classifiers exceed the computing ability of most current wearable sensor platforms. This paper proposes a method to adopt multiple sensors on distributed body locations to overcome this problem. The objective of the proposed system is to achieve higher recognition accuracy with "light-weight" signal processing algorithms, which run on a distributed computing based sensor system comprised of computationally efficient nodes. For analysing and evaluating the multi-sensor system, eight subjects were recruited to perform eight normal scripted activities in different life scenarios, each repeated three times. Thus a total of 192 activities were recorded resulting in 864 separate annotated activity states. The methods for designing such a multi-sensor system required consideration of the following: signal pre-processing algorithms, sampling rate, feature selection and classifier selection. Each has been investigated and the most appropriate approach is selected to achieve a trade-off between recognition accuracy and computing execution time. A comparison of six different systems, which employ single or multiple sensors, is presented. The experimental results illustrate that the proposed multi-sensor system can achieve an overall recognition accuracy of 96.4% by adopting the mean and variance features, using the Decision Tree classifier. The results demonstrate that elaborate classifiers and feature sets are not required to achieve high recognition accuracies on a multi-sensor system. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Remote Sensing of the Arctic Seas.

ERIC Educational Resources Information Center

Weeks, W. F.; And Others

1986-01-01

Examines remote sensing of the arctic seas by discussing: (1) passive microwave sensors; (2) active microwave sensors; (3) other types of sensors; (4) the future deployment of sensors; (5) data buoys; and (6) future endeavors. (JN)

Single-event transient imaging with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor.

PubMed

Mochizuki, Futa; Kagawa, Keiichiro; Okihara, Shin-ichiro; Seo, Min-Woong; Zhang, Bo; Takasawa, Taishi; Yasutomi, Keita; Kawahito, Shoji

2016-02-22

In the work described in this paper, an image reproduction scheme with an ultra-high-speed temporally compressive multi-aperture CMOS image sensor was demonstrated. The sensor captures an object by compressing a sequence of images with focal-plane temporally random-coded shutters, followed by reconstruction of time-resolved images. Because signals are modulated pixel-by-pixel during capturing, the maximum frame rate is defined only by the charge transfer speed and can thus be higher than those of conventional ultra-high-speed cameras. The frame rate and optical efficiency of the multi-aperture scheme are discussed. To demonstrate the proposed imaging method, a 5×3 multi-aperture image sensor was fabricated. The average rising and falling times of the shutters were 1.53 ns and 1.69 ns, respectively. The maximum skew among the shutters was 3 ns. The sensor observed plasma emission by compressing it to 15 frames, and a series of 32 images at 200 Mfps was reconstructed. In the experiment, by correcting disparities and considering temporal pixel responses, artifacts in the reconstructed images were reduced. An improvement in PSNR from 25.8 dB to 30.8 dB was confirmed in simulations.

Improving long-term global precipitation dataset using multi-sensor surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART)

USDA-ARS?s Scientific Manuscript database

Using multiple historical satellite surface soil moisture products, the Kalman Filtering-based Soil Moisture Analysis Rainfall Tool (SMART) is applied to improve the accuracy of a multi-decadal global daily rainfall product that has been bias-corrected to match the monthly totals of available rain g...

Assimilation of SeaWiFS Ocean Chlorophyll Data into a Three-Dimensional Global Ocean Model

NASA Technical Reports Server (NTRS)

Gregg, Watson W.

2005-01-01

Assimilation of satellite ocean color data is a relatively new phenomenon in ocean sciences. However, with routine observations from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), launched in late 1997, and now with new data from the Moderate Resolution Imaging Spectroradometer (MODIS) Aqua, there is increasing interest in ocean color data assimilation. Here SeaWiFS chlorophyll data were assimilated with an established thre-dimentional global ocean model. The assimilation improved estimates of hlorophyll and primary production relative to a free-run (no assimilation) model. This represents the first attempt at ocean color data assimilation using NASA satellites in a global model. The results suggest the potential of assimilation of satellite ocean chlorophyll data for improving models.

Antarctic surface elevation and slope from multi-mission lidar mapping

NASA Astrophysics Data System (ADS)

Sutterley, T. C.; Velicogna, I.; Neumann, T.; Markus, T.

2017-12-01

We present integrated estimates of surface elevation change and slope for the Antarctic Ice Sheet from a combination of measurements from the Airborne Topographic Mapper (ATM), the Land, Vegetation and Ice Sensor (LVIS) and the Ice Cloud and land Elevation Satellite (ICESat-1). This technique is a data-driven approach that calculates elevation differentials on a shot-by-shot basis. Our method extends the records of each instrument, increases the overall spatial coverage compared to a single instrument and produces high-quality, integrated maps of surface elevation, surface elevation change and slope. We use our estimates of elevation change to assess the current state of major outlet glaciers in the Bellinghausen Sea, Amundsen Sea and Getz regions of West Antarctica (WAIS). In the Amundsen Sea, we find that thinning rates of Pine Island Glacier have decreased after 2011 while thinning rates of Smith and Kohler glaciers have increased unabated.

New single-aircraft integrated atmospheric observation capabilities

NASA Astrophysics Data System (ADS)

Wang, Z.

2011-12-01

Improving current weather and climate model capabilities requires better understandings of many atmospheric processes. Thus, advancing atmospheric observation capabilities has been regarded as the highest imperatives to advance the atmospheric science in the 21st century. Under the NSF CAREER support, we focus on developing new airborne observation capabilities through the developments of new instrumentations and the single-aircraft integration of multiple remote sensors with in situ probes. Two compact Wyoming cloud lidars were built to work together with a 183 GHz microwave radiometer, a multi-beam Wyoming cloud radar and in situ probes for cloud studies. The synergy of these remote sensor measurements allows us to better resolve the vertical structure of cloud microphysical properties and cloud scale dynamics. Together with detailed in situ data for aerosol, cloud, water vapor and dynamics, we developed the most advanced observational capability to study cloud-scale properties and processes from a single aircraft (Fig. 1). A compact Raman lidar was also built to work together with in situ sampling to characterize boundary layer aerosol and water vapor distributions for many important atmospheric processes studies, such as, air-sea interaction and convective initialization. Case studies will be presented to illustrate these new observation capabilities.

SeaWiFS Technical Report Series. Volume 7: Cloud screening for polar orbiting visible and infrared (IR) satellite sensors

NASA Technical Reports Server (NTRS)

Darzi, Michael; Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor)

1992-01-01

Methods for detecting and screening cloud contamination from satellite derived visible and infrared data are reviewed in this document. The methods are applicable to past, present, and future polar orbiting satellite radiometers. Such instruments include the Coastal Zone Color Scanner (CZCS), operational from 1978 through 1986; the Advanced Very High Resolution Radiometer (AVHRR); the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), scheduled for launch in August 1993; and the Moderate Resolution Imaging Spectrometer (IMODIS). Constant threshold methods are the least demanding computationally, and often provide adequate results. An improvement to these methods are the least demanding computationally, and often provide adequate results. An improvement to these methods is to determine the thresholds dynamically by adjusting them according to the areal and temporal distributions of the surrounding pixels. Spatial coherence methods set thresholds based on the expected spatial variability of the data. Other statistically derived methods and various combinations of basic methods are also reviewed. The complexity of the methods is ultimately limited by the computing resources. Finally, some criteria for evaluating cloud screening methods are discussed.

Personalized medicine: from genotypes, molecular phenotypes and the quantified self, towards improved medicine.

PubMed

Dudley, Joel T; Listgarten, Jennifer; Stegle, Oliver; Brenner, Steven E; Parts, Leopold

2015-01-01

Advances in molecular profiling and sensor technologies are expanding the scope of personalized medicine beyond genotypes, providing new opportunities for developing richer and more dynamic multi-scale models of individual health. Recent studies demonstrate the value of scoring high-dimensional microbiome, immune, and metabolic traits from individuals to inform personalized medicine. Efforts to integrate multiple dimensions of clinical and molecular data towards predictive multi-scale models of individual health and wellness are already underway. Improved methods for mining and discovery of clinical phenotypes from electronic medical records and technological developments in wearable sensor technologies present new opportunities for mapping and exploring the critical yet poorly characterized "phenome" and "envirome" dimensions of personalized medicine. There are ambitious new projects underway to collect multi-scale molecular, sensor, clinical, behavioral, and environmental data streams from large population cohorts longitudinally to enable more comprehensive and dynamic models of individual biology and personalized health. Personalized medicine stands to benefit from inclusion of rich new sources and dimensions of data. However, realizing these improvements in care relies upon novel informatics methodologies, tools, and systems to make full use of these data to advance both the science and translational applications of personalized medicine.

Biochemical component identification by plasmonic improved whispering gallery mode optical resonance based sensor

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas

2014-05-01

Experimental data on detection and identification of variety of biochemical agents, such as proteins, microelements, antibiotic of different generation etc. in both single and multi component solutions under varied in wide range concentration analyzed on the light scattering parameters of whispering gallery mode optical resonance based sensor are represented. Multiplexing on parameters and components has been realized using developed fluidic sensor cell with fixed in adhesive layer dielectric microspheres and data processing. Biochemical component identification has been performed by developed network analysis techniques. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis. Novel technique based on optical resonance on microring structures, plasmon resonance and identification tools has been developed. To improve a sensitivity of microring structures microspheres fixed by adhesive had been treated previously by gold nanoparticle solution. Another technique used thin film gold layers deposited on the substrate below adhesive. Both biomolecule and nanoparticle injections caused considerable changes of optical resonance spectra. Plasmonic gold layers under optimized thickness also improve parameters of optical resonance spectra. Biochemical component identification has been also performed by developed network analysis techniques both for single and for multi component solution. So advantages of plasmon enhancing optical microcavity resonance with multiparameter identification tools is used for development of a new platform for ultra sensitive label-free biomedical sensor.

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

Applications of satellite ocean color sensors for monitoring and predicting harmful algal blooms

USGS Publications Warehouse

Stumpf, Richard P.

2001-01-01

The new satellite ocean color sensors offer a means of detecting and monitoring algal blooms in the ocean and coastal zone. Beginning with SeaWiFS (Sea Wide Field-of-view Sensor) in September 1997, these sensors provide coverage every 1 to 2 days with 1-km pixel view at nadir. Atmospheric correction algorithms designed for the coastal zone combined with regional chlorophyll algorithms can provide good and reproducible estimates of chlorophyll, providing the means of monitoring various algal blooms. Harmful algal blooms (HABs) caused by Karenia brevis in the Gulf of Mexico are particularly amenable to remote observation. The Gulf of Mexico has relatively clear water and K. brevis, in bloom conditions, tends to produce a major portion of the phytoplankton biomass. A monitoring program has begun in the Gulf of Mexico that integrates field data from state monitoring programs with satellite imagery, providing an improved capability for the monitoring of K. brevis blooms.

An Embodied Multi-Sensor Fusion Approach to Visual Motion Estimation Using Unsupervised Deep Networks.

PubMed

Shamwell, E Jared; Nothwang, William D; Perlis, Donald

2018-05-04

Aimed at improving size, weight, and power (SWaP)-constrained robotic vision-aided state estimation, we describe our unsupervised, deep convolutional-deconvolutional sensor fusion network, Multi-Hypothesis DeepEfference (MHDE). MHDE learns to intelligently combine noisy heterogeneous sensor data to predict several probable hypotheses for the dense, pixel-level correspondence between a source image and an unseen target image. We show how our multi-hypothesis formulation provides increased robustness against dynamic, heteroscedastic sensor and motion noise by computing hypothesis image mappings and predictions at 76⁻357 Hz depending on the number of hypotheses being generated. MHDE fuses noisy, heterogeneous sensory inputs using two parallel, inter-connected architectural pathways and n (1⁻20 in this work) multi-hypothesis generating sub-pathways to produce n global correspondence estimates between a source and a target image. We evaluated MHDE on the KITTI Odometry dataset and benchmarked it against the vision-only DeepMatching and Deformable Spatial Pyramids algorithms and were able to demonstrate a significant runtime decrease and a performance increase compared to the next-best performing method.

Reprocessing of multi-channel seismic-reflection data collected in the Chukchi Sea

USGS Publications Warehouse

Agena, W.F.; Lee, M.W.; Hart, P.E.

2001-01-01

Contained on this set of two CD-ROMs are stacked and migrated multi-channel seismic-reflection data for 44 lines recorded in the Chukchi Sea, northern Alaska, by the United States Geological Survey in 1977, 1978, and 1980. All data were reprocessed by the USGS in 2000 using updated methods. The resulting final data have both increased temporal and spatial resolution thus providing improved interpretability. An added benefit of these CD-ROMs is that they are a more stable, long-term archival medium for the data.

Maritime Aerosol Network optical depth measurements and comparison with satellite retrievals from various different sensors

NASA Astrophysics Data System (ADS)

Smirnov, Alexander; Petrenko, Maksym; Ichoku, Charles; Holben, Brent N.

2017-10-01

The paper reports on the current status of the Maritime Aerosol Network (MAN) which is a component of the Aerosol Robotic Network (AERONET). A public domain web-based data archive dedicated to MAN activity can be found at https://aeronet.gsfc.nasa.gov/new_web/maritime_aerosol_network.html . Since 2006 over 450 cruises were completed and the data archive consists of more than 6000 measurement days. In this work, we present MAN observations collocated with MODIS Terra, MODIS Aqua, MISR, POLDER, SeaWIFS, OMI, and CALIOP spaceborne aerosol products using a modified version of the Multi-Sensor Aerosol Products Sampling System (MAPSS) framework. Because of different spatio-temporal characteristics of the analyzed products, the number of MAN data points collocated with spaceborne retrievals varied between 1500 matchups for MODIS to 39 for CALIOP (as of August 2016). Despite these unavoidable sampling biases, latitudinal dependencies of AOD differences for all satellite sensors, except for SeaWIFS and POLDER, showed positive biases against ground truth (i.e. MAN) in the southern latitudes (<50° S), and substantial scatter in the Northern Atlantic "dust belt" (5°-15° N). Our analysis did not intend to determine whether satellite retrievals are within claimed uncertainty boundaries, but rather show where bias exists and corrections are needed.

Calibrating a novel multi-sensor physical activity measurement system.

PubMed

John, D; Liu, S; Sasaki, J E; Howe, C A; Staudenmayer, J; Gao, R X; Freedson, P S

2011-09-01

Advancing the field of physical activity (PA) monitoring requires the development of innovative multi-sensor measurement systems that are feasible in the free-living environment. The use of novel analytical techniques to combine and process these multiple sensor signals is equally important. This paper describes a novel multi-sensor 'integrated PA measurement system' (IMS), the lab-based methodology used to calibrate the IMS, techniques used to predict multiple variables from the sensor signals, and proposes design changes to improve the feasibility of deploying the IMS in the free-living environment. The IMS consists of hip and wrist acceleration sensors, two piezoelectric respiration sensors on the torso, and an ultraviolet radiation sensor to obtain contextual information (indoors versus outdoors) of PA. During lab-based calibration of the IMS, data were collected on participants performing a PA routine consisting of seven different ambulatory and free-living activities while wearing a portable metabolic unit (criterion measure) and the IMS. Data analyses on the first 50 adult participants are presented. These analyses were used to determine if the IMS can be used to predict the variables of interest. Finally, physical modifications for the IMS that could enhance the feasibility of free-living use are proposed and refinement of the prediction techniques is discussed.

Arctic and Antarctic Sea Ice Concentrations from Multichannel Passive-Microwave Satellite Data Sets: October 1978-September 1995 User's Guide

NASA Technical Reports Server (NTRS)

Cavalieri, Donald J.; Parkinson, Claire L.; Gloersen, Per; Zwally, H. Jay

1997-01-01

Satellite multichannel passive-microwave sensors have provided global radiance measurements with which to map, monitor, and study the Arctic and Antarctic polar sea ice covers. The data span over 18 years (as of April 1997), starting with the launch of the Scanning Multichannel Microwave Radiometer (SMMR) on NASA's SeaSat A and Nimbus 7 in 1978 and continuing with the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMI) series beginning in 1987. It is anticipated that the DMSP SSMI series will continue into the 21st century. The SSMI series will be augmented by new, improved sensors to be flown on Japanese and U.S. space platforms. This User's Guide provides a description of a new sea ice concentration data set generated from observations made by three of these multichannel sensors. The data set includes gridded daily ice concentrations (every-other-day for the SMMR data) for both the north and south polar regions from October 26, 1978 through September 30, 1995, with the one exception of a 6-week data gap from December 3, 1987 through January 12, 1988. The data have been placed on two CD-ROMs that include a ReadMeCD file giving the technical details on the file format, file headers, north and south polar grids, ancillary data sets, and directory structure of the CD-ROM. The CD-ROMS will be distributed by the National Snow and Ice Data Center in Boulder, CO.

The coupling of MATISSE and the SE-WORKBENCH: a new solution for simulating efficiently the atmospheric radiative transfer and the sea surface radiation

NASA Astrophysics Data System (ADS)

Cathala, Thierry; Douchin, Nicolas; Latger, Jean; Caillault, Karine; Fauqueux, Sandrine; Huet, Thierry; Lubarre, Luc; Malherbe, Claire; Rosier, Bernard; Simoneau, Pierre

2009-05-01

The SE-WORKBENCH workshop, also called CHORALE (French acceptation for "simulated Optronic Acoustic Radar battlefield") is used by the French DGA (MoD) and several other Defense organizations and companies all around the World to perform multi-sensors simulations. CHORALE enables the user to create virtual and realistic multi spectral 3D scenes that may contain several types of target, and then generate the physical signal received by a sensor, typically an IR sensor. The SE-WORKBENCH can be used either as a collection of software modules through dedicated GUIs or as an API made of a large number of specialized toolkits. The SE-WORKBENCH is made of several functional block: one for geometrically and physically modeling the terrain and the targets, one for building the simulation scenario and one for rendering the synthetic environment, both in real and non real time. Among the modules that the modeling block is composed of, SE-ATMOSPHERE is used to simulate the atmospheric conditions of a Synthetic Environment and then to integrate the impact of these conditions on a scene. This software product generates an exploitable physical atmosphere by the SE WORKBENCH tools generating spectral images. It relies on several external radiative transfer models such as MODTRAN V4.2 in the current version. MATISSE [4,5] is a background scene generator developed for the computation of natural background spectral radiance images and useful atmospheric radiative quantities (radiance and transmission along a line of sight, local illumination, solar irradiance ...). Backgrounds include atmosphere, low and high altitude clouds, sea and land. A particular characteristic of the code is its ability to take into account atmospheric spatial variability (temperatures, mixing ratio, etc) along each line of sight. An Application Programming Interface (API) is included to facilitate its use in conjunction with external codes. MATISSE is currently considered as a new external radiative transfer model to be integrated in SE-ATMOSPHERE as a complement to MODTRAN. Compared to the latter which is used as a whole MATISSE can be used step by step and modularly as an API: this can avoid to pre compute large atmospheric parameters tables as it is done currently with MODTRAN. The use of MATISSE will also enable a real coupling between the ray tracing process of the SEWORKBENCH and the radiative transfer model of MATISSE. This will lead to the improvement of the link between a general atmospheric model and a specific 3D terrain. The paper will demonstrate the advantages for the SE WORKEBNCH of using MATISSE as a new atmospheric code, but also for computing the radiative properties of the sea surface.

Feasibility analysis of marine ecological on-line integrated monitoring system

NASA Astrophysics Data System (ADS)

Chu, D. Z.; Cao, X.; Zhang, S. W.; Wu, N.; Ma, R.; Zhang, L.; Cao, L.

2017-08-01

The in-situ water quality sensors were susceptible to biological attachment. Moreover, sea water corrosion and wave impact damage, and many sensors scattered distribution would cause maintenance inconvenience. The paper proposed a highly integrated marine ecological on-line integrated monitoring system, which can be used inside monitoring station. All sensors were reasonably classified, the similar in series, the overall in parallel. The system composition and workflow were described. In addition, the paper proposed attention issues of the system design and corresponding solutions. Water quality multi-parameters and 5 nutrient salts as the verification index, in-situ and systematic data comparison experiment were carried out. The results showed that the data consistency of nutrient salt, PH and salinity was better. Temperature and dissolved oxygen data trend was consistent, but the data had deviation. Turbidity fluctuated greatly; the chlorophyll trend was similar with it. Aiming at the above phenomena, three points system optimization direction were proposed.

Tomographic wavefront retrieval by combined use of geometric and plenoptic sensors

NASA Astrophysics Data System (ADS)

Trujillo-Sevilla, J. M.; Rodríguez-Ramos, L. F.; Fernández-Valdivia, Juan J.; Marichal-Hernández, José G.; Rodríguez-Ramos, J. M.

2014-05-01

Modern astronomic telescopes take advantage of multi-conjugate adaptive optics, in which wavefront sensors play a key role. A single sensor capable of measuring wavefront phases at any angle of observation would be helpful when improving atmospheric tomographic reconstruction. A new sensor combining both geometric and plenoptic arrangements is proposed, and a simulation demonstrating its working principle is also shown. Results show that this sensor is feasible, and also that single extended objects can be used to perform tomography of atmospheric turbulence.

Current Status and Future Plan of Arctic Sea Ice monitoring in South Korea

NASA Astrophysics Data System (ADS)

Shin, J.; Park, J.

2016-12-01

Arctic sea ice is one of the most important parameters in climate. For monitoring of sea ice changes, the National Meteorological Satellite Center (NMSC) of Korea Metrological Administration has developed the "Arctic sea ice monitoring system" to retrieve the sea ice extent and surface roughness using microwave sensor data, and statistical prediction model for Arctic sea ice extent. This system has been implemented to the web site for real-time public service. The sea ice information can be retrieved using the spaceborne microwave sensor-Special Sensor Microwave Imager/Sounder (SSMI/S). The sea ice information like sea ice extent, sea ice surface roughness, and predictive sea ice extent are produced weekly base since 2007. We also publish the "Analysis report of the Arctic sea ice" twice a year. We are trying to add more sea ice information into this system. Details of current status and future plan of Arctic sea ice monitoring and the methodology of the sea ice information retrievals will be presented in the meeting.

Improved Kalman Filter Method for Measurement Noise Reduction in Multi Sensor RFID Systems

PubMed Central

Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon

2011-01-01

Recently, the range of available Radio Frequency Identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less Mean Squared Error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments. PMID:22346641

Improved Kalman filter method for measurement noise reduction in multi sensor RFID systems.

PubMed

Eom, Ki Hwan; Lee, Seung Joon; Kyung, Yeo Sun; Lee, Chang Won; Kim, Min Chul; Jung, Kyung Kwon

2011-01-01

Recently, the range of available radio frequency identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We propose in this paper an improved Kalman filter method to reduce noise and obtain correct data. Performance of Kalman filter is determined by a measurement and system noise covariance which are usually called the R and Q variables in the Kalman filter algorithm. Choosing a correct R and Q variable is one of the most important design factors for better performance of the Kalman filter. For this reason, we proposed an improved Kalman filter to advance an ability of noise reduction of the Kalman filter. The measurement noise covariance was only considered because the system architecture is simple and can be adjusted by the neural network. With this method, more accurate data can be obtained with smart RFID tags. In a simulation the proposed improved Kalman filter has 40.1%, 60.4% and 87.5% less mean squared error (MSE) than the conventional Kalman filter method for a temperature sensor, humidity sensor and oxygen sensor, respectively. The performance of the proposed method was also verified with some experiments.

AOD trends during 2001-2010 from observations and model simulations

NASA Astrophysics Data System (ADS)

Pozzer, A.; de Meij, A.; Yoon, J.; Tost, H.; Georgoulias, A. K.; Astitha, M.

2015-05-01

The aerosol optical depth (AOD) trend between 2001 and 2010 is estimated globally and regionally from observations and results from simulations with the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model. Although interannual variability is applied only to anthropogenic and biomass-burning emissions, the model is able to quantitatively reproduce the AOD trends as observed by the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor, while some discrepancies are found when compared to MISR (Multi-angle Imaging SpectroRadiometer) and SeaWIFS (Sea-viewing Wide Field-of-view Sensor) observations. Thanks to an additional simulation without any change in emissions, it is shown that decreasing AOD trends over the US and Europe are due to the decrease in the emissions, while over the Sahara Desert and the Middle East region, the meteorological changes play a major role. Over Southeast Asia, both meteorology and emissions changes are equally important in defining AOD trends. Additionally, decomposing the regional AOD trends into individual aerosol components reveals that the soluble components are the most dominant contributors to the total AOD, as their influence on the total AOD is enhanced by the aerosol water content.

The melting sea ice of Arctic polar cap in the summer solstice month and the role of ocean

NASA Astrophysics Data System (ADS)

Lee, S.; Yi, Y.

2014-12-01

The Arctic sea ice is becoming smaller and thinner than climatological standard normal and more fragmented in the early summer. We investigated the widely changing Arctic sea ice using the daily sea ice concentration data. Sea ice data is generated from brightness temperature data derived from the sensors: Defense Meteorological Satellite Program (DMSP)-F13 Special Sensor Microwave/Imagers (SSM/Is), the DMSP-F17 Special Sensor Microwave Imager/Sounder (SSMIS) and the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument on the NASA Earth Observing System (EOS) Aqua satellite. We tried to figure out appearance of arctic sea ice melting region of polar cap from the data of passive microwave sensors. It is hard to explain polar sea ice melting only by atmosphere effects like surface air temperature or wind. Thus, our hypothesis explaining this phenomenon is that the heat from deep undersea in Arctic Ocean ridges and the hydrothermal vents might be contributing to the melting of Arctic sea ice.

Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles.

PubMed

Zhu, Qingyuan; Xiao, Chunsheng; Hu, Huosheng; Liu, Yuanhui; Wu, Jinjin

2018-01-13

Articulated wheel loaders used in the construction industry are heavy vehicles and have poor stability and a high rate of accidents because of the unpredictable changes of their body posture, mass and centroid position in complex operation environments. This paper presents a novel distributed multi-sensor system for real-time attitude estimation and stability measurement of articulated wheel loaders to improve their safety and stability. Four attitude and heading reference systems (AHRS) are constructed using micro-electro-mechanical system (MEMS) sensors, and installed on the front body, rear body, rear axis and boom of an articulated wheel loader to detect its attitude. A complementary filtering algorithm is deployed for sensor data fusion in the system so that steady state margin angle (SSMA) can be measured in real time and used as the judge index of rollover stability. Experiments are conducted on a prototype wheel loader, and results show that the proposed multi-sensor system is able to detect potential unstable states of an articulated wheel loader in real-time and with high accuracy.

Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles

PubMed Central

Xiao, Chunsheng; Liu, Yuanhui; Wu, Jinjin

2018-01-01

Articulated wheel loaders used in the construction industry are heavy vehicles and have poor stability and a high rate of accidents because of the unpredictable changes of their body posture, mass and centroid position in complex operation environments. This paper presents a novel distributed multi-sensor system for real-time attitude estimation and stability measurement of articulated wheel loaders to improve their safety and stability. Four attitude and heading reference systems (AHRS) are constructed using micro-electro-mechanical system (MEMS) sensors, and installed on the front body, rear body, rear axis and boom of an articulated wheel loader to detect its attitude. A complementary filtering algorithm is deployed for sensor data fusion in the system so that steady state margin angle (SSMA) can be measured in real time and used as the judge index of rollover stability. Experiments are conducted on a prototype wheel loader, and results show that the proposed multi-sensor system is able to detect potential unstable states of an articulated wheel loader in real-time and with high accuracy. PMID:29342850

SeaWiFS Postlaunch Calibration and Validation Analyses

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); McClain, Charles R.; Ainsworth, Ewa J.; Barnes, Robert A.; Eplee, Robert E., Jr.; Patt, Frederick S.; Robinson, Wayne D.; Wang, Menghua; Bailey, Sean W.

2000-01-01

The effort to resolve data quality issues and improve on the initial data evaluation methodologies of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project was an extensive one. These evaluations have resulted, to date, in three major reprocessings of the entire data set where each reprocessing addressed the data quality issues that could be identified up to the time of each reprocessing. The number of chapters (21) needed to document this extensive work in the SeaWiFS Postlaunch Technical Report Series requires three volumes. The chapters in Volumes 9, 10, and 11 are in a logical order sequencing through sensor calibration, atmospheric correction, masks and flags, product evaluations, and bio-optical algorithms. The first chapter of Volume 9 is an overview of the calibration and validation program, including a table of activities from the inception of the SeaWiFS Project. Chapter 2 describes the fine adjustments of sensor detector knee radiances, i.e., radiance levels where three of the four detectors in each SeaWiFS band saturate. Chapters 3 and 4 describe the analyses of the lunar and solar calibration time series, respectively, which are used to track the temporal changes in radiometric sensitivity in each band. Chapter 5 outlines the procedure used to adjust band 7 relative to band 8 to derive reasonable aerosol radiances in band 7 as compared to those in band 8 in the vicinity of Lanai, Hawaii, the vicarious calibration site. Chapter 6 presents the procedure used to estimate the vicarious calibration gain adjustment factors for bands 1-6 using the waterleaving radiances from the Marine Optical Buoy (MOBY) offshore of Lanai. Chapter 7 provides the adjustments to the coccolithophore flag algorithm which were required for improved performance over the prelaunch version. Chapter 8 is an overview of the numerous modifications to the atmospheric correction algorithm that have been implemented. Chapter 9 describes the methodology used to remove artifacts of sun glint contamination for portions of the imagery outside the sun glint mask. Finally, Chapter 10 explains a modification to the ozone interpolation method to account for actual time differences between the SeaWiFS and Total Ozone Mapping Spectrometer (TOMS) orbits.

Development and applications of an acoustic package for deep-sea sub-bottom profiling and detailed seafloor imaging

NASA Astrophysics Data System (ADS)

Nishimura, Kiyokazu; Kisimoto, Kiyoyuki; Joshima, Masato; Arai, Kohsaku

In the deep-sea geological survey, good survey results are difficult to obtain by a conventional surface-towed acoustic survey system, because the horizontal resolution is limited due to the long distance between the sensor and the target (seafloor). In order to improve the horizontal resolution, a deep-tow system, which tows the sensor in the vicinity of seafloor, is most practical, and many such systems have been developed and used until today. It is not easy, however, to carry out a high-density survey in a small area by maneuvering the towing body altitude sufficiently close to the seafloor with rugged topography. A ROV (Remotely Operated Vehicle) can be used to solve this problem. The ROV makes a high-density 2D survey feasible because of its maneuverability, although a long-distance survey is difficult with it. Accordingly, we have developed an acoustic survey system installed on a ROV. The system named DAIPACK (Deep-sea Acoustic Imaging Package) consists of (1) a deep-sea sub-bottom profiler and (2) a deep-sea sidescan sonar. (1) Deep-sea sub-bottom profiler A light-weight and compact sub-bottom profiler for shallow water was chosen to improve and repackage for the deep sea usage. The system is composed of three units; a transducer, an electronic unit and a notebook computer for system control and data acquisition. The source frequency is 10kHz. To convert the system for the deep sea, the transducer was exchanged for the deep sea model, and the electronic unit was improved accordingly. The electronic unit and the notebook computer were installed in a spherical pressure vessel. (2) Deep-sea sidescan sonar We remodeled a compact shallow sea sidescan sonar(water depth limitation is 30m ) into a deep sea one. This sidescan sonar is composed of a sonar towfish (transducers and an electronic unit ), a cable and a notebook computer (data processor). To accommodate in the deep water, the transducers were remodeled into a high pressure resistance type, and the electronic unit and the computer unit were stored in a spherical pressure vessel. The frequency output of the sidescan sonar is 330kHz, and the ranging distance is variable from 15m to 120m (one side).

Machine Learning Algorithms for Automated Satellite Snow and Sea Ice Detection

NASA Astrophysics Data System (ADS)

Bonev, George

The continuous mapping of snow and ice cover, particularly in the arctic and poles, are critical to understanding the earth and atmospheric science. Much of the world's sea ice and snow covers the most inhospitable places, making measurements from satellite-based remote sensors essential. Despite the wealth of data from these instruments many challenges remain. For instance, remote sensing instruments reside on-board different satellites and observe the earth at different portions of the electromagnetic spectrum with different spatial footprints. Integrating and fusing this information to make estimates of the surface is a subject of active research. In response to these challenges, this dissertation will present two algorithms that utilize methods from statistics and machine learning, with the goal of improving on the quality and accuracy of current snow and sea ice detection products. The first algorithm aims at implementing snow detection using optical/infrared instrument data. The novelty in this approach is that the classifier is trained using ground station measurements of snow depth that are collocated with the reflectance observed at the satellite. Several classification methods are compared using this training data to identify the one yielding the highest accuracy and optimal space/time complexity. The algorithm is then evaluated against the current operational NASA snow product and it is found that it produces comparable and in some cases superior accuracy results. The second algorithm presents a fully automated approach to sea ice detection that integrates data obtained from passive microwave and optical/infrared satellite instruments. For a particular region of interest the algorithm generates sea ice maps of each individual satellite overpass and then aggregates them to a daily composite level, maximizing the amount of high resolution information available. The algorithm is evaluated at both, the individual satellite overpass level, and at the daily composite level. Results show that at the single overpass level for clear-sky regions, the developed multi-sensor algorithm performs with accuracy similar to that of the optical/infrared products, with the advantage of being able to also classify partially cloud-obscured regions with the help of passive microwave data. At the daily composite level, results show that the algorithm's performance with respect to total ice extent is in line with other daily products, with the novelty of being fully automated and having higher resolution.

Deployment operation of NanTroSEIZE C0002 riserless LTBMS

NASA Astrophysics Data System (ADS)

Kyo, N.; Saruhashi, T.; Sawada, I.; Namba, Y.; Kitada, K.; Kimura, T.; Toczko, S.; Araki, E.; Kopf, A.; IODP EXP 332 Scientists

2011-12-01

The installation of LTBMS (Long Term Borehole Monitoring System) for NanTroSEIZE (Nankai Trough Seismogenic Zone Experiment) C0002 riserless hole was successfully carried out as part of IODP Expedition 332 operations by DV Chikyu in November - December 2010. The water depth of the site and penetration depth of the hole are 1937.5 m and 980 mbsf respectively. Casing (9-5/8") was set to the depth of 888 mbsf and below the CORK head, 3-1/2" tubing was deployed inside the casing as the support structure for the downhole instruments. Within the rat hole section, two pressure ports, a strain meter, a tilt meter, a broadband seismometer, geophone, and accelerometer were deployed. These seismic and geodetic sensors were set within the borehole, and coupled to the formation via cement whose physical properties (Young's modulus, Poisson's ratio, density) were adjusted to fit the formation's properties. Screen sections were set to access the pore fluids, while isolating them from the sea floor and the lower lithological units by a swellable packer, and cement, respectively. At the top of wellhead, and at the apex of the 3-1/2" tubing assembly, a CORK head was landed. The CORK head holds the pressure sensor unit (4 pressure sensors), underwater mateable data connectors (connected to the cemented sensors), and hydraulic valves to access and sample formation fluids by ROV. The major scientific features of the Hole C0002G (riserless) LTBMS are sensors monitoring multiple parameters related to seismic, geodetic and pore fluid behavior simultaneously at distinct, multiple, layers within the same borehole. The main technical difficulties in the LTBMS development are as follows: (1) Reduction method for current-induced VIV (Vortex Induced Vibration) (2) Borehole coupling for seismic and geodetic sensors (3) Anti-vibration/shock and protection method for borehole sensors/instruments (4) Attachment and protection for sensor cables and pressure lines (5) Zone isolation for multi-layer pressure measurements (6) Wellhead system (CORK) for data connection to submarine cable network (7) Downsizing borehole instruments (installation with 3-1/2-in tubing) (8) System reliability (redundant sensor system) We carried out sea trials using a dummy sensor assembly to study the effects of deploying the assembly in strong currents, and also carried out additional pool experiments and numerical simulations to evaluate VIV countermeasures. Through shock and vibration mechanical tests, we improved the robustness of sensors and the sensor carrier. As part of these investigations, we conducted risk analysis based on the operation, science, and engineering points of view from, which helped clarify operational procedures for actual deployment. Future plans include returning to Hole C0002G site to deploy a data logger and battery for temporary observations. After examining the data quality, we'll finally connect the LTBMS to the DONET (Dense Oceanfloor Network System for Earthquakes and Tsunamis) submarine cabled network. Plans are also underway for deploying more LTBMS's into Site C0010 (riserless) and Site C0002 (riser).

Data assimilation of an airborne multiple-remote-sensor system and of satellite images for the North Sea and Baltic Sea

NASA Astrophysics Data System (ADS)

Trieschmann, Olaf; Hunsaenger, Thomas; Tufte, Lars; Barjenbruch, Ulrich

2004-02-01

Marine pollution in the sensible North and Baltic Sea forces an international aerial surveillance. Within this framework the German aerial surveillance operates an advanced instrumentation on board of two 'Dornier 228" aircrafts. The instrumentation consists of a set of state-of-the-art imaging remote sensors, like side looking airborne radar (SLAR), IR/UV line scanner and particularly a microwave radiometer (MWR) and a laser-fluoro-sensor (LFS). The most important aim is to detect oil discharges on the water surface, emitted accidentally or illegally. In case of discharge, the pollution has to be classified and quantified with a high accuracy. Another aim is to monitor biological and hydrological parameters, as there are the concentration of chlorophyll and dissolved organic matter (DOM) or the growth of phytoplancton. This paper describes the set of instruments and their potential to fulfill these demands. The SLAR operates to locate oil discharges and phytoplancton, whereas the IR/UV scanner allows to distinct the detected area. The IR/UV and especially the MWR sensor allow to quantify the thickness of the oil film. Finally, the LFS classifies the oil species as well as organic material. Emphasis is placed on the results of the sensor measurements and their synergy effects. The combination of the sensor data yields value added information for the operational users. An use of satellite data to improve the operational surveillance will be discussed. The potential and limitations of satellite and airborne data for the surveillance tasks will be compared.

Abnormal Winter Melting of the Arctic Sea Ice Cap Observed by the Spaceborne Passive Microwave Sensors

NASA Astrophysics Data System (ADS)

Lee, Seongsuk; Yi, Yu

2016-12-01

The spatial size and variation of Arctic sea ice play an important role in Earth’s climate system. These are affected by conditions in the polar atmosphere and Arctic sea temperatures. The Arctic sea ice concentration is calculated from brightness temperature data derived from the Defense Meteorological Satellite program (DMSP) F13 Special Sensor Microwave/Imagers (SSMI) and the DMSP F17 Special Sensor Microwave Imager/Sounder (SSMIS) sensors. Many previous studies point to significant reductions in sea ice and their causes. We investigated the variability of Arctic sea ice using the daily sea ice concentration data from passive microwave observations to identify the sea ice melting regions near the Arctic polar ice cap. We discovered the abnormal melting of the Arctic sea ice near the North Pole during the summer and the winter. This phenomenon is hard to explain only surface air temperature or solar heating as suggested by recent studies. We propose a hypothesis explaining this phenomenon. The heat from the deep sea in Arctic Ocean ridges and/ or the hydrothermal vents might be contributing to the melting of Arctic sea ice. This hypothesis could be verified by the observation of warm water column structure below the melting or thinning arctic sea ice through the project such as Coriolis dataset for reanalysis (CORA).

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information

PubMed Central

Wang, Xiaohong; Wang, Lizhi

2017-01-01

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system. PMID:28926930

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information.

PubMed

Wang, Jingbin; Wang, Xiaohong; Wang, Lizhi

2017-09-15

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system.

A Novel Multi-Aperture Based Sun Sensor Based on a Fast Multi-Point MEANSHIFT (FMMS) Algorithm

PubMed Central

You, Zheng; Sun, Jian; Xing, Fei; Zhang, Gao-Fei

2011-01-01

With the current increased widespread interest in the development and applications of micro/nanosatellites, it was found that we needed to design a small high accuracy satellite attitude determination system, because the star trackers widely used in large satellites are large and heavy, and therefore not suitable for installation on micro/nanosatellites. A Sun sensor + magnetometer is proven to be a better alternative, but the conventional sun sensor has low accuracy, and cannot meet the requirements of the attitude determination systems of micro/nanosatellites, so the development of a small high accuracy sun sensor with high reliability is very significant. This paper presents a multi-aperture based sun sensor, which is composed of a micro-electro-mechanical system (MEMS) mask with 36 apertures and an active pixels sensor (APS) CMOS placed below the mask at a certain distance. A novel fast multi-point MEANSHIFT (FMMS) algorithm is proposed to improve the accuracy and reliability, the two key performance features, of an APS sun sensor. When the sunlight illuminates the sensor, a sun spot array image is formed on the APS detector. Then the sun angles can be derived by analyzing the aperture image location on the detector via the FMMS algorithm. With this system, the centroid accuracy of the sun image can reach 0.01 pixels, without increasing the weight and power consumption, even when some missing apertures and bad pixels appear on the detector due to aging of the devices and operation in a harsh space environment, while the pointing accuracy of the single-aperture sun sensor using the conventional correlation algorithm is only 0.05 pixels. PMID:22163770

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.

PubMed

Pycinski, Bartlomiej; Czajkowska, Joanna; Badura, Pawel; Juszczyk, Jan; Pietka, Ewa

2016-01-01

A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

An Autonomous, Low Cost Platform for Seafloor Geodetic Observations

NASA Astrophysics Data System (ADS)

Ericksen, T.; Foster, J. H.; Bingham, B. S.

2013-12-01

The high cost of acquiring geodetic data from the sea floor has limited the observations available to help us understand and model the behavior of seafloor geodetic processes. To address this problem, the Pacific GPS Facility at the University of Hawaii is developing a cost effective approach for accurately measuring short-term vertical motions of the seafloor and maintaining a continuous long-term record of seafloor pressure without the requirement for costly ship time. There is a recognized need to vastly increase our underwater geodetic observing capacity. Most of the largest recorded earthquakes and most devastating tsunamis are generated at subduction zones underwater. Similarly, many volcanoes are partly (e.g. Santorini) or completely (e.g. Loihi) submerged, and are not well observed and understood. Furthermore, landslide features ring many ocean basins, and huge debris deposits surround many volcanic oceanic islands. Our approach will lower the cost of collecting sea-floor geodetic data, reducing the barriers preventing us from acquiring the information we need to observe and understand these types of structures and provide a direct societal benefit in improving hazard assessment. The capability is being developed by equipping one of the University of Hawaii Wave Gliders with an integrated acoustic telemetry package, a dual frequency geodetic-grade Global Positioning System (GPS) receiver, processing unit, and cellular communications. The Wave Glider will interrogate high accuracy pressure sensors on the sea floor to maintain a near-continuous stream of pressure and temperature data, but seafloor pressure data includes contribution from a variety of sources and on its own may not provide the accuracy required for geodetic investigations. Independent measurements of sea surface pressure and sea surface height can be used to remove these contributions from the observed sea floor pressure timeseries. We will integrate our seafloor pressure measurements with air pressure data, and precise vertical measurements of the sea surface from kinematic positioning of the Wave Glider over the bottom sensor, to determine cm-scale vertical seafloor motions. The seafloor package will consist of a simple tripod frame that seats the pressure sensor unit, and includes an attachment onto which an ROV can install a mobile pressure recorder (MPR) should ship and ROV time be available. Two visits with an MPR would allow calibration of the linear drift of the continuous sensor, further enhancing the value of the timeseries. The pressure sensor is recoverable and serviceable and using the MPR calibration will enable the seafloor monument to be re-occupied to extend the pressure record beyond a single 5+ year deployment. We are currently focused on retrieving high accuracy vertical sea floor motions, but, importantly, we have chosen a development approach that provides a simple upgrade path for incorporating the Wave Glider GPS-Acoustic (GPS/A) measurement system under development at SIO. With this upgrade, Wave Gliders could also acquire accurate horizontal motions of the sea floor sensors, and provide a cost-effective way of performing full, 3-dimensional, surveys of sea-floor motions.

Ice Types in the Beaufort Sea, Alaska

NASA Technical Reports Server (NTRS)

2003-01-01

Determining the amount and type of sea ice in the polar oceans is crucial to improving our knowledge and understanding of polar weather and long term climate fluctuations. These views from two satellite remote sensing instruments; the synthetic aperture radar (SAR) on board the RADARSAT satellite and the Multi-angle Imaging SpectroRadiometer (MISR), illustrate different methods that may be used to assess sea ice type. Sea ice in the Beaufort Sea off the north coast of Alaska was classified and mapped in these concurrent images acquired March 19, 2001 and mapped to the same geographic area.

To identify sea ice types, the National Oceanic and Atmospheric Administration (NOAA) National Ice Center constructs ice charts using several data sources including RADARSAT SAR images such as the one shown at left. SAR classifies sea ice types primarily by how the surface and subsurface roughness influence radar backscatter. In the SAR image, white lines delineate different sea ice zones as identified by the National Ice Center. Regions of mostly multi-year ice (A) are separated from regions with large amounts of first year and younger ice (B-D), and the dashed white line at bottom marks the coastline. In general, sea ice types that exhibit increased radar backscatter appear bright in SAR and are identified as rougher, older ice types. Younger, smoother ice types appear dark to SAR. Near the top of the SAR image, however, red arrows point to bright areas in which large, crystalline 'frost flowers' have formed on young, thin ice, causing this young ice type to exhibit an increased radar backscatter. Frost flowers are strongly backscattering at radar wavelengths (cm) due to both surface roughness and the high salinity of frost flowers, which causes them to be highly reflective to radar energy.

Surface roughness is also registered by MISR, although the roughness observed is at a different spatial scale. Older, rougher ice areas are predominantly backward scattering to the MISR cameras, whereas younger, smoother ice types are predominantly forward scattering. The MISR map at right was generated using a statistical classification routine (called ISODATA) and analyzed using ice charts from the National Ice Center. Five classes of sea ice were found based upon the classification of MISR angular data. These are described, based on interpretation of the SAR image, by the image key. Very smooth ice areas that are predominantly forward scattering are colored red. Frost flowers are largely smooth to the MISR visible band sensor and are mapped as forward scattering. Areas mapped as blue are predominantly backward scattering, and the other three classes have statistically distinct angular signatures and fall within the middle of the forward/backward scattering continuum. Some areas that may be first year or younger ice between the multi year ice floes are not discernible to SAR, illustrating how MISR potentially can make a unique contribution to sea ice mapping.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. This data product was generated from a portion of the imagery acquired during Terra orbit 6663. The MISR image has been cropped to include an area that is 200 kilometers wide, and utilizes data from blocks 30 to 33 within World Reference System-2 path 71.

MISR was built and is managed by NASA's Jet Propulsion Laboratory,Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Generic framework for vessel detection and tracking based on distributed marine radar image data

NASA Astrophysics Data System (ADS)

Siegert, Gregor; Hoth, Julian; Banyś, Paweł; Heymann, Frank

2018-04-01

Situation awareness is understood as a key requirement for safe and secure shipping at sea. The primary sensor for maritime situation assessment is still the radar, with the AIS being introduced as supplemental service only. In this article, we present a framework to assess the current situation picture based on marine radar image processing. Essentially, the framework comprises a centralized IMM-JPDA multi-target tracker in combination with a fully automated scheme for track management, i.e., target acquisition and track depletion. This tracker is conditioned on measurements extracted from radar images. To gain a more robust and complete situation picture, we are exploiting the aspect angle diversity of multiple marine radars, by fusing them a priori to the tracking process. Due to the generic structure of the proposed framework, different techniques for radar image processing can be implemented and compared, namely the BLOB detector and SExtractor. The overall framework performance in terms of multi-target state estimation will be compared for both methods based on a dedicated measurement campaign in the Baltic Sea with multiple static and mobile targets given.

Application of Artificial Neural Networks to the Development of Improved Multi-Sensor Retrievals of Near-Surface Air Temperature and Humidity Over Ocean

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Clayson, Carol Anne

2012-01-01

Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.

Sea Surface Temperature Records from the Along-Track Scanning Radiometers

NASA Astrophysics Data System (ADS)

Mutlow, C. T.; Smith, D. L.; Delderfield, J.; Llewellyn-Jones, D.

2006-12-01

Since the early 1990s ESA has flown Along Track Scanning Radiometer (ATSR) instruments on its ERS-1 and -2 satellites and is currently flying the Advanced ATSR instrument (AATSR) on its very successful Envisat mission; each successive sensor has been an incremental improvement over the last. The sensors have been specifically designed to provide the information urgently needed for the debate on climate change and global warming, as well as to produce properly calibrated image data sets for use in a wide range of EO studies. The ATSR instruments are a series of second generation space radiometers which build on the long heritage of the NOAA Advanced Very High Resolution Radiometers (AVHRR). Each ATSR exploits the multi-channel method pioneered in AVHRR but also uses new technology to improve instrument stability and calibration, detector signal to noise, and to provide observations of the same surface scene at two different angles. The novel feature of each ATSR, from which the sensor is derives its name, is its use of along-track scanning to reduce the effects of the atmosphere on surface measurements. This method obtains two observations of the scene through differing amounts of atmosphere; the "along track" view passes through a longer atmospheric path so is more affected by the atmosphere than the nadir view. ATSR-1 was launched on the ESA ERS-1 satellite on 17th July 1991, as the test-bed for the along track scanning concept using infrared channels at 1.6, 3.7, 10.8 and 12.0um. ATSR-1 continued to operate until the ERS-1 spacecraft was lost some 10 years after launch. The ATSR-2 and Advanced ATSR (AATSR) instruments are developments from the original ATSR-1, which in addition to the infrared channels; carry extra visible channels at 0.55, 0.67 and 0.87um for vegetation, cloud and aerosol remote sensing. ATSR-2 has operating on the ESA ERS-2 satellite since April 1995 and has provided over 10 years of data. The current operational sensor is AATSR flying on ESA's Envisat platform. AATSR has been largely funded by the UK Department of Environment, Food and Rural Affairs (DEFRA) in recognition of the need to provide continuity of the ATSR sea surface temperature (SST) data record for climate studies. Overlaps of the ATSR-1 and ATSR-2 missions, and subsequently ATSR-2 and AATSR have allowed cross- calibration between the sensors. A continuous archive of over 15 years of SST data from the ATSR instruments is being prepared and due for release in 2007. Further sensors based on the ATSR concept are being planned to continue this high quality dataset. Data will be presented to demonstrate the capabilities of these novel sensors and the high quality of the data sets that are produced.

Hybrid Integrated Label-Free Chemical and Biological Sensors

PubMed Central

Mehrabani, Simin; Maker, Ashley J.; Armani, Andrea M.

2014-01-01

Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach. PMID:24675757

Hybrid integrated label-free chemical and biological sensors.

PubMed

Mehrabani, Simin; Maker, Ashley J; Armani, Andrea M

2014-03-26

Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach.

Transitioning mine warfare to network-centric sensor analysis: future PMA technologies & capabilities

NASA Astrophysics Data System (ADS)

Stack, J. R.; Guthrie, R. S.; Cramer, M. A.

2009-05-01

The purpose of this paper is to outline the requisite technologies and enabling capabilities for network-centric sensor data analysis within the mine warfare community. The focus includes both automated processing and the traditional humancentric post-mission analysis (PMA) of tactical and environmental sensor data. This is motivated by first examining the high-level network-centric guidance and noting the breakdown in the process of distilling actionable requirements from this guidance. Examples are provided that illustrate the intuitive and substantial capability improvement resulting from processing sensor data jointly in a network-centric fashion. Several candidate technologies are introduced including the ability to fully process multi-sensor data given only partial overlap in sensor coverage and the ability to incorporate target identification information in stride. Finally the critical enabling capabilities are outlined including open architecture, open business, and a concept of operations. This ability to process multi-sensor data in a network-centric fashion is a core enabler of the Navy's vision and will become a necessity with the increasing number of manned and unmanned sensor systems and the requirement for their simultaneous use.

Decadal Changes in Global Ocean Annual Primary Production

NASA Technical Reports Server (NTRS)

Gregg, Watson; Conkright, Margarita E.; Behrenfeld, Michael J.; Ginoux, Paul; Casey, Nancy W.; Koblinsky, Chester J. (Technical Monitor)

2002-01-01

The Sea-viewing Wide Field-of-View Sensor (SeaWiFS) has produced the first multi-year time series of global ocean chlorophyll observations since the demise of the Coastal Zone Color Scanner (CZCS) in 1986. Global observations from 1997-present from SeaWiFS combined with observations from 1979-1986 from the CZCS should in principle provide an opportunity to observe decadal changes in global ocean annual primary production, since chlorophyll is the primary driver for estimates of primary production. However, incompatibilities between algorithms have so far precluded quantitative analysis. We have developed and applied compatible processing methods for the CZCS, using modern advances in atmospheric correction and consistent bio-optical algorithms to advance the CZCS archive to comparable quality with SeaWiFS. We applied blending methodologies, where in situ data observations are incorporated into the CZCS and SeaWiFS data records, to provide improvement of the residuals. These re-analyzed, blended data records provide maximum compatibility and permit, for the first time, a quantitative analysis of the changes in global ocean primary production in the early-to-mid 1980's and the present, using synoptic satellite observations. An intercomparison of the global and regional primary production from these blended satellite observations is important to understand global climate change and the effects on ocean biota. Photosynthesis by chlorophyll-containing phytoplankton is responsible for biotic uptake of carbon in the oceans and potentially ultimately from the atmosphere. Global ocean annual primary decreased from the CZCS record to SeaWiFS, by nearly 6% from the early 1980s to the present. Annual primary production in the high latitudes was responsible for most of the decadal change. Conversely, primary production in the low latitudes generally increased, with the exception of the tropical Pacific. The differences and similarities of the two data records provide evidence of how the Earth's climate may be changing and how ocean biota respond. Furthermore, the results have implications for the ocean carbon cycle.

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification.

PubMed

Zhou, Tao; Li, Zhaofu; Pan, Jianjun

2018-01-27

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively.

IMHRP: Improved Multi-Hop Routing Protocol for Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Huang, Jianhua; Ruan, Danwei; Hong, Yadong; Zhao, Ziming; Zheng, Hong

2017-10-01

Wireless sensor network (WSN) is a self-organizing system formed by a large number of low-cost sensor nodes through wireless communication. Sensor nodes collect environmental information and transmit it to the base station (BS). Sensor nodes usually have very limited battery energy. The batteries cannot be charged or replaced. Therefore, it is necessary to design an energy efficient routing protocol to maximize the network lifetime. This paper presents an improved multi-hop routing protocol (IMHRP) for homogeneous networks. In the IMHRP protocol, based on the distances to the BS, the CH nodes are divided into internal CH nodes and external CH nodes. The set-up phase of the protocol is based on the LEACH protocol and the minimum distance between CH nodes are limited to a special constant distance, so a more uniform distribution of CH nodes is achieved. In the steady-state phase, the routes of different CH nodes are created on the basis of the distances between the CH nodes. The energy efficiency of communication can be maximized. The simulation results show that the proposed algorithm can more effectively reduce the energy consumption of each round and prolong the network lifetime compared with LEACH protocol and MHT protocol.

Marine Physical Laboratory Multi-Disciplinary Ocean Science and Technology Program

DTIC Science & Technology

1991-04-01

ambierit noise were made with the advent of large. of 3800 m. Reflection profiles and drill logs from this hole scale seismome ter arrays." Sensor arrays...Deaion. and S C Webb."A deep-sea differential pressure frequency. The array was too limited in extent to make spa- gauge ." J. Aimos Ocean Tech. 2. 237...75, 847-864 (1985). 2"P. K Spudich andi I A. Orcutt," Petrology and porcisit% of tn oceanic "M E Dougherty and R. A. Stephen."Seismic energy

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

New sonic shockwave multi-element sensors mounted on a small airfoil flown on F-15B testbed aircraft

NASA Technical Reports Server (NTRS)

1996-01-01

An experimental device to pinpoint the location of a shockwave that develops in an aircraft flying at transonic and supersonic speeds was recently flight-tested at NASA's Dryden Flight Research Center, Edwards, California. The shock location sensor, developed by TAO Systems, Hampton, Va., utilizes a multi-element hot-film sensor array along with a constant-voltage anemometer and special diagnostic software to pinpoint the exact location of the shockwave and its characteristics as it develops on an aircraft surface. For this experiment, the 45-element sensor was mounted on the small Dryden-designed airfoil shown in this illustration. The airfoil was attached to the Flight Test Fixture mounted underneath the fuselage of Dryden's F-15B testbed aircraft. Tests were flown at transonic speeds of Mach 0.7 to 0.9, and the device isolated the location of the shock wave to within a half-inch. Application of this technology could assist designers of future supersonic aircraft in improving the efficiency of engine air inlets by controlling the shockwave, with a related improvement in aircraft performance and fuel economy.

Experiences integrating autonomous components and legacy systems into tsunami early warning systems

NASA Astrophysics Data System (ADS)

Reißland, S.; Herrnkind, S.; Guenther, M.; Babeyko, A.; Comoglu, M.; Hammitzsch, M.

2012-04-01

Fostered by and embedded in the general development of Information and Communication Technology (ICT) the evolution of Tsunami Early Warning Systems (TEWS) shows a significant development from seismic-centred to multi-sensor system architectures using additional sensors, e.g. sea level stations for the detection of tsunami waves and GPS stations for the detection of ground displacements. Furthermore, the design and implementation of a robust and scalable service infrastructure supporting the integration and utilisation of existing resources serving near real-time data not only includes sensors but also other components and systems offering services such as the delivery of feasible simulations used for forecasting in an imminent tsunami threat. In the context of the development of the German Indonesian Tsunami Early Warning System (GITEWS) and the project Distant Early Warning System (DEWS) a service platform for both sensor integration and warning dissemination has been newly developed and demonstrated. In particular, standards of the Open Geospatial Consortium (OGC) and the Organization for the Advancement of Structured Information Standards (OASIS) have been successfully incorporated. In the project Collaborative, Complex, and Critical Decision-Support in Evolving Crises (TRIDEC) new developments are used to extend the existing platform to realise a component-based technology framework for building distributed TEWS. This talk will describe experiences made in GITEWS, DEWS and TRIDEC while integrating legacy stand-alone systems and newly developed special-purpose software components into TEWS using different software adapters and communication strategies to make the systems work together in a corporate infrastructure. The talk will also cover task management and data conversion between the different systems. Practical approaches and software solutions for the integration of sensors, e.g. providing seismic and sea level data, and utilisation of special-purpose components, such as simulation systems, in TEWS will be presented.

Inland-coastal water interaction: Remote sensing application for shallow-water quality and algal blooms modeling

NASA Astrophysics Data System (ADS)

Melesse, Assefa; Hajigholizadeh, Mohammad; Blakey, Tara

2017-04-01

In this study, Landsat 8 and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) sensors were used to model the spatiotemporal changes of four water quality parameters: Landsat 8 (turbidity, chlorophyll-a (chl-a), total phosphate, and total nitrogen) and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) (algal blooms). The study was conducted in Florda bay, south Florida and model outputs were compared with in-situ observed data. The Landsat 8 based study found that, the predictive models to estimate chl-a and turbidity concentrations, developed through the use of stepwise multiple linear regression (MLR), gave high coefficients of determination in dry season (wet season) (R2 = 0.86(0.66) for chl-a and R2 = 0.84(0.63) for turbidity). Total phosphate and TN were estimated using best-fit multiple linear regression models as a function of Landsat TM and OLI,127 and ground data and showed a high coefficient of determination in dry season (wet season) (R2 = 0.74(0.69) for total phosphate and R2 = 0.82(0.82) for TN). Similarly, the ability of SeaWIFS for chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels' benthic class was evaluated. Benthic class was determined through satellite image-based classification methods. It was found that benthic class based chl-a modeling algorithm was better than the existing regionally-tuned approach. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Key words: Landsat, SeaWIFS, water quality, Florida bay, Chl-a, turbidity

Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform.

PubMed

Xu, Huile; Liu, Jinyi; Hu, Haibo; Zhang, Yi

2016-12-02

Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform (FT) or wavelet transform (WT). However, these signal processing approaches are suitable for a linear signal but not for a nonlinear signal. In this paper, we investigate the characteristics of the Hilbert-Huang transform (HHT) for dealing with activity data with properties such as nonlinearity and non-stationarity. A multi-features extraction method based on HHT is then proposed to improve the effect of activity recognition. The extracted multi-features include instantaneous amplitude (IA) and instantaneous frequency (IF) by means of empirical mode decomposition (EMD), as well as instantaneous energy density (IE) and marginal spectrum (MS) derived from Hilbert spectral analysis. Experimental studies are performed to verify the proposed approach by using the PAMAP2 dataset from the University of California, Irvine for wearable sensors-based activity recognition. Moreover, the effect of combining multi-features vs. a single-feature are investigated and discussed in the scenario of a dependent subject. The experimental results show that multi-features combination can further improve the performance measures. Finally, we test the effect of multi-features combination in the scenario of an independent subject. Our experimental results show that we achieve four performance indexes: recall, precision, F-measure, and accuracy to 0.9337, 0.9417, 0.9353, and 0.9377 respectively, which are all better than the achievements of related works.

Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform

PubMed Central

Xu, Huile; Liu, Jinyi; Hu, Haibo; Zhang, Yi

2016-01-01

Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform (FT) or wavelet transform (WT). However, these signal processing approaches are suitable for a linear signal but not for a nonlinear signal. In this paper, we investigate the characteristics of the Hilbert-Huang transform (HHT) for dealing with activity data with properties such as nonlinearity and non-stationarity. A multi-features extraction method based on HHT is then proposed to improve the effect of activity recognition. The extracted multi-features include instantaneous amplitude (IA) and instantaneous frequency (IF) by means of empirical mode decomposition (EMD), as well as instantaneous energy density (IE) and marginal spectrum (MS) derived from Hilbert spectral analysis. Experimental studies are performed to verify the proposed approach by using the PAMAP2 dataset from the University of California, Irvine for wearable sensors-based activity recognition. Moreover, the effect of combining multi-features vs. a single-feature are investigated and discussed in the scenario of a dependent subject. The experimental results show that multi-features combination can further improve the performance measures. Finally, we test the effect of multi-features combination in the scenario of an independent subject. Our experimental results show that we achieve four performance indexes: recall, precision, F-measure, and accuracy to 0.9337, 0.9417, 0.9353, and 0.9377 respectively, which are all better than the achievements of related works. PMID:27918414

Feeding rates and under-ice foraging strategies of the smallest lunge filter feeder, the Antarctic minke whale (Balaenoptera bonaerensis).

PubMed

Friedlaender, A S; Goldbogen, J A; Nowacek, D P; Read, A J; Johnston, D; Gales, N

2014-08-15

Body size and feeding mode are two fundamental characteristics that determine foraging performance and ecological niche. As the smallest obligate lunge filter feeders, minke whales represent an ideal system for studying the physical and energetic limits of filter feeding in endotherms. We used multi-sensor suction cup tags to quantify the feeding performance of Antarctic minke whales. Foraging dives around and beneath sea ice contained up to 24 lunges per dive, the highest feeding rates for any lunge-feeding whale. Their small size allows minke whales access to krill in sea-ice environments not easily accessible to larger baleen whales. Furthermore, their ability to filter feed provides an advantage over other smaller sympatric krill predators such as penguins and seals that feed on individual prey. The unique combination of body size, feeding mechanism and sea-ice habitat of Antarctic minke whales defines a previously undocumented energetic niche that is unique among aquatic vertebrates. © 2014. Published by The Company of Biologists Ltd.

Real-time sensor validation and fusion for distributed autonomous sensors

NASA Astrophysics Data System (ADS)

Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

2004-04-01

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

Routine Mapping of the Snow Depth Distribution on Sea Ice

NASA Astrophysics Data System (ADS)

Farrell, S. L.; Newman, T.; Richter-Menge, J.; Dattler, M.; Paden, J. D.; Yan, S.; Li, J.; Leuschen, C.

2016-12-01

The annual growth and retreat of the polar sea ice cover is influenced by the seasonal accumulation, redistribution and melt of snow on sea ice. Due to its high albedo and low thermal conductivity, snow is also a controlling parameter in the mass and energy budgets of the polar climate system. Under a changing climate scenario it is critical to obtain reliable and routine measurements of snow depth, across basin scales, and long time periods, so as to understand regional, seasonal and inter-annual variability, and the subsequent impacts on the sea ice cover itself. Moreover the snow depth distribution remains a significant source of uncertainty in the derivation of sea ice thickness from remote sensing measurements, as well as in numerical model predictions of future climate state. Radar altimeter systems flown onboard NASA's Operation IceBridge (OIB) mission now provide annual measurements of snow across both the Arctic and Southern Ocean ice packs. We describe recent advances in the processing techniques used to interpret airborne radar waveforms and produce accurate and robust snow depth results. As a consequence of instrument effects and data quality issues associated with the initial release of the OIB airborne radar data, the entire data set was reprocessed to remove coherent noise and sidelobes in the radar echograms. These reprocessed data were released to the community in early 2016, and are available for improved derivation of snow depth. Here, using the reprocessed data, we present the results of seven years of radar measurements collected over Arctic sea ice at the end of winter, just prior to melt. Our analysis provides the snow depth distribution on both seasonal and multi-year sea ice. We present the inter-annual variability in snow depth for both the Central Arctic and the Beaufort/Chukchi Seas. We validate our results via comparison with temporally and spatially coincident in situ measurements gathered during many of the OIB surveys. The results will influence future sensor suite development for sea ice studies, and they provide a new metric for comparison with other sea ice observations. Integrating these novel snow depth observations with modeling studies will help inform model development, and advance our predictive capabilities to help better understand how sea ice is responding to a changing climate.

Marker-Based Multi-Sensor Fusion Indoor Localization System for Micro Air Vehicles.

PubMed

Xing, Boyang; Zhu, Quanmin; Pan, Feng; Feng, Xiaoxue

2018-05-25

A novel multi-sensor fusion indoor localization algorithm based on ArUco marker is designed in this paper. The proposed ArUco mapping algorithm can build and correct the map of markers online with Grubbs criterion and K-mean clustering, which avoids the map distortion due to lack of correction. Based on the conception of multi-sensor information fusion, the federated Kalman filter is utilized to synthesize the multi-source information from markers, optical flow, ultrasonic and the inertial sensor, which can obtain a continuous localization result and effectively reduce the position drift due to the long-term loss of markers in pure marker localization. The proposed algorithm can be easily implemented in a hardware of one Raspberry Pi Zero and two STM32 micro controllers produced by STMicroelectronics (Geneva, Switzerland). Thus, a small-size and low-cost marker-based localization system is presented. The experimental results show that the speed estimation result of the proposed system is better than Px4flow, and it has the centimeter accuracy of mapping and positioning. The presented system not only gives satisfying localization precision, but also has the potential to expand other sensors (such as visual odometry, ultra wideband (UWB) beacon and lidar) to further improve the localization performance. The proposed system can be reliably employed in Micro Aerial Vehicle (MAV) visual localization and robotics control.

Evaluation of Unmanned Aircraft Systems (UAS) for Weather and Climate using the Multi-testbed approach

NASA Astrophysics Data System (ADS)

Baker, B.; Lee, T.; Buban, M.; Dumas, E. J.

2017-12-01

Evaluation of Unmanned Aircraft Systems (UAS) for Weather and Climate using the Multi-testbed approachC. Bruce Baker1, Ed Dumas1,2, Temple Lee1,2, Michael Buban1,21NOAA ARL, Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN2Oak Ridge Associated Universities, Oak Ridge, TN The development of a small Unmanned Aerial System (sUAS) testbeds that can be used to validate, integrate, calibrate and evaluate new technology and sensors for routine boundary layer research, validation of operational weather models, improvement of model parameterizations, and recording observations within high-impact storms is important for understanding the importance and impact of using sUAS's routinely as a new observing platform. The goal of the multi-testbed approach is to build a robust set of protocols to assess the cost and operational feasibility of unmanned observations for routine applications using various combinations of sUAS aircraft and sensors in different locations and field experiments. All of these observational testbeds serve different community needs, but they also use a diverse suite of methodologies for calibration and evaluation of different sensors and platforms for severe weather and boundary layer research. The primary focus will be to evaluate meteorological sensor payloads to measure thermodynamic parameters and define surface characteristics with visible, IR, and multi-spectral cameras. This evaluation will lead to recommendations for sensor payloads for VTOL and fixed-wing sUAS.

Environmental Variability in the Florida Keys: Impacts on Coral Reef Resilience and Health

NASA Astrophysics Data System (ADS)

Soto, I. M.; Muller-Karger, F. E.

2005-12-01

Environmental variability contributes to both mass mortality and resilience in tropical coral reef communities. We assess variations in sea surface temperature (SST) and ocean color in the Florida Keys using satellite imagery, and provide insight into how this variability is associated with locations of resilient coral communities (those unaffected by or able to recover from major events). The project tests the hypothesis that areas with historically low environmental variability promote lower levels of coral reef resilience. Time series of SST from the Advanced Very High Resolution Radiometer (AVHRR) sensors and ocean color derived quantities (e.g., turbidity and chlorophyll) from the Sea-viewing Wide Field of View Sensor (SeaWiFS) are being constructed over the entire Florida Keys region for a period of twelve and nine years, respectively. These data will be compared with historical coral cover data derived from Landsat imagery (1984-2002). Improved understanding of the causes of coral reef decline or resilience will help protect and manage these natural treasures.

A Novel Energy-Efficient Multi-Sensor Fusion Wake-Up Control Strategy Based on a Biomimetic Infectious-Immune Mechanism for Target Tracking.

PubMed

Zhou, Jie; Liang, Yan; Shen, Qiang; Feng, Xiaoxue; Pan, Quan

2018-04-18

A biomimetic distributed infection-immunity model (BDIIM), inspired by the immune mechanism of an infected organism, is proposed in order to achieve a high-efficiency wake-up control strategy based on multi-sensor fusion for target tracking. The resultant BDIIM consists of six sub-processes reflecting the infection-immunity mechanism: occurrence probabilities of direct-infection (DI) and cross-infection (CI), immunity/immune-deficiency of DI and CI, pathogen amount of DI and CI, immune cell production, immune memory, and pathogen accumulation under immunity state. Furthermore, a corresponding relationship between the BDIIM and sensor wake-up control is established to form the collaborative wake-up method. Finally, joint surveillance and target tracking are formulated in the simulation, in which we show that the energy cost and position tracking error are reduced to 50.8% and 78.9%, respectively. Effectiveness of the proposed BDIIM algorithm is shown, and this model is expected to have a significant role in guiding the performance improvement of multi-sensor networks.

Multi-centennial Record of Labrador Sea Primary Productivity and Sea-Ice Variability Archived in Coralline Algal Ba/Ca

NASA Astrophysics Data System (ADS)

Chan, Phoebe; Halfar, Jochen; Adey, Walter; Hetzinger, Steffen; Zack, Thomas; Moore, Kent; Wortmann, Ulrich; Williams, Branwen; Hou, Alicia

2017-04-01

Arctic sea-ice thickness and concentration have dropped by approximately 9% per decade since 1978. Concurrent with this sea-ice decline is an increase in rates of phytoplankton productivity, driven by shoaling of the mixed layer and enhanced transmittance of solar radiation into the surface ocean. This has recently been confirmed by phytoplankton studies in Arctic and Subarctic basins that have revealed earlier timing, prolonged duration, and increased primary productivity of the spring phytoplankton bloom. However, difficulties of navigating in remote ice-laden waters and harsh polar climates have often resulted in short and incomplete records of in-situ plankton abundance in the northwestern Labrador Sea. Alternatively, information of past ocean productivity may be gained through the study of trace nutrient distributions in the surface water column. Investigations of dissolved barium (Ba) concentrations in the Arctic reveal significant depletions of Ba in surface seawaters due to biological scavenging during the spring phytoplankton bloom. Here we apply a barium-to-calcium (Ba/Ca) and carbon isotope (δ13C) multiproxy approach to long-lived crustose coralline algae in order to reconstruct an annually-resolved multi-centennial record of Labrador Sea productivity related to sea-ice variability in Labrador, Canada that extends well into the Little Ice Age (LIA; 1646 AD). The crustose coralline alga Clathromorphum compactum is a shallow marine calcareous plant that is abundant along the eastern Canadian coastline, and produces annual growth increments which allow for the precise calendar dating and geochemical sampling of hard tissue. Algal Ba/Ca ratios can serve as a promising new proxy for surface water productivity, demonstrating a close correspondence to δ13C that does not suffer from the anthropogenically-induced carbon isotope decline (ex. Suess Effect) beginning in the 1960s. Coralline algal Ba/Ca demonstrates statistically significant correlations to both observational and proxy records of sea-ice extent and transport variability, and shows a persistent pattern of covariability that is broadly consistent with the timing and phasing of the Atlantic Multidecadal Oscillation (AMO). Lower algal Ba/Ca values are interpreted as increased productivity (via biological scavenging) coinciding with warming sea surface temperatures and melting of sea-ice, and vice versa. This relationship is further supported by negative correlations between algal Ba/Ca and spatially averaged chlorophyll α concentrations determined from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS; 1998 - 2009) ocean colour data. Extended comparisons to a multi-centennial tree-ring proxy AMO index demonstrates more frequent positive Ba/Ca excursions (indicating reduced productivity) associated with AMO cool phases during the Little Ice Age, followed by a step-wise decline in Ba/Ca (indicating increasing productivity) from 1910 to present levels - unprecedented in the last 365 years. Our multi-centennial record of coralline algal Ba/Ca in the Subarctic northwest Atlantic demonstrates a long-term increasing trend in primary productivity that is in agreement with recent satellite-based productivity in the Arctic Ocean. This ongoing increase in phytoplankton productivity is expected to fundamentally alter marine biodiversity and trophic dynamics as warming and freshening of the surface layer is projected to intensify over the coming century.

Impact of the initialisation on the predictability of the Southern Ocean sea ice at interannual to multi-decadal timescales

NASA Astrophysics Data System (ADS)

Zunz, Violette; Goosse, Hugues; Dubinkina, Svetlana

2014-05-01

In this study, we assess systematically the impact of different initialisation procedures on the predictability of the sea ice in the Southern Ocean. These initialisation strategies are based on three data assimilation methods: the nudging, the particle filter with sequential resampling and the nudging proposal particle filter. An Earth-system model of intermediate complexity has been used to perform hindcast simulations in a perfect model approach. The predictability of the Southern Ocean sea ice is estimated through two aspects: the spread of the hindcast ensemble, indicating the uncertainty on the ensemble, and the correlation between the ensemble mean and the pseudo-observations, used to assess the accuracy of the prediction. Our results show that, at decadal timescales, more sophisticated data assimilation methods as well as denser pseudo-observations used to initialise the hindcasts decrease the spread of the ensemble but improve only slightly the accuracy of the prediction of the sea ice in the Southern Ocean. Overall, the predictability at interannual timescales is limited, at most, to three years ahead. At multi-decadal timescales, there is a clear improvement of the correlation of the trend in sea ice extent between the hindcasts and the pseudo-observations if the initialisation takes into account the pseudo-observations. The correlation reaches values larger than 0.5 and is due to the inertia of the ocean, showing the importance of the quality of the initialisation below the sea ice.

An Overview of SIMBIOS Program Activities and Accomplishments. Chapter 1

NASA Technical Reports Server (NTRS)

Fargion, Giulietta S.; McClain, Charles R.

2003-01-01

The SIMBIOS Program was conceived in 1994 as a result of a NASA management review of the agency's strategy for monitoring the bio-optical properties of the global ocean through space-based ocean color remote sensing. At that time, the NASA ocean color flight manifest included two data buy missions, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Earth Observing System (EOS) Color, and three sensors, two Moderate Resolution Imaging Spectroradiometers (MODIS) and the Multi-angle Imaging Spectro-Radiometer (MISR), scheduled for flight on the EOS-Terra and EOS-Aqua satellites. The review led to a decision that the international assemblage of ocean color satellite systems provided ample redundancy to assure continuous global coverage, with no need for the EOS Color mission. At the same time, it was noted that non-trivial technical difficulties attended the challenge (and opportunity) of combining ocean color data from this array of independent satellite systems to form consistent and accurate global bio-optical time series products. Thus, it was announced at the October 1994 EOS Interdisciplinary Working Group meeting that some of the resources budgeted for EOS Color should be redirected into an intercalibration and validation program (McClain et al., 2002).

Robust infrared targets tracking with covariance matrix representation

NASA Astrophysics Data System (ADS)

Cheng, Jian

2009-07-01

Robust infrared target tracking is an important and challenging research topic in many military and security applications, such as infrared imaging guidance, infrared reconnaissance, scene surveillance, etc. To effectively tackle the nonlinear and non-Gaussian state estimation problems, particle filtering is introduced to construct the theory framework of infrared target tracking. Under this framework, the observation probabilistic model is one of main factors for infrared targets tracking performance. In order to improve the tracking performance, covariance matrices are introduced to represent infrared targets with the multi-features. The observation probabilistic model can be constructed by computing the distance between the reference target's and the target samples' covariance matrix. Because the covariance matrix provides a natural tool for integrating multiple features, and is scale and illumination independent, target representation with covariance matrices can hold strong discriminating ability and robustness. Two experimental results demonstrate the proposed method is effective and robust for different infrared target tracking, such as the sensor ego-motion scene, and the sea-clutter scene.

Multifuctional integrated sensors (MFISES).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Homeijer, Brian D.; Roozeboom, Clifton

2015-10-01

Many emerging IoT applications require sensing of multiple physical and environmental parameters for: completeness of information, measurement validation, unexpected demands, improved performance. For example, a typical outdoor weather station measures temperature, humidity, barometric pressure, light intensity, rainfall, wind speed and direction. Existing sensor technologies do not directly address the demand for cost, size, and power reduction in multi-paramater sensing applications. Industry sensor manufacturers have developed integrated sensor systems for inertial measurements that combine accelerometers, gyroscopes, and magnetometers, but do not address environmental sensing functionality. In existing research literature, a technology gap exists between the functionality of MEMS sensors and themore » real world applications of the sensors systems.« less

Sea ice motion measurements from Seasat SAR images

NASA Technical Reports Server (NTRS)

Leberl, F.; Raggam, J.; Elachi, C.; Campbell, W. J.

1983-01-01

Data from the Seasat synthetic aperture radar (SAR) experiment are analyzed in order to determine the accuracy of this information for mapping the distribution of sea ice and its motion. Data from observations of sea ice in the Beaufort Sea from seven sequential orbits of the satellite were selected to study the capabilities and limitations of spaceborne radar application to sea-ice mapping. Results show that there is no difficulty in identifying homologue ice features on sequential radar images and the accuracy is entirely controlled by the accuracy of the orbit data and the geometric calibration of the sensor. Conventional radargrammetric methods are found to serve well for satellite radar ice mapping, while ground control points can be used to calibrate the ice location and motion measurements in the cases where orbit data and sensor calibration are lacking. The ice motion was determined to be approximately 6.4 + or - 0.5 km/day. In addition, the accuracy of pixel location was found over land areas. The use of one control point in 10,000 sq km produced an accuracy of about + or 150 m, while with a higher density of control points (7 in 1000 sq km) the location accuracy improves to the image resolution of + or - 25 m. This is found to be applicable for both optical and digital data.

An Improved Scheduling Algorithm for Data Transmission in Ultrasonic Phased Arrays with Multi-Group Ultrasonic Sensors

PubMed Central

Tang, Wenming; Liu, Guixiong; Li, Yuzhong; Tan, Daji

2017-01-01

High data transmission efficiency is a key requirement for an ultrasonic phased array with multi-group ultrasonic sensors. Here, a novel FIFOs scheduling algorithm was proposed and the data transmission efficiency with hardware technology was improved. This algorithm includes FIFOs as caches for the ultrasonic scanning data obtained from the sensors with the output data in a bandwidth-sharing way, on the basis of which an optimal length ratio of all the FIFOs is achieved, allowing the reading operations to be switched among all the FIFOs without time slot waiting. Therefore, this algorithm enhances the utilization ratio of the reading bandwidth resources so as to obtain higher efficiency than the traditional scheduling algorithms. The reliability and validity of the algorithm are substantiated after its implementation in the field programmable gate array (FPGA) technology, and the bandwidth utilization ratio and the real-time performance of the ultrasonic phased array are enhanced. PMID:29035345

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor

PubMed Central

Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-01-01

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times. PMID:29393862

On-Line Temperature Estimation for Noisy Thermal Sensors Using a Smoothing Filter-Based Kalman Predictor.

PubMed

Li, Xin; Ou, Xingtao; Li, Zhi; Wei, Henglu; Zhou, Wei; Duan, Zhemin

2018-02-02

Dynamic thermal management (DTM) mechanisms utilize embedded thermal sensors to collect fine-grained temperature information for monitoring the real-time thermal behavior of multi-core processors. However, embedded thermal sensors are very susceptible to a variety of sources of noise, including environmental uncertainty and process variation. This causes the discrepancies between actual temperatures and those observed by on-chip thermal sensors, which seriously affect the efficiency of DTM. In this paper, a smoothing filter-based Kalman prediction technique is proposed to accurately estimate the temperatures from noisy sensor readings. For the multi-sensor estimation scenario, the spatial correlations among different sensor locations are exploited. On this basis, a multi-sensor synergistic calibration algorithm (known as MSSCA) is proposed to improve the simultaneous prediction accuracy of multiple sensors. Moreover, an infrared imaging-based temperature measurement technique is also proposed to capture the thermal traces of an advanced micro devices (AMD) quad-core processor in real time. The acquired real temperature data are used to evaluate our prediction performance. Simulation shows that the proposed synergistic calibration scheme can reduce the root-mean-square error (RMSE) by 1.2 ∘ C and increase the signal-to-noise ratio (SNR) by 15.8 dB (with a very small average runtime overhead) compared with assuming the thermal sensor readings to be ideal. Additionally, the average false alarm rate (FAR) of the corrected sensor temperature readings can be reduced by 28.6%. These results clearly demonstrate that if our approach is used to perform temperature estimation, the response mechanisms of DTM can be triggered to adjust the voltages, frequencies, and cooling fan speeds at more appropriate times.

Conceptualizing strategic environmental assessment: Principles, approaches and research directions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noble, Bram, E-mail: b.noble@usask.ca; Nwanekezie, Kelechi

Increasing emphasis has been placed in recent years on transitioning strategic environmental assessment (SEA) away from its environmental impact assessment (EIA) roots. Scholars have argued the need to conceptualize SEA as a process designed to facilitate strategic thinking, thus enabling transitions toward sustainability. The practice of SEA, however, remains deeply rooted in the EIA tradition and scholars and practitioners often appear divided on the nature and purpose of SEA. This paper revisits the strategic principles of SEA and conceptualizes SEA as a multi-faceted and multi-dimensional assessment process. It is suggested that SEA can be conceptualized as series of approaches operatingmore » along a spectrum from less to more strategic – from impact assessment-based to strategy-based – with each approach to SEA differentiated by the specific objectives of SEA application and the extent to which strategic principles are reflected in its design and implementation. Advancing the effectiveness of SEA requires a continued research agenda focused on improving the traditional SEA approach, as a tool to assess the impacts of policies, plans and programs (PPPs). Realizing the full potential of SEA, however, requires a new research agenda — one focused on the development and testing of a deliberative governance approach to SEA that can facilitate strategic innovations in PPP formulation and drive transitions in short-term policy and initiatives based on longer-term thinking. - Highlights: • SEA facilitates strategic thinking, enabling transitions toward sustainability. • SEA is conceptualized as a spectrum of approaches, from IA-based to strategy-based. • Each approach variably emphasizes strategic principles in its design and practice. • There is no one conceptualization of SEA that is best, SEA is fit for PPP purpose. • Research is needed to advance SEA to facilitate strategic PPP transformations.« less

Digital sun sensor multi-spot operation.

PubMed

Rufino, Giancarlo; Grassi, Michele

2012-11-28

The operation and test of a multi-spot digital sun sensor for precise sun-line determination is described. The image forming system consists of an opaque mask with multiple pinhole apertures producing multiple, simultaneous, spot-like images of the sun on the focal plane. The sun-line precision can be improved by averaging multiple simultaneous measures. Nevertheless, the sensor operation on a wide field of view requires acquiring and processing images in which the number of sun spots and the related intensity level are largely variable. To this end, a reliable and robust image acquisition procedure based on a variable shutter time has been considered as well as a calibration function exploiting also the knowledge of the sun-spot array size. Main focus of the present paper is the experimental validation of the wide field of view operation of the sensor by using a sensor prototype and a laboratory test facility. Results demonstrate that it is possible to keep high measurement precision also for large off-boresight angles.

A Synchronous Multi-Body Sensor Platform in a Wireless Body Sensor Network: Design and Implementation

PubMed Central

Gil, Yeongjoon; Wu, Wanqing; Lee, Jungtae

2012-01-01

Background Human life can be further improved if diseases and disorders can be predicted before they become dangerous, by correctly recognizing signals from the human body, so in order to make disease detection more precise, various body-signals need to be measured simultaneously in a synchronized manner. Object This research aims at developing an integrated system for measuring four signals (EEG, ECG, respiration, and PPG) and simultaneously producing synchronous signals on a Wireless Body Sensor Network. Design We designed and implemented a platform for multiple bio-signals using Bluetooth communication. Results First, we developed a prototype board and verified the signals from the sensor platform using frequency responses and quantities. Next, we designed and implemented a lightweight, ultra-compact, low cost, low power-consumption Printed Circuit Board. Conclusion A synchronous multi-body sensor platform is expected to be very useful in telemedicine and emergency rescue scenarios. Furthermore, this system is expected to be able to analyze the mutual effects among body signals. PMID:23112605

Skylab

NASA Image and Video Library

1973-09-01

This Earth Resource Experiment Package (EREP) photograph of the Uncompahgre area of Colorado was electronically acquired in September of 1973 by the Multi-spectral Scarner, Skylab Experiment S192. EREP images were used to analyze the vegetation conditions and landscape characteristic of this area. Skylab's Earth sensors played the dual roles of gathering information about the planet and perfecting instruments and techniques for future satellites and manned stations. An array of six fixed cameras, another for high resolution, and the astronauts' handheld cameras photographed surface features. Other instruments, recording on magnetic tape, measured the reflectivity of plants, soils, and water. Radar measured the altitude of land and water surfaces. The sensors' objectives were to survey croplands and forests, identify soils and rock types, map natural features and urban developments, detect sediments and the spread of pollutants, study clouds and the sea, and determine the extent of snow and ice cover.

Non-covalently anchored multi-walled carbon nanotubes with hexa-decafluorinated zinc phthalocyanine as ppb level chemiresistive chlorine sensor

NASA Astrophysics Data System (ADS)

Sharma, Anshul Kumar; Mahajan, Aman; Bedi, R. K.; Kumar, Subodh; Debnath, A. K.; Aswal, D. K.

2018-01-01

A cost effective solution assembly method has been explored for preparing zinc(II)1,2,3,4,8,9,10,11,15,16,17,18,22,23,24,25-hexa-decafluoro-29H,31H-phthalocyanine/multi-walled carbon nanotubes (F16ZnPc/MWCNTs-COOH) hybrid. Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy, transmission electron microscopy (TEM) and field emission scanning electron microscopy (FE-SEM) investigations confirm the non-covalent anchoring of F16ZnPc onto MWCNTs-COOH through п-п stacking interactions. Further, a highly sensitive and selective chemiresistive Cl2 sensor has been fabricated using F16ZnPc/MWCNTs-COOH hybrid. The response of sensor is found to be 21.28% for 2 ppm of Cl2 with a response time of 14 s and theoretical detection limit of the sensor is found down to 0.06 ppb. The improved Cl2 sensing characteristics of hybrid are found to be originated from the synergetic interaction between F16ZnPc and MWCNTs-COOH. The underlying mechanism for improved gas sensing performance of F16ZnPc/MWCNTs-COOH sensor towards Cl2 has been explained using Raman, X-ray photoelectron spectroscopy (XPS) and electrochemical impedance spectroscopy (EIS) studies.

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration

PubMed Central

Badura, Pawel; Juszczyk, Jan; Pietka, Ewa

2016-01-01

Purpose A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. Methods We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. Results The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. Conclusion The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers. PMID:27434396

Optimized star sensors laboratory calibration method using a regularization neural network.

PubMed

Zhang, Chengfen; Niu, Yanxiong; Zhang, Hao; Lu, Jiazhen

2018-02-10

High-precision ground calibration is essential to ensure the performance of star sensors. However, the complex distortion and multi-error coupling have brought great difficulties to traditional calibration methods, especially for large field of view (FOV) star sensors. Although increasing the complexity of models is an effective way to improve the calibration accuracy, it significantly increases the demand for calibration data. In order to achieve high-precision calibration of star sensors with large FOV, a novel laboratory calibration method based on a regularization neural network is proposed. A multi-layer structure neural network is designed to represent the mapping of the star vector and the corresponding star point coordinate directly. To ensure the generalization performance of the network, regularization strategies are incorporated into the net structure and the training algorithm. Simulation and experiment results demonstrate that the proposed method can achieve high precision with less calibration data and without any other priori information. Compared with traditional methods, the calibration error of the star sensor decreased by about 30%. The proposed method can satisfy the precision requirement for large FOV star sensors.

Ramifications of a potential gap in passive microwave data for the long-term sea ice climate record

NASA Astrophysics Data System (ADS)

Meier, W.; Stewart, J. S.

2017-12-01

The time series of sea ice concentration and extent from passive microwave sensors is one of the longest satellite-derived climate records and the significant decline in Arctic sea ice extent is one of the most iconic indicators of climate change. However, this continuous and consistent record is under threat due to the looming gap in passive microwave sensor coverage. The record started in late 1978 with the launch of the Scanning Multichannel Microwave Radiometer (SMMR) and has continued with a series of Special Sensor Microwave Imager (SSMI) and Special Sensor Microwave Imager and Sounder (SSMIS) instruments on U.S. Defense Meteorological Satellite Program (DMSP) satellites. The data from the different sensors are intercalibrated at the algorithm level by adjusting algorithm coefficients so that the output sea ice data is as consistent as possible between the older and the newer sensor. A key aspect in constructing the time series is to have at least two sensors operating simultaneously so that data from the older and newer sensor can be obtained from the same locations. However, with recent losses of the DMSP F19 and F20, the remaining SSMIS sensors are all well beyond their planned mission lifetime. This means that risk of failure is not small and is increasing with each day of operation. The newest passive microwave sensor, the JAXA Advanced Microwave Scanning Radiometer-2 (AMSR2), is a potential contributor to the time series (though it too is now beyond it's planned 5-year mission lifetime). However, AMSR2's larger antenna and higher spatial resolution presents a challenge in integrating its data with the rest of the sea ice record because the ice edge is quite sensitive to the sensor resolution, which substantially affects the total sea ice extent and area estimates. This will need to be adjusted for if AMSR2 is used to continue the time series. Here we will discuss efforts at NSIDC to integrate AMSR2 estimates into the sea ice climate record if needed. We will also discuss potential contingency plans, such as using operational sea ice charts, to fill any gaps. This would allow the record to continue, but the consistency of the time series will be degraded because the ice charts use human analysis and differing sources, amounts and quality of input data, which makes them sub-optimal for long-term climate records.

Late summer sea ice segmentation with multi-polarisation SAR features in C- and X-band

NASA Astrophysics Data System (ADS)

Fors, A. S.; Brekke, C.; Doulgeris, A. P.; Eltoft, T.; Renner, A. H. H.; Gerland, S.

2015-09-01

In this study we investigate the potential of sea ice segmentation by C- and X-band multi-polarisation synthetic aperture radar (SAR) features during late summer. Five high-resolution satellite SAR scenes were recorded in the Fram Strait covering iceberg-fast first-year and old sea ice during a week with air temperatures varying around zero degrees Celsius. In situ data consisting of sea ice thickness, surface roughness and aerial photographs were collected during a helicopter flight at the site. Six polarimetric SAR features were extracted for each of the scenes. The ability of the individual SAR features to discriminate between sea ice types and their temporally consistency were examined. All SAR features were found to add value to sea ice type discrimination. Relative kurtosis, geometric brightness, cross-polarisation ratio and co-polarisation correlation angle were found to be temporally consistent in the investigated period, while co-polarisation ratio and co-polarisation correlation magnitude were found to be temporally inconsistent. An automatic feature-based segmentation algorithm was tested both for a full SAR feature set, and for a reduced SAR feature set limited to temporally consistent features. In general, the algorithm produces a good late summer sea ice segmentation. Excluding temporally inconsistent SAR features improved the segmentation at air temperatures above zero degrees Celcius.

Development and Sensing Properties Study of Underwater Assembled Water Depth-Inclination Sensors for a Multi-Component Mooring System, Using a Self-Contained Technique

PubMed Central

Wu, Wenhua; Feng, Jiaguo; Xie, Bin; Tang, Da; Yue, Qianjin; Xie, Ribin

2016-01-01

Prototype monitoring techniques play an important role in the safety guarantee of mooring systems in marine engineering. In general, the complexities of harsh ocean environmental conditions bring difficulties to the traditional monitoring methods of application, implementation and maintenance. Large amounts of existing mooring systems still lack valid monitoring strategies. In this paper, an underwater monitoring method which may be used to achieve the mechanical responses of a multi-point catenary mooring system, is present. A novel self-contained assembled water depth-inclination (D-I) sensor is designed and manufactured. Several advanced technologies, such as standalone, low power consumption and synchronism, are considered to satisfy the long-term implementation requirements with low cost during the design process. The design scheme of the water resistance barrel and installation clamp, which satisfies the diver installation, are also provided in the paper. An on-site test has previously been carried out on a production semisubmersible platform in the South China Sea. The prototype data analyses, including the D-I value in the time domain (including the data recorded during the mooring retraction and release process) and spectral characteristics, are presented to reveal the accuracy, feasibility and stability of the sensor in terms of fitting for the prototype monitoring of catenary mooring systems, especially for in-service aging platforms. PMID:27854357

ESONET LIDO Demonstration Mission: the East Sicily node

NASA Astrophysics Data System (ADS)

Riccobene, Giorgio; Favali, Paolo; Andrè, Michel; Chierici, Francesco; Pavan, Gianni; Esonet Lido Demonstration Mission Team

2010-05-01

Off East Sicily (at 2100 m depth, 25 km off the harbour of Catania) a prototype of a cabled deep-sea observatory (NEMO-SN1) was set up and has been operational in real-time since 2005 (the cabled deep-sea multi-parameter station SN1, equipped with geophysical and environmental sensors and the cabled NEMO-OνDE, equipped with 4 broadband hydrophones). The Western Ionian Sea is one of the node sites for the upcoming European permanent underwater network (EMSO). Within the activities of the EC project ESONET-NoE some demonstration missions have been funded. The LIDO-DM (Listening to the Deep Ocean-Demonstration Mission) is one of these and is related to two sites, East Sicily and Iberian Margin (Gulf of Cadiz), the main aims being geo-hazards monitoring and warning (seismic, tsunami, and volcanic) and bio-acoustics. The LIDO-DM East Sicily installation represents a further major step within ESONET-NoE, resulting in a fully integrated system for multidisciplinary deep-sea science, capable to transmit and distribute data in real time to the scientific community and to the general public. LIDO-DM East Sicily hosts a large number of sensors aimed at monitoring and studying oceanographic and environmental parameters (by means of CTD, ADCP, 3-C single point current meter, turbidity meter), geophysical phenomena (low frequency hydrophones, accelerometer, gravity meter, vector and scalar magnetometers, seismometer, absolute and differential pressure gauges), ocean noise monitoring and identification and tracking of biological acoustic sources in deep sea. The latter will be performed using two tetrahedral arrays of 4 hydrophones, located at a relative distance of about 5 km, and at about 25 km from the shore. The whole system will be connected and powered from shore, by means of the electro-optical cable net installed at the East Sicily Site Infrastructure, and synchronised with GPS. Sensors data sampling is performed underwater and transmitted via optical fibre link, with optimal S/N ratio for all signals. This will also permit real-time data acquisition, analysis and distribution on-shore. Innovative electronics for the off-shore data acquisition and transmission systems has been designed, built and tested. A dedicated computing and networking infrastructure for data acquisition, storage and distribution through the internet has been also created. The deployment and connection of the deep sea structures will be performed using the dedicated ROV and Deep Sea Shuttle handling facilities (PEGASO, owned by INGV and INFN). LIDO-DM constitutes the enhancement of the Western Ionian site in view of the EMSO Research Infrastructure.

Integrated monitoring of wind plant systems

NASA Astrophysics Data System (ADS)

Whelan, Matthew J.; Janoyan, Kerop D.; Qiu, Tong

2008-03-01

Wind power is a renewable source of energy that is quickly gaining acceptance by many. Advanced sensor technologies have currently focused solely on improving wind turbine rotor aerodynamics and increasing of the efficiency of the blade design and concentration. Alternatively, potential improvements in wind plant efficiency may be realized through reduction of reactionary losses of kinetic energy to the structural and substructural systems supporting the turbine mechanics. Investigation of the complete dynamic structural response of the wind plant is proposed using a large-scale, high-rate wireless sensor network. The wireless network enables sensors to be placed across the sizable structure, including the rotating blades, without consideration of cabling issues and the economic burden associated with large spools of measurement cables. A large array of multi-axis accelerometers is utilized to evaluate the modal properties of the system as well as individual members and would enable long-term structural condition monitoring of the wind turbine as well. Additionally, environmental parameters, including wind speed, temperature, and humidity, are wirelessly collected for correlation. Such a wireless system could be integrated with electrical monitoring sensors and actuators and incorporated into a remote multi-turbine centralized plant monitoring and control system.

Evaluation of Potential Test Environments for Assessing the Impact of Multi-Sensor Data Fusion on Command and Control Operations in the HALIFAX Class Frigate

DTIC Science & Technology

2001-05-01

specifying the gaming area and land masses , the meteorological and ocean environments, and the sea conditions that exist within the gaming area. Unlike...exchanges 1.12. Customise env1ronment for data collection 1.12.1. Extra audio and v1deo 1.12.2. Add on software modules 1.13. Standalone keypads...State boards No, could be added Manuals I Charts IT acpacs I Post its I etc. No, could be added 1.11 Customise environment for data collection Ability

Enhanced sensitivity of self-assembled-monolayer-based SPR immunosensor for detection of benzaldehyde using a single-step multi-sandwich immunoassay.

PubMed

Gobi, K Vengatajalabathy; Matsumoto, Kiyoshi; Toko, Kiyoshi; Ikezaki, Hidekazu; Miura, Norio

2007-04-01

This paper describes the fabrication and sensing characteristics of a self-assembled monolayer (SAM)-based surface plasmon resonance (SPR) immunosensor for detection of benzaldehyde (BZ). The functional sensing surface was fabricated by the immobilization of a benzaldehyde-ovalbumin conjugate (BZ-OVA) on Au-thiolate SAMs containing carboxyl end groups. Covalent binding of BZ-OVA on SAM was found to be dependent on the composition of the base SAM, and it is improved very much with the use of a mixed monolayer strategy. Based on SPR angle measurements, the functional sensor surface is established as a compact monolayer of BZ-OVA bound on the mixed SAM. The BZ-OVA-bound sensor surface undergoes immunoaffinity binding with anti-benzaldehyde antibody (BZ-Ab) selectively. An indirect inhibition immunoassay principle has been applied, in which analyte benzaldehyde solution was incubated with an optimal concentration of BZ-Ab for 5 min and injected over the sensor chip. Analyte benzaldehyde undergoes immunoreaction with BZ-Ab and makes it inactive for binding to BZ-OVA on the sensor chip. As a result, the SPR angle response decreases with an increase in the concentration of benzaldehyde. The fabricated immunosensor demonstrates a low detection limit (LDL) of 50 ppt (pg mL(-1)) with a response time of 5 min. Antibodies bound to the sensor chip during an immunoassay could be detached by a brief exposure to acidic pepsin. With this surface regeneration, reusability of the same sensor chip for as many as 30 determination cycles has been established. Sensitivity has been enhanced further with the application of an additional single-step multi-sandwich immunoassay step, in which the BZ-Ab bound to the sensor chip was treated with a mixture of biotin-labeled secondary antibody, streptavidin and biotin-bovine serum albumin (Bio-BSA) conjugate. With this approach, the SPR sensor signal increased by ca. 12 times and the low detection limit improved to 5 ppt with a total response time of no more than ca. 10 min. Figure A single-step multi-sandwich immunoassay step increases SPR sensor signal by ca. 12 times affording a low detection limit for benzaldehyde of 5 ppt.

High Frequency, Long Time Series Measurements from the Bermuda Testbed Mooring in Support of SIMBIOS. Chapter 8

NASA Technical Reports Server (NTRS)

Dickey, Tommy; Dobeck, Laura; Sigurdson, David; Zedler, Sarah; Manov, Derek; Yu, Xuri

2001-01-01

It has been recognized that optical moorings are important platforms for the validation of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS). It was recommended that optical moorings be maintained in order to: (1) provide long-term time series comparisons between in situ and SeaWIFS measurements of normalized water-leaving radiance; (2) develop and test algorithms for pigment biomass and phytoplankton primary productivity; and (3) provide long-term, virtually continuous in situ observations which can be used to determine and optimize the accuracy of derived satellite products. These applications require the use of in situ radiometers for long periods of time to evaluate and correct for inherent satellite undersampling (aliasing and biasing) and degradation of satellite color sensors (e.g., drifts as experienced by the Coastal Zone Color Scanner). The Bermuda Testbed Mooring (BTM) program was initiated in 1994 at a site located about 80km southeast of Bermuda in waters of about 4530 m depth. In August 1997, with NASA's support, we started to provide the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) program with large volumes of high frequency, long-term time-series bio-optical data from the BTM for SeaWiFS satellite ocean color groundtruthing and algorithm development. This NASA supported portion of the BTM activity spanned three years and covered five BTM deployments. During these three years, the quality of radiometric data has improved dramatically. Excellent agreement between BTM moored data and both SeaWiFS and nearby ship profile radiometric data demonstrate that technical advances in the moored optical observations have reduced the major difficulties that moored platforms face: biofouling and less frequent calibration.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

NASA Astrophysics Data System (ADS)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Towards Simpler Custom and OpenSearch Services for Voluminous NEWS Merged A-Train Data (Invited)

NASA Astrophysics Data System (ADS)

Hua, H.; Fetzer, E.; Braverman, A. J.; Lewis, S.; Henderson, M. L.; Guillaume, A.; Lee, S.; de La Torre Juarez, M.; Dang, H. T.

2010-12-01

To simplify access to large and complex satellite data sets for climate analysis and model verification, we developed web services that is used to study long-term and global-scale trends in climate, water and energy cycle, and weather variability. A related NASA Energy and Water Cycle Study (NEWS) task has created a merged NEWS Level 2 data from multiple instruments in NASA’s A-Train constellation of satellites. We used this data to enable creation of climatologies that include correlation between observed temperature, water vapor and cloud properties from the A-Train sensors. Instead of imposing on the user an often rigid and limiting web-based analysis environment, we recognize the need for simple and well-designed services so that users can perform analysis in their own familiar computing environments. Custom on-demand services were developed to improve data accessibility of voluminous multi-sensor data. Services enabling geospatial, geographical, and multi-sensor parameter subsets of the data, as well a custom time-averaged Level 3 service will be presented. We will also show how a Level 3Q data reduction approach can be used to help “browse” the voluminous multi-sensor Level 2 data. An OpenSearch capability with full text + space + time search of data products will also be presented as an approach to facilitated interoperability with other data systems. We will present our experiences for improving user usability as well as strategies for facilitating interoperability with other data systems.

Improving Kinematic Accuracy of Soft Wearable Data Gloves by Optimizing Sensor Locations

PubMed Central

Kim, Dong Hyun; Lee, Sang Wook; Park, Hyung-Soon

2016-01-01

Bending sensors enable compact, wearable designs when used for measuring hand configurations in data gloves. While existing data gloves can accurately measure angular displacement of the finger and distal thumb joints, accurate measurement of thumb carpometacarpal (CMC) joint movements remains challenging due to crosstalk between the multi-sensor outputs required to measure the degrees of freedom (DOF). To properly measure CMC-joint configurations, sensor locations that minimize sensor crosstalk must be identified. This paper presents a novel approach to identifying optimal sensor locations. Three-dimensional hand surface data from ten subjects was collected in multiple thumb postures with varied CMC-joint flexion and abduction angles. For each posture, scanned CMC-joint contours were used to estimate CMC-joint flexion and abduction angles by varying the positions and orientations of two bending sensors. Optimal sensor locations were estimated by the least squares method, which minimized the difference between the true CMC-joint angles and the joint angle estimates. Finally, the resultant optimal sensor locations were experimentally validated. Placing sensors at the optimal locations, CMC-joint angle measurement accuracies improved (flexion, 2.8° ± 1.9°; abduction, 1.9° ± 1.2°). The proposed method for improving the accuracy of the sensing system can be extended to other types of soft wearable measurement devices. PMID:27240364

Multi-Sensor Fusion with Interacting Multiple Model Filter for Improved Aircraft Position Accuracy

PubMed Central

Cho, Taehwan; Lee, Changho; Choi, Sangbang

2013-01-01

The International Civil Aviation Organization (ICAO) has decided to adopt Communications, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) as the 21st century standard for navigation. Accordingly, ICAO members have provided an impetus to develop related technology and build sufficient infrastructure. For aviation surveillance with CNS/ATM, Ground-Based Augmentation System (GBAS), Automatic Dependent Surveillance-Broadcast (ADS-B), multilateration (MLAT) and wide-area multilateration (WAM) systems are being established. These sensors can track aircraft positions more accurately than existing radar and can compensate for the blind spots in aircraft surveillance. In this paper, we applied a novel sensor fusion method with Interacting Multiple Model (IMM) filter to GBAS, ADS-B, MLAT, and WAM data in order to improve the reliability of the aircraft position. Results of performance analysis show that the position accuracy is improved by the proposed sensor fusion method with the IMM filter. PMID:23535715

Multi-sensor fusion with interacting multiple model filter for improved aircraft position accuracy.

PubMed

Cho, Taehwan; Lee, Changho; Choi, Sangbang

2013-03-27

The International Civil Aviation Organization (ICAO) has decided to adopt Communications, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) as the 21st century standard for navigation. Accordingly, ICAO members have provided an impetus to develop related technology and build sufficient infrastructure. For aviation surveillance with CNS/ATM, Ground-Based Augmentation System (GBAS), Automatic Dependent Surveillance-Broadcast (ADS-B), multilateration (MLAT) and wide-area multilateration (WAM) systems are being established. These sensors can track aircraft positions more accurately than existing radar and can compensate for the blind spots in aircraft surveillance. In this paper, we applied a novel sensor fusion method with Interacting Multiple Model (IMM) filter to GBAS, ADS-B, MLAT, and WAM data in order to improve the reliability of the aircraft position. Results of performance analysis show that the position accuracy is improved by the proposed sensor fusion method with the IMM filter.

Point Cloud Refinement with a Target-Free Intrinsic Calibration of a Mobile Multi-Beam LIDAR System

NASA Astrophysics Data System (ADS)

Nouiraa, H.; Deschaud, J. E.; Goulettea, F.

2016-06-01

LIDAR sensors are widely used in mobile mapping systems. The mobile mapping platforms allow to have fast acquisition in cities for example, which would take much longer with static mapping systems. The LIDAR sensors provide reliable and precise 3D information, which can be used in various applications: mapping of the environment; localization of objects; detection of changes. Also, with the recent developments, multi-beam LIDAR sensors have appeared, and are able to provide a high amount of data with a high level of detail. A mono-beam LIDAR sensor mounted on a mobile platform will have an extrinsic calibration to be done, so the data acquired and registered in the sensor reference frame can be represented in the body reference frame, modeling the mobile system. For a multibeam LIDAR sensor, we can separate its calibration into two distinct parts: on one hand, we have an extrinsic calibration, in common with mono-beam LIDAR sensors, which gives the transformation between the sensor cartesian reference frame and the body reference frame. On the other hand, there is an intrinsic calibration, which gives the relations between the beams of the multi-beam sensor. This calibration depends on a model given by the constructor, but the model can be non optimal, which would bring errors and noise into the acquired point clouds. In the litterature, some optimizations of the calibration parameters are proposed, but need a specific routine or environment, which can be constraining and time-consuming. In this article, we present an automatic method for improving the intrinsic calibration of a multi-beam LIDAR sensor, the Velodyne HDL-32E. The proposed approach does not need any calibration target, and only uses information from the acquired point clouds, which makes it simple and fast to use. Also, a corrected model for the Velodyne sensor is proposed. An energy function which penalizes points far from local planar surfaces is used to optimize the different proposed parameters for the corrected model, and we are able to give a confidence value for the calibration parameters found. Optimization results on both synthetic and real data are presented.

Effects of Atmospheric Water and Surface Wind on Passive Microwave Retrievals of Sea Ice Concentration: a Simulation Study

NASA Astrophysics Data System (ADS)

Shin, D.; Chiu, L. S.; Clemente-Colon, P.

2006-05-01

The atmospheric effects on the retrieval of sea ice concentration from passive microwave sensors are examined using simulated data typical for the Arctic summer. The simulation includes atmospheric contributions of cloud liquid water, water vapor and surface wind on the microwave signatures. A plane parallel radiative transfer model is used to compute brightness temperatures at SSM/I frequencies over surfaces that contain open water, first-year (FY) ice and multi-year (MY) ice and their combinations. Synthetic retrievals in this study use the NASA Team (NT) algorithm for the estimation of sea ice concentrations. This study shows that if the satellite sensor's field of view is filled with only FY ice the retrieval is not much affected by the atmospheric conditions due to the high contrast between emission signals from FY ice surface and the signals from the atmosphere. Pure MY ice concentration is generally underestimated due to the low MY ice surface emissivity that results in the enhancement of emission signals from the atmospheric parameters. Simulation results in marginal ice areas also show that the atmospheric effects from cloud liquid water, water vapor and surface wind tend to degrade the accuracy at low sea ice concentration. FY ice concentration is overestimated and MY ice concentration is underestimated in the presence of atmospheric water and surface wind at low ice concentration. This compensating effect reduces the retrieval uncertainties of total (FY and MY) ice concentration. Over marginal ice zones, our results suggest that strong surface wind is more important than atmospheric water in contributing to the retrieval errors of total ice concentrations in the normal ranges of these variables.

Spectral and spatial resolution analysis of multi sensor satellite data for coral reef mapping: Tioman Island, Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet; Kabiri, Keivan

2012-07-01

This paper describes an assessment of coral reef mapping using multi sensor satellite images such as Landsat ETM, SPOT and IKONOS images for Tioman Island, Malaysia. The study area is known to be one of the best Islands in South East Asia for its unique collection of diversified coral reefs and serves host to thousands of tourists every year. For the coral reef identification, classification and analysis, Landsat ETM, SPOT and IKONOS images were collected processed and classified using hierarchical classification schemes. At first, Decision tree classification method was implemented to separate three main land cover classes i.e. water, rural and vegetation and then maximum likelihood supervised classification method was used to classify these main classes. The accuracy of the classification result is evaluated by a separated test sample set, which is selected based on the fieldwork survey and view interpretation from IKONOS image. Few types of ancillary data in used are: (a) DGPS ground control points; (b) Water quality parameters measured by Hydrolab DS4a; (c) Sea-bed substrates spectrum measured by Unispec and; (d) Landcover observation photos along Tioman island coastal area. The overall accuracy of the final classification result obtained was 92.25% with the kappa coefficient is 0.8940. Key words: Coral reef, Multi-spectral Segmentation, Pixel-Based Classification, Decision Tree, Tioman Island

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification

PubMed Central

Pan, Jianjun

2018-01-01

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively. PMID:29382073

Classification methods for monitoring Arctic sea ice using OKEAN passive/active two-channel microwave data

USGS Publications Warehouse

Belchansky, Gennady I.; Douglas, David C.

2000-01-01

This paper presents methods for classifying Arctic sea ice using both passive and active (2-channel) microwave imagery acquired by the Russian OKEAN 01 polar-orbiting satellite series. Methods and results are compared to sea ice classifications derived from nearly coincident Special Sensor Microwave Imager (SSM/I) and Advanced Very High Resolution Radiometer (AVHRR) image data of the Barents, Kara, and Laptev Seas. The Russian OKEAN 01 satellite data were collected over weekly intervals during October 1995 through December 1997. Methods are presented for calibrating, georeferencing and classifying the raw active radar and passive microwave OKEAN 01 data, and for correcting the OKEAN 01 microwave radiometer calibration wedge based on concurrent 37 GHz horizontal polarization SSM/I brightness temperature data. Sea ice type and ice concentration algorithms utilized OKEAN's two-channel radar and passive microwave data in a linear mixture model based on the measured values of brightness temperature and radar backscatter, together with a priori knowledge about the scattering parameters and natural emissivities of basic sea ice types. OKEAN 01 data and algorithms tended to classify lower concentrations of young or first-year sea ice when concentrations were less than 60%, and to produce higher concentrations of multi-year sea ice when concentrations were greater than 40%, when compared to estimates produced from SSM/I data. Overall, total sea ice concentration maps derived independently from OKEAN 01, SSM/I, and AVHRR satellite imagery were all highly correlated, with uniform biases, and mean differences in total ice concentration of less than four percent (sd<15%).

Data fusion algorithm for rapid multi-mode dust concentration measurement system based on MEMS

NASA Astrophysics Data System (ADS)

Liao, Maohao; Lou, Wenzhong; Wang, Jinkui; Zhang, Yan

2018-03-01

As single measurement method cannot fully meet the technical requirements of dust concentration measurement, the multi-mode detection method is put forward, as well as the new requirements for data processing. This paper presents a new dust concentration measurement system which contains MEMS ultrasonic sensor and MEMS capacitance sensor, and presents a new data fusion algorithm for this multi-mode dust concentration measurement system. After analyzing the relation between the data of the composite measurement method, the data fusion algorithm based on Kalman filtering is established, which effectively improve the measurement accuracy, and ultimately forms a rapid data fusion model of dust concentration measurement. Test results show that the data fusion algorithm is able to realize the rapid and exact concentration detection.

The EUMETSAT sea ice concentration climate data record

NASA Astrophysics Data System (ADS)

Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Toudal Pedersen, Leif; Høyer, Jacob L.; Kern, Stefan

2016-09-01

An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea ice concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice concentration climate data record is available for download at www.osi-saf.org, including documentation.

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

Overview of Shipboard Data Fusion and Resource Management R&D Results and Rationale for Its Real-Time Implementation in the ASCACT Testbed

DTIC Science & Technology

1996-04-01

and IRST sensor simulations. More specifically, the CPF radars currently supported by the CASE_ATTI sensor module are the SG-150 Sea Giraffe and the...specifications. The current A WW sensor suite of the CPF comprises the SPS-49 long range 2-D radar, the Sea Giraffe medium range 2-D radar, the CANEWS ESM...Sea Giraffe . This represents an original novelty of our simulation environment. P435278.PDF [Page: 66 of 128] UNCLASSIFIED 50 The baseline

Enhancement of NH3 gas sensitivity at room temperature by carbon nanotube-based sensor coated with Co nanoparticles.

PubMed

Nguyen, Lich Quang; Phan, Pho Quoc; Duong, Huyen Ngoc; Nguyen, Chien Duc; Nguyen, Lam Huu

2013-01-30

Multi-walled carbon nanotube (MWCNT) film has been fabricated onto Pt-patterned alumina substrates using the chemical vapor deposition method for NH(3) gas sensing applications. The MWCNT-based sensor is sensitive to NH(3) gas at room temperature. Nanoclusters of Co catalysts have been sputtered on the surface of the MWCNT film to enhance gas sensitivity with respect to unfunctionalized CNT films. The gas sensitivity of Co-functionalized MWCNT-based gas sensors is thus significantly improved. The sensor exhibits good repeatability and high selectivity towards NH(3), compared with alcohol and LPG.

A Real Time System for Multi-Sensor Image Analysis through Pyramidal Segmentation

DTIC Science & Technology

1992-01-30

A Real Time Syte for M~ulti- sensor Image Analysis S. E I0 through Pyramidal Segmentation/ / c •) L. Rudin, S. Osher, G. Koepfler, J.9. Morel 7. ytu...experiments with reconnaissance photography, multi- sensor satellite imagery, medical CT and MRI multi-band data have shown a great practi- cal potential...C ,SF _/ -- / WSM iS-I-0-d41-40450 $tltwt, kw" I (nor.- . Z-97- A real-time system for multi- sensor image analysis through pyramidal segmentation

Multi-Purpose Avionic Architecture for Vision Based Navigation Systems for EDL and Surface Mobility Scenarios

NASA Astrophysics Data System (ADS)

Tramutola, A.; Paltro, D.; Cabalo Perucha, M. P.; Paar, G.; Steiner, J.; Barrio, A. M.

2015-09-01

Vision Based Navigation (VBNAV) has been identified as a valid technology to support space exploration because it can improve autonomy and safety of space missions. Several mission scenarios can benefit from the VBNAV: Rendezvous & Docking, Fly-Bys, Interplanetary cruise, Entry Descent and Landing (EDL) and Planetary Surface exploration. For some of them VBNAV can improve the accuracy in state estimation as additional relative navigation sensor or as absolute navigation sensor. For some others, like surface mobility and terrain exploration for path identification and planning, VBNAV is mandatory. This paper presents the general avionic architecture of a Vision Based System as defined in the frame of the ESA R&T study “Multi-purpose Vision-based Navigation System Engineering Model - part 1 (VisNav-EM-1)” with special focus on the surface mobility application.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

PubMed

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

2015-12-26

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

PubMed Central

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X.

2015-01-01

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols. PMID:26712764

Multi-Wavelength Based Optical Density Sensor for Autonomous Monitoring of Microalgae

PubMed Central

Jia, Fei; Kacira, Murat; Ogden, Kimberly L.

2015-01-01

A multi-wavelength based optical density sensor unit was designed, developed, and evaluated to monitor microalgae growth in real time. The system consisted of five main components including: (1) laser diode modules as light sources; (2) photodiodes as detectors; (3) driver circuit; (4) flow cell; and (5) sensor housing temperature controller. The sensor unit was designed to be integrated into any microalgae culture system for both real time and non-real time optical density measurements and algae growth monitoring applications. It was shown that the sensor unit was capable of monitoring the dynamics and physiological changes of the microalgae culture in real-time. Algae biomass concentration was accurately estimated with optical density measurements at 650, 685 and 780 nm wavelengths used by the sensor unit. The sensor unit was able to monitor cell concentration as high as 1.05 g·L−1 (1.51 × 108 cells·mL−1) during the culture growth without any sample preparation for the measurements. Since high cell concentrations do not need to be diluted using the sensor unit, the system has the potential to be used in industrial microalgae cultivation systems for real time monitoring and control applications that can lead to improved resource use efficiency. PMID:26364640

Highly Stable and Flexible Pressure Sensors with Modified Multi-Walled Carbon Nanotube/Polymer Composites for Human Monitoring

PubMed Central

He, Yin; Ming, Yue; Li, Wei; Li, Yafang; Wu, Maoqi; Song, Jinzhong; Li, Xiaojiu; Liu, Hao

2018-01-01

A facile method for preparing an easy processing, repeatable and flexible pressure sensor was presented via the synthesis of modified multi-walled carbon nanotubes (m-MWNTs) and polyurethane (PU) films. The surface modification of multi-walled carbon nanotubes (MWNTs) simultaneously used a silane coupling agent (KH550) and sodium dodecyl benzene sulfonate (SDBS) to improve the dispersibility and compatibility of the MWNTs in a polymer matrix. The electrical property and piezoresistive behavior of the m-MWNT/PU composites were compared with raw multi-walled carbon nanotube (raw MWNT)/PU composites. Under linear uniaxial pressure, the m-MWNT/PU composite exhibited 4.282%kPa−1 sensitivity within the pressure of 1 kPa. The nonlinear error, hysteresis error and repeatability error of the piezoresistivity of m-MWNT/PU decreased 9%, 16.72% and 54.95% relative to raw MWNT/PU respectively. Therefore, the piezoresistive response of m-MWNT/PU had better stability than that of raw MWNT/PU composites. The m-MWNT/PU sensors could be utilized in wearable devices for body movement detection, monitoring of respiration and pressure detection in garments. PMID:29701643

Highly Stable and Flexible Pressure Sensors with Modified Multi-Walled Carbon Nanotube/Polymer Composites for Human Monitoring.

PubMed

He, Yin; Ming, Yue; Li, Wei; Li, Yafang; Wu, Maoqi; Song, Jinzhong; Li, Xiaojiu; Liu, Hao

2018-04-26

A facile method for preparing an easy processing, repeatable and flexible pressure sensor was presented via the synthesis of modified multi-walled carbon nanotubes (m-MWNTs) and polyurethane (PU) films. The surface modification of multi-walled carbon nanotubes (MWNTs) simultaneously used a silane coupling agent (KH550) and sodium dodecyl benzene sulfonate (SDBS) to improve the dispersibility and compatibility of the MWNTs in a polymer matrix. The electrical property and piezoresistive behavior of the m-MWNT/PU composites were compared with raw multi-walled carbon nanotube (raw MWNT)/PU composites. Under linear uniaxial pressure, the m-MWNT/PU composite exhibited 4.282%kPa −1 sensitivity within the pressure of 1 kPa. The nonlinear error, hysteresis error and repeatability error of the piezoresistivity of m-MWNT/PU decreased 9%, 16.72% and 54.95% relative to raw MWNT/PU respectively. Therefore, the piezoresistive response of m-MWNT/PU had better stability than that of raw MWNT/PU composites. The m-MWNT/PU sensors could be utilized in wearable devices for body movement detection, monitoring of respiration and pressure detection in garments.

Developments of next generation of seafloor observatories in MARsite project

NASA Astrophysics Data System (ADS)

Italiano, Francesco; Favali, Paolo; Zaffuto, Alfonso; Zora, Marco; D'Anca, Fabio

2015-04-01

The development of new generation of autonomous sea-floor observatories is among the aims of the EC supersite project MARsite (MARMARA Supersite; FP7 EC-funded project, grant n° 308417). An approach based on multiparameter seafloor observatories is considered of basic importance to better understand the role of the fluids in an active tectonic system and their behaviour during the development of the seismogenesis. To continuously collect geochemical and geophysical data from the immediate vicinity of the submerged North Anatolian Fault Zone (NAFZ) is one of the possibilities to contribute to the seismic hazard minimization of the Marmara area. The planning of next generation of seafloor observatories for geo-hazard monitoring is a task in one of the MARsite Work Packages (WP8). The activity is carried out combining together either the experience got after years of investigating fluids and their interactions with the seafloor and tectonic structures and the long-term experience on the development and management of permanent seafloor observatories in the main frame of the EMSO (European Multidisciplinary Seafloor and water-column Observatory, www.emso-eu.org) Research Infrastructure. The new generation of seafloor observatories have to support the observation of both slow and quick variations, thus allow collecting low and high-frequency signals besides the storage of long-term dataset and/or enable the near-real-time mode data transmission. Improvements of some the seafloor equipments have been done so far within MARsite project in terms of the amount of contemporary active instruments, their interlink with "smart sensor" capacities (threshold detection, triggering), quality of the collected data and power consumption reduction. In order to power the multiparameter sensors the digitizer and the microprocessor, an electronic board named PMS (Power Management System) with multi-master, multi-slave, single-ended, serial bus Inter-Integrated Circuit (I²C) interface has been designed, and the prototype is under test. To reduce energy consumption an embedded system has been used. All the parts of the data acquisition module are integrated in a compact and reliable aluminum frame that can be easily fitted inside vessels for tests in the marine environment. The module also includes two solid-state drives for data storage and connectors for integration with other devices and sensors. The ongoing testing activity is aimed to check the three main advances obtained so far: an open architecture of the system, very low power consumption and the possibility of digitizing at 24 bit signals from a large variety of analog sensors. The tests are carried out in the extreme marine environment of the submarine hydrothermal system of Panarea (Aeolian islands), where tectonic and volcanic activities are the responsible for the November 2002 submarine explosion which is the only submarine volcanic event recorded in the Mediterranean sea in recent times. The tests include corrosion resistance of the materials, data recording, storage and transmission. The tests are carried out using two sets of sensors, very different in terms of data acquisition frequency: temperature and pressure probes and hydrophones.

Multi-Temporal Multi-Sensor Analysis of Urbanization and Environmental/Climate Impact in China for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Ban, Yifang; Gong, Peng; Gamba, Paolo; Taubenbock, Hannes; Du, Peijun

2016-08-01

The overall objective of this research is to investigate multi-temporal, multi-scale, multi-sensor satellite data for analysis of urbanization and environmental/climate impact in China to support sustainable planning. Multi- temporal multi-scale SAR and optical data have been evaluated for urban information extraction using innovative methods and algorithms, including KTH- Pavia Urban Extractor, Pavia UEXT, and an "exclusion- inclusion" framework for urban extent extraction, and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Various pixel- based and object-based change detection algorithms were also developed to extract urban changes. Several Chinese cities including Beijing, Shanghai and Guangzhou are selected as study areas. Spatio-temporal urbanization patterns and environmental impact at regional, metropolitan and city core were evaluated through ecosystem service, landscape metrics, spatial indices, and/or their combinations. The relationship between land surface temperature and land-cover classes was also analyzed.The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal SAR data with the KTH-Pavia Urban Extractor and UEXT. The fusion of SAR data at multiple scales from multiple sensors was proven to improve urban extraction. For urban land cover mapping, the results show that the fusion of multitemporal SAR and optical data could produce detailed land cover maps with improved accuracy than that of SAR or optical data alone. Pixel-based and object-based change detection algorithms developed with the project were effective to extract urban changes. Comparing the urban land cover results from mulitemporal multisensor data, the environmental impact analysis indicates major losses for food supply, noise reduction, runoff mitigation, waste treatment and global climate regulation services through landscape structural changes in terms of decreases in service area, edge contamination and fragmentation. In terms ofclimate impact, the results indicate that land surface temperature can be related to land use/land cover classes.

Modeling UV-B Effects on Primary Production Throughout the Southern Ocean Using Multi-Sensor Satellite Data

NASA Technical Reports Server (NTRS)

Lubin, Dan

2001-01-01

This study has used a combination of ocean color, backscattered ultraviolet, and passive microwave satellite data to investigate the impact of the springtime Antarctic ozone depletion on the base of the Antarctic marine food web - primary production by phytoplankton. Spectral ultraviolet (UV) radiation fields derived from the satellite data are propagated into the water column where they force physiologically-based numerical models of phytoplankton growth. This large-scale study has been divided into two components: (1) the use of Total Ozone Mapping Spectrometer (TOMS) and Special Sensor Microwave Imager (SSM/I) data in conjunction with radiative transfer theory to derive the surface spectral UV irradiance throughout the Southern Ocean; and (2) the merging of these UV irradiances with the climatology of chlorophyll derived from SeaWiFS data to specify the input data for the physiological models.

Highly Sensitive, Transparent, and Durable Pressure Sensors Based on Sea-Urchin Shaped Metal Nanoparticles.

PubMed

Lee, Donghwa; Lee, Hyungjin; Jeong, Youngjun; Ahn, Yumi; Nam, Geonik; Lee, Youngu

2016-11-01

Highly sensitive, transparent, and durable pressure sensors are fabricated using sea-urchin-shaped metal nanoparticles and insulating polyurethane elastomer. The pressure sensors exhibit outstanding sensitivity (2.46 kPa -1 ), superior optical transmittance (84.8% at 550 nm), fast response/relaxation time (30 ms), and excellent operational durability. In addition, the pressure sensors successfully detect minute movements of human muscles. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Note on the Temporary Misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery

NASA Technical Reports Server (NTRS)

Storey, James; Roy, David P.; Masek, Jeffrey; Gascon, Ferran; Dwyer, John; Choate, Michael

2016-01-01

The Landsat-8 and Sentinel-2 sensors provide multi-spectral image data with similar spectral and spatial characteristics that together provide improved temporal coverage globally. Both systems are designed to register Level 1 products to a reference image framework, however, the Landsat-8 framework, based upon the Global Land Survey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38 m (2sigma). These misalignments vary geographically but should be stable for a given area. The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. In the interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of interest and if appropriate to reproject the data to better alignment.

A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery

USGS Publications Warehouse

Storey, James C.; Roy, David P.; Masek, Jeffrey; Gascon, Ferran; Dwyer, John L.; Choate, Michael J.

2016-01-01

The Landsat-8 and Sentinel-2 sensors provide multi-spectral image data with similar spectral and spatial characteristics that together provide improved temporal coverage globally. Both systems are designed to register Level 1 products to a reference image framework, however, the Landsat-8 framework, based upon the Global Land Survey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38 m (2σ). These misalignments vary geographically but should be stable for a given area. The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. In the interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of interest and if appropriate to reproject the data to better alignment.

Tunable nano-scale graphene-based devices in mid-infrared wavelengths composed of cylindrical resonators

NASA Astrophysics Data System (ADS)

Asgari, Somayyeh; Ghattan Kashani, Zahra; Granpayeh, Nosrat

2018-04-01

The performances of three optical devices including a refractive index sensor, a power splitter, and a 4-channel multi/demultiplexer based on graphene cylindrical resonators are proposed, analyzed, and simulated numerically by using the finite-difference time-domain method. The proposed sensor operates on the principle of the shift in resonance wavelength with a change in the refractive index of dielectric materials. The sensor sensitivity has been numerically derived. In addition, the performances of the power splitter and the multi/demultiplexer based on the variation of the resonance wavelengths of cylindrical resonator have been thoroughly investigated. The simulation results are in good agreement with the theoretical ones. Our studies demonstrate that the graphene based ultra-compact, nano-scale devices can be improved to be used as photonic integrated devices, optical switching, and logic gates.

Rolling bearing fault diagnosis based on information fusion using Dempster-Shafer evidence theory

NASA Astrophysics Data System (ADS)

Pei, Di; Yue, Jianhai; Jiao, Jing

2017-10-01

This paper presents a fault diagnosis method for rolling bearing based on information fusion. Acceleration sensors are arranged at different position to get bearing vibration data as diagnostic evidence. The Dempster-Shafer (D-S) evidence theory is used to fuse multi-sensor data to improve diagnostic accuracy. The efficiency of the proposed method is demonstrated by the high speed train transmission test bench. The results of experiment show that the proposed method in this paper improves the rolling bearing fault diagnosis accuracy compared with traditional signal analysis methods.

Arctic and Antarctic Sea-Ice Freeboard and Thickness Retrievals from CryoSat-2 and EnviSat

NASA Astrophysics Data System (ADS)

Ricker, Robert; Hendricks, Stefan; Schwegmann, Sandra; Helm, Veit; Rinne, Eero

2016-04-01

The CryoSat-2 satellite is now in the 6th year of data acquisition. With its synthetic aperture radar altimeter, CryoSat-2 achieves great improvements in the along track resolution compared to previous radar altimeter missions like ERS or Envisat. The latitudinal coverage contains major parts of the Arctic marine ice fields where previous missions left a big data gap around the North Pole and especially over the multiyear ice zone north of Greenland. With this unique data set, changes in sea-ice thickness can be investigated in the context of the rapid reduction of the Arctic sea-ice cover which has been observed during the last decades. We present the current state of the CryoSat-2 Arctic sea-ice thickness retrieval that is processed at the Alfred Wegener Institute and available via seaiceportal.de (originally: meereisportal.de). Though biases in sea-ice thickness may occur due to the interpretation of waveforms, airborne and ground-based validation measurements give confidence that the retrieval algorithm enables us to capture the actual distributions of sea-ice regimes. Nevertheless, long time series of data retrievals are essential to estimate trends in sea-ice thickness and volume. Today, more than 20 years of radar altimeter data are potentially available and capable to derive sea ice thickness. However, data originate from satellites with different sensor characteristics. Therefore, it is crucial to study the consistency between single sensors to derive long and consistent time series. We present results from the tested consistency between Antarctic freeboard measurements of the radar altimeters on-board of Envisat and CryoSat-2 for their overlap period in 2011.

A Multi-Agent Framework for Packet Routing in Wireless Sensor Networks

PubMed Central

Ye, Dayon; Zhang, Minji; Yang, Yu

2015-01-01

Wireless sensor networks (WSNs) have been widely investigated in recent years. One of the fundamental issues in WSNs is packet routing, because in many application domains, packets have to be routed from source nodes to destination nodes as soon and as energy efficiently as possible. To address this issue, a large number of routing approaches have been proposed. Although every existing routing approach has advantages, they also have some disadvantages. In this paper, a multi-agent framework is proposed that can assist existing routing approaches to improve their routing performance. This framework enables each sensor node to build a cooperative neighbour set based on past routing experience. Such cooperative neighbours, in turn, can help the sensor to effectively relay packets in the future. This framework is independent of existing routing approaches and can be used to assist many existing routing approaches. Simulation results demonstrate the good performance of this framework in terms of four metrics: average delivery latency, successful delivery ratio, number of live nodes and total sensing coverage. PMID:25928063

Combining Satellite and in Situ Data with Models to Support Climate Data Records in Ocean Biology

NASA Technical Reports Server (NTRS)

Gregg, Watson

2011-01-01

The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected by solar zenith angle requirements and obscuration from clouds and aerosols. Combined with in situ dataenhanced satellite data, the model is forced into consistency using data assimilation. This approach eliminates sampling discrepancies from satellites. Combining the reduced differences of satellite data sets using in situ data, and the removal of sampling biases using data assimilation, we generate consistent data records of ocean color. These data records can support investigations of long-term effects of climate change on ocean biology over multiple satellites, and can improve the consistency of future satellite data sets.

A Decade of High-Resolution Arctic Sea Ice Measurements from Airborne Altimetry

NASA Astrophysics Data System (ADS)

Duncan, K.; Farrell, S. L.; Connor, L. N.; Jackson, C.; Richter-Menge, J.

2017-12-01

Satellite altimeters carried on board ERS-1,-2, EnviSat, ICESat, CryoSat-2, AltiKa and Sentinel-3 have transformed our ability to map the thickness and volume of the polar sea ice cover, on seasonal and decadal time-scales. The era of polar satellite altimetry has coincided with a rapid decline of the Arctic ice cover, which has thinned, and transitioned from a predominantly multi-year to first-year ice cover. In conjunction with basin-scale satellite altimeter observations, airborne surveys of the Arctic Ocean at the end of winter are now routine. These surveys have been targeted to monitor regions of rapid change, and are designed to obtain the full snow and ice thickness distribution, across a range of ice types. Sensors routinely deployed as part of NASA's Operation IceBridge (OIB) campaigns include the Airborne Topographic Mapper (ATM) laser altimeter, the frequency-modulated continuous-wave snow radar, and the Digital Mapping System (DMS). Airborne measurements yield high-resolution data products and thus present a unique opportunity to assess the quality and characteristics of the satellite observations. We present a suite of sea ice data products that describe the snow depth and thickness of the Arctic ice cover during the last decade. Fields were derived from OIB measurements collected between 2009-2017, and from reprocessed data collected during ad-hoc sea ice campaigns prior to OIB. Our bespoke algorithms are designed to accommodate the heterogeneous sea ice surface topography, that varies at short spatial scales. We assess regional and inter-annual variability in the sea ice thickness distribution. Results are compared to satellite-derived ice thickness fields to highlight the sensitivities of satellite footprints to the tails of the thickness distribution. We also show changes in the dynamic forcing shaping the ice pack over the last eight years through an analysis of pressure-ridge sail-height distributions and surface roughness conditions. Variability is linked to the geographic location and extent of multi-year sea ice. Finally, we describe accessing our high-resolution data products at the NOAA Laboratory for Satellite Altimetry.

Automated ocean color product validation for the Southern California Bight

NASA Astrophysics Data System (ADS)

Davis, Curtiss O.; Tufillaro, Nicholas; Jones, Burt; Arnone, Robert

2012-06-01

Automated match ups allow us to maintain and improve the products of current satellite ocean color sensors (MODIS, MERIS), and new sensors (VIIRS). As part of the VIIRS mission preparation, we have created a web based automated match up tool that provides access to searchable fields for date, site, and products, and creates match-ups between satellite (MODIS, MERIS, VIIRS), and in-situ measurements (HyperPRO and SeaPRISM). The back end of the system is a 'mySQL' database, and the front end is a `php' web portal with pull down menus for searchable fields. Based on selections, graphics are generated showing match-ups and statistics, and ascii files are created for downloads for the matchup data. Examples are shown for matching the satellite data with the data from Platform Eureka SeaPRISM off L.A. Harbor in the Southern California Bight.

Comparing the Ocean Color Measurements Between MOS and SeaWiFS: A Vicarious Intercalibration Approach for MOS

NASA Technical Reports Server (NTRS)

Wang, Menghua; Franz, Bryan A.

1998-01-01

One of the primary goals of the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project is to develop methods for meaningful comparison and possible merging of data products from multiple ocean color missions. The Modular Optoelectronic Scanner (MOS) is a German instrument that was launched in the spring of 1996 on the Indian IRS-P3 satellite. With the successful launch of NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) in the summer of 1997, there are now two ocean color missions in concurrent operation and there is interest within the scientific community to compare data from these two sensors. In this paper, we describe our efforts to retrieve ocean optical properties from both SeaWiFS and MOS using consistent methods. We first briefly review the atmospheric correction, which removes more than 90% of the observed radiances in the visible, and then describe how the atmospheric correction algorithm used for the SeaWiFS data can be modified for application to other ocean color sensors. Next, since the retrieved water-leaving radiances in the visible between MOS and SeaWiFS are significantly different, we developed a vicarious intercalibration method to recalibrate the MOS spectral bands based on the optical properties of the ocean and atmosphere derived from the coincident SeaWiFS measurements. We present and discuss the MOS retrieved ocean optical properties before and after the vicarious calibration, and demonstrate the efficacy of this approach. We show that it is possible and efficient to vicariously intercalibrate sensors between one and another.

Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

PubMed

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-10-02

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

Adaptive Multi-Node Multiple Input and Multiple Output (MIMO) Transmission for Mobile Wireless Multimedia Sensor Networks

PubMed Central

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-01-01

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase. PMID:24152920

A multi-model evaluation of aerosols over South Asia: common problems and possible causes

NASA Astrophysics Data System (ADS)

Pan, X.; Chin, M.; Gautam, R.; Bian, H.; Kim, D.; Colarco, P. R.; Diehl, T. L.; Takemura, T.; Pozzoli, L.; Tsigaridis, K.; Bauer, S.; Bellouin, N.

2015-05-01

Atmospheric pollution over South Asia attracts special attention due to its effects on regional climate, water cycle and human health. These effects are potentially growing owing to rising trends of anthropogenic aerosol emissions. In this study, the spatio-temporal aerosol distributions over South Asia from seven global aerosol models are evaluated against aerosol retrievals from NASA satellite sensors and ground-based measurements for the period of 2000-2007. Overall, substantial underestimations of aerosol loading over South Asia are found systematically in most model simulations. Averaged over the entire South Asia, the annual mean aerosol optical depth (AOD) is underestimated by a range 15 to 44% across models compared to MISR (Multi-angle Imaging SpectroRadiometer), which is the lowest bound among various satellite AOD retrievals (from MISR, SeaWiFS (Sea-Viewing Wide Field-of-View Sensor), MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and Terra). In particular during the post-monsoon and wintertime periods (i.e., October-January), when agricultural waste burning and anthropogenic emissions dominate, models fail to capture AOD and aerosol absorption optical depth (AAOD) over the Indo-Gangetic Plain (IGP) compared to ground-based Aerosol Robotic Network (AERONET) sunphotometer measurements. The underestimations of aerosol loading in models generally occur in the lower troposphere (below 2 km) based on the comparisons of aerosol extinction profiles calculated by the models with those from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. Furthermore, surface concentrations of all aerosol components (sulfate, nitrate, organic aerosol (OA) and black carbon (BC)) from the models are found much lower than in situ measurements in winter. Several possible causes for these common problems of underestimating aerosols in models during the post-monsoon and wintertime periods are identified: the aerosol hygroscopic growth and formation of secondary inorganic aerosol are suppressed in the models because relative humidity (RH) is biased far too low in the boundary layer and thus foggy conditions are poorly represented in current models, the nitrate aerosol is either missing or inadequately accounted for, and emissions from agricultural waste burning and biofuel usage are too low in the emission inventories. These common problems and possible causes found in multiple models point out directions for future model improvements in this important region.

A fiber optic multi-stress monitoring system for power transformer

NASA Astrophysics Data System (ADS)

Kim, Dae-gil; Sampath, Umesh; Kim, Hyunjin; Song, Minho

2017-04-01

A fiber-optic multi-stress monitoring system which uses 4 FBG sensors and a fiber-optic mandrel acoustic emission sensor is proposed. FBG sensors and a mandrel sensor measure different types of stresses occurring in electrical power transformer, such as temperature and acoustic signals. The sensor system uses single broadband light source to address the outputs of both sensors using single fiber-optic circuitry. An athermal-packaged FBG is used to supply quasi-coherent light for the Sagnac interferometer demodulation which processes the mandrel sensor output. The proposed sensor system could simplify the optical circuit for the multi-stress measurements and enhance the cost-effectiveness of the sensor system.

NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager

NASA Technical Reports Server (NTRS)

Cavalieri, Donald J. (Editor); Crawford, John P.; Drinkwater, Mark R.; Emery, William J.; Eppler, Duane T.; Farmer, L. Dennis; Fowler, Charles W.; Goodberlet, Mark; Jentz, Robert R.; Milman, Andrew

1992-01-01

The history of the program is described along with the SSM/I sensor, including its calibration and geolocation correction procedures used by NASA, SSM/I data flow, and the NASA program to distribute polar gridded SSM/I radiances and sea ice concentrations (SIC) on CD-ROMs. Following a discussion of the NASA algorithm used to convert SSM/I radiances to SICs, results of 95 SSM/I-MSS Landsat IC comparisons for regions in both the Arctic and the Antarctic are presented. The Landsat comparisons show that the overall algorithm accuracy under winter conditions is 7 pct. on average with 4 pct. negative bias. Next, high resolution active and passive microwave image mosaics from coordinated NASA and Navy aircraft underflights over regions of the Beaufort and Chukchi seas in March 1988 were used to show that the algorithm multiyear IC accuracy is 11 pct. on average with a positive bias of 12 pct. Ice edge crossings of the Bering Sea by the NASA DC-8 aircraft were used to show that the SSM/I 15 pct. ice concentration contour corresponds best to the location of the initial bands at the ice edge. Finally, a summary of results and recommendations for improving the SIC retrievals from spaceborne radiometers are provided.

The resilient hybrid fiber sensor network with self-healing function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Shibo, E-mail: Shibo-Xu@tju.edu.cn; Liu, Tiegen; Ge, Chunfeng

This paper presents a novel resilient fiber sensor network (FSN) with multi-ring architecture, which could interconnect various kinds of fiber sensors responsible for more than one measurands. We explain how the intelligent control system provides sensors with self-healing function meanwhile sensors are working properly, besides each fiber in FSN is under real-time monitoring. We explain the software process and emergency mechanism to respond failures or other circumstances. To improve the efficiency in the use of limited spectrum resources in some situations, we have two different structures to distribute the light sources rationally. Then, we propose a hybrid sensor working inmore » FSN which is a combination of a distributed sensor and a FBG (Fiber Bragg Grating) array fused in a common fiber sensing temperature and vibrations simultaneously with neglectable crosstalk to each other. By making a failure to a working fiber in experiment, the feasibility and effectiveness of the network with a hybrid sensor has been demonstrated, hybrid sensors could not only work as designed but also survive from destructive failures with the help of resilient network and smart and quick self-healing actions. The network has improved the viability of the fiber sensors and diversity of measurands.« less

A summary of the test procedures and operational details of a Delaware River and an ocean dumping pollution monitoring experiment conducted 28 August 1975

NASA Technical Reports Server (NTRS)

Hypes, W. D.; Ohlhorst, C. W.

1977-01-01

Two remote sensor evaluation experiments are discussed. One experiment was conducted at the DuPont acid-dump site off the Delaware coast. The second was conducted at an organic waste outfall in the Delaware River. The operational objective of obtaining simultaneous sea truth sampling with remote sensors overpasses was met. Descriptions of the test sites, sensors, sensor platforms, flight lines, sea truth data collected, and operational chronology are presented.

Research on multi-source image fusion technology in haze environment

NASA Astrophysics Data System (ADS)

Ma, GuoDong; Piao, Yan; Li, Bing

2017-11-01

In the haze environment, the visible image collected by a single sensor can express the details of the shape, color and texture of the target very well, but because of the haze, the sharpness is low and some of the target subjects are lost; Because of the expression of thermal radiation and strong penetration ability, infrared image collected by a single sensor can clearly express the target subject, but it will lose detail information. Therefore, the multi-source image fusion method is proposed to exploit their respective advantages. Firstly, the improved Dark Channel Prior algorithm is used to preprocess the visible haze image. Secondly, the improved SURF algorithm is used to register the infrared image and the haze-free visible image. Finally, the weighted fusion algorithm based on information complementary is used to fuse the image. Experiments show that the proposed method can improve the clarity of the visible target and highlight the occluded infrared target for target recognition.

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments.

PubMed

Lee, ZhongPing; Carder, Kendall; Arnone, Robert; He, MingXia

2007-12-20

About 30 years ago, NASA launched the first ocean-color observing satellite:the Coastal Zone Color Scanner. CZCS had 5 bands in the visible-infrared domain with anobjective to detect changes of phytoplankton (measured by concentration of chlorophyll) inthe oceans. Twenty years later, for the same objective but with advanced technology, theSea-viewing Wide Field-of-view Sensor (SeaWiFS, 7 bands), the Moderate-ResolutionImaging Spectrometer (MODIS, 8 bands), and the Medium Resolution ImagingSpectrometer (MERIS, 12 bands) were launched. The selection of the number of bands andtheir positions was based on experimental and theoretical results achieved before thedesign of these satellite sensors. Recently, Lee and Carder (2002) demonstrated that foradequate derivation of major properties (phytoplankton biomass, colored dissolved organicmatter, suspended sediments, and bottom properties) in both oceanic and coastalenvironments from observation of water color, it is better for a sensor to have ~15 bands inthe 400 - 800 nm range. In that study, however, it did not provide detailed analysesregarding the spectral locations of the 15 bands. Here, from nearly 400 hyperspectral (~ 3-nm resolution) measurements of remote-sensing reflectance (a measure of water color)taken in both coastal and oceanic waters covering both optically deep and optically shallowwaters, first- and second-order derivatives were calculated after interpolating themeasurements to 1-nm resolution. From these derivatives, the frequency of zero values foreach wavelength was accounted for, and the distribution spectrum of such frequencies wasobtained. Furthermore, the wavelengths that have the highest appearance of zeros wereidentified. Because these spectral locations indicate extrema (a local maximum orminimum) of the reflectance spectrum or inflections of the spectral curvature, placing the bands of a sensor at these wavelengths maximizes the potential of capturing (and then restoring) the spectral curve, and thus maximizes the potential of accurately deriving properties of the water column and/or bottom of various aquatic environments with a multi-band sensor.

A passive optical fibre hydrophone array utilising fibre Bragg grating sensors

NASA Astrophysics Data System (ADS)

Karas, Andrew R.; Papageorgiou, Anthony W.; Cook, Peter R.; Arkwright, John W.

2018-02-01

Many current high performance hydrophones use piezo-electric technology to measure sound pressure in water. These hydrophones are sensitive enough to detect any sound above the lowest ambient ocean acoustic noise, however cost of manufacture, weight and storage volume of the array as well as deployment and maintenance costs can limit their largescale application. Piezo-electric systems also have issues with electro-magnetic interference and the signature of the electrical cabling required in a large array. A fibre optic hydrophone array has advantages over the piezo-electric technology in these areas. This paper presents the operating principle of a passive optical fibre hydrophone array utilising Fibre Bragg Gratings (FBGs). The multiple FBG sensors are interrogated using a single solid state spectrometer which further reduces the cost of the deployed system. A noise equivalent power (NEP) comparison of the developed FBG hydrophone versus an existing piezo-electric hydrophone is presented as well as a comparison to the lowest ambient ocean acoustic noise (sea state zero). This research provides an important first step towards a cost effective multi sensor hydrophone array using FBGs.

Late-summer sea ice segmentation with multi-polarisation SAR features in C and X band

NASA Astrophysics Data System (ADS)

Fors, Ane S.; Brekke, Camilla; Doulgeris, Anthony P.; Eltoft, Torbjørn; Renner, Angelika H. H.; Gerland, Sebastian

2016-02-01

In this study, we investigate the potential of sea ice segmentation by C- and X-band multi-polarisation synthetic aperture radar (SAR) features during late summer. Five high-resolution satellite SAR scenes were recorded in the Fram Strait covering iceberg-fast first-year and old sea ice during a week with air temperatures varying around 0 °C. Sea ice thickness, surface roughness and aerial photographs were collected during a helicopter flight at the site. Six polarimetric SAR features were extracted for each of the scenes. The ability of the individual SAR features to discriminate between sea ice types and their temporal consistency were examined. All SAR features were found to add value to sea ice type discrimination. Relative kurtosis, geometric brightness, cross-polarisation ratio and co-polarisation correlation angle were found to be temporally consistent in the investigated period, while co-polarisation ratio and co-polarisation correlation magnitude were found to be temporally inconsistent. An automatic feature-based segmentation algorithm was tested both for a full SAR feature set and for a reduced SAR feature set limited to temporally consistent features. In C band, the algorithm produced a good late-summer sea ice segmentation, separating the scenes into segments that could be associated with different sea ice types in the next step. The X-band performance was slightly poorer. Excluding temporally inconsistent SAR features improved the segmentation in one of the X-band scenes.

NASA Sea Ice and Snow Validation Program for the DMSP SSM/I: NASA DC-8 flight report

NASA Technical Reports Server (NTRS)

Cavalieri, D. J.

1988-01-01

In June 1987 a new microwave sensor called the Special Sensor Microwave Imager (SSM/I) was launched as part of the Defense Meteorological Satellite Program (DMSP). In recognition of the importance of this sensor to the polar research community, NASA developed a program to acquire the data, to convert the data into sea ice parameters, and finally to validate and archive both the SSM/I radiances and the derived sea ice parameters. Central to NASA's sea ice validation program was a series of SSM/I aircraft underflights with the NASA DC-8 airborne Laboratory. The mission (the Arctic '88 Sea Ice Mission) was completed in March 1988. This report summarizes the mission and includes a summary of aircraft instrumentation, coordination with participating Navy aircraft, flight objectives, flight plans, data collected, SSM/I orbits for each day during the mission, and lists several piggyback experiments supported during this mission.

Toward RADSCAT measurements over the sea and their interpretation

NASA Technical Reports Server (NTRS)

Claassen, J. P.; Fung, A. K.; Wu, S. T.; Chan, H. L.

1973-01-01

Investigations into several areas which are essential to the execution and interpretation of suborbital observations by composite radiometer - scatterometer sensor (RADSCAT) are reported. Experiments and theory were developed to demonstrate the remote anemometric capability of the sensor over the sea through various weather conditions. It is shown that weather situations found in extra tropical cyclones are useful for demonstrating the all weather capability of the composite sensor. The large scale fluctuations of the wind over the sea dictate the observational coverage required to correlate measurements with the mean surface wind speed. Various theoretical investigations were performed to establish a premise for the joint interpretation of the experiment data. The effects of clouds and rains on downward radiometric observations over the sea were computed. A method of predicting atmospheric attenuation from joint observations is developed. In other theoretical efforts, the emission and scattering characteristics of the sea were derived. Composite surface theories with coherent and noncoherent assumptions were employed.

Barrow real-time sea ice mass balance data: ingestion, processing, dissemination and archival of multi-sensor data

NASA Astrophysics Data System (ADS)

Grimes, J.; Mahoney, A. R.; Heinrichs, T. A.; Eicken, H.

2012-12-01

Sensor data can be highly variable in nature and also varied depending on the physical quantity being observed, sensor hardware and sampling parameters. The sea ice mass balance site (MBS) operated in Barrow by the University of Alaska Fairbanks (http://seaice.alaska.edu/gi/observatories/barrow_sealevel) is a multisensor platform consisting of a thermistor string, air and water temperature sensors, acoustic altimeters above and below the ice and a humidity sensor. Each sensor has a unique specification and configuration. The data from multiple sensors are combined to generate sea ice data products. For example, ice thickness is calculated from the positions of the upper and lower ice surfaces, which are determined using data from downward-looking and upward-looking acoustic altimeters above and below the ice, respectively. As a data clearinghouse, the Geographic Information Network of Alaska (GINA) processes real time data from many sources, including the Barrow MBS. Doing so requires a system that is easy to use, yet also offers the flexibility to handle data from multisensor observing platforms. In the case of the Barrow MBS, the metadata system needs to accommodate the addition of new and retirement of old sensors from year to year as well as instrument configuration changes caused by, for example, spring melt or inquisitive polar bears. We also require ease of use for both administrators and end users. Here we present the data and processing steps of using sensor data system powered by the NoSQL storage engine, MongoDB. The system has been developed to ingest, process, disseminate and archive data from the Barrow MBS. Storing sensor data in a generalized format, from many different sources, is a challenging task, especially for traditional SQL databases with a set schema. MongoDB is a NoSQL (not only SQL) database that does not require a fixed schema. There are several advantages using this model over the traditional relational database management system (RDBMS) model databases. The lack of a required schema allows flexibility in how the data can be ingested into the database. For example, MongoDB imposes no restrictions on field names. For researchers using the system, this means that the name they have chosen for the sensor is carried through the database, any processing, and to the final output helping to preserve data integrity. Also, MongoDB allows the data to be pushed to it dynamically meaning that field attributes can be defined at the point of ingestion. This allows any sensor data to be ingested as a document and for this functionality to be transferred to the user interface, allowing greater adaptability to different use-case scenarios. In presenting the MondoDB data system being developed for the Barrow MBS, we demonstrate the versatility of this approach and its suitability as the foundation of a Barrow node of the Arctic Observing Network. Authors Jason Grimes - Geographic Information Network of Alaska - jason@gina.alaska.edu Andy Mahony - Geophysical Institute - mahoney@gi.alaska.edu Hajo Eiken - Geophysical Institute - Hajo.Eicken@gi.alaska.edu Tom Heinrichs - Geographic Information Network of Alaska - Tom.Heinrichs@alaska.edu

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Petrenko, Maksym; Ichoku, Charles

2012-01-01

Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

Sensor fusion for antipersonnel landmine detection: a case study

NASA Astrophysics Data System (ADS)

den Breejen, Eric; Schutte, Klamer; Cremer, Frank

1999-08-01

In this paper the multi sensor fusion results obtained within the European research project GEODE are presented. The layout of the test lane and the individual sensors used are described. The implementation of the SCOOP algorithm improves the ROC curves, as the false alarm surface and the number of false alarms both are taken into account. The confidence grids, as produced by the sensor manufacturers, of the sensors are used as input for the different sensor fusion methods implemented. The multisensor fusion methods implemented are Bayes, Dempster-Shafer, fuzzy probabilities and rules. The mapping of the confidence grids to the input parameters for fusion methods is an important step. Due to limited amount of the available data the entire test lane is used for training and evaluation. All four sensor fusion methods provide better detection results than the individual sensors.

Principles and practical implementation for high resolution multi-sensor QPE

NASA Astrophysics Data System (ADS)

Chandra, C. V.; Lim, S.; Cifelli, R.

2011-12-01

The multi-sensor Quantitative Precipitation Estimation (MPE) is a principle and a practical concept and is becoming a well-known term in the scientific circles of hydrology and atmospheric science. The main challenge in QPE is that precipitation is a highly variable quantity with extensive spatial and temporal variability at multiple scales. There are MPE products produced from satellites, radars, models and ground sensors. There are MPE products at global scale (Heinemann et al. 2002), continental scale (Seo et al. 2010; Zhang et al. 2011) and regional scale (Kitzmiller et al. 2011). Lots of the MPE products are used to alleviate the problems of one type of sensor by another. Some multi-sensor products are used to move across scales. This paper looks at a comprehensive view of the "concept of multi sensor precipitation estimate", from different perspectives. This paper delineates the MPE problem into three categories namely, a) Scale based MPE, b) MPE for accuracy enhancement and coverage and c) Integrative across scales. For example, by introducing dual polarization radar data to the MPE system, QPE can be improved significantly. In last decade, dual polarization radars are becoming an important tool for QPE in operational networks. Dual polarization radars offer an advantage to interpret more accurate physical models by providing information of the size, shape, phase and orientation of hydrometers (Bringi and Chandrasekar 2001). In addition, these systems have the ability to provide measurements that are immune to absolute radar calibration and partial beam blockage as well as help in data quality enhancement. By integrating these characteristics of dual polarization radar, QPE performance can be improved in comparison of single polarization radar based QPE (Cifelli and Chandrasekar 2010). Dual-polarization techniques have been applied to S and C band radar systems for several decades and higher frequency system such as X band are now widely available to the radar community. One solution to the dilemma of precipitation variability across scales can be to supplement existing long-range radar networks with short-range higher frequency systems (X band). The smaller X band systems provide more portability and higher data resolution, and networks of these systems may be a cost-effective option for improved rainfall estimation for radar networks with large separation distances (McLaughlin et al. 2009). This paper will describe the principles of the MPE concept and implementation issues of within the context of the classification described above.

A complete tomography of the Earth's interior with floating seismometers in the oceans: the EarthScope-Oceans

NASA Astrophysics Data System (ADS)

Chen, Y. J.; Nolet, G.

2016-12-01

While the tomography techniques of imaging the earth's interior have been improved significantly over the past three decades the resolution of the resulting 3D images of the earth's interior, particularly the lower mantle, has been severely limited by the lack of seismic stations in the oceans which cover the 2/3 of the earth's surface. But this is going to be changed by the recently developed floating hydrophones called "Mermaids" which, freely floating under the sea surface, can operate as seismometers (see abstract by Nolet et al. in session DI010). These `Mermaids' have recorded (1) teleseismic waves, crucial to provide resolution for tomographic images of the deep mantle beneath oceanic areas, as well as (2) swarms of earthquakes too small to be observed on land, indicative of tectonic motions on oceanic ridges. Transmission is in quasi-real time by satellite (Iridium). A new version of the Mermaid, of much larger capacity, with a lifetime of five to six years is available for deployment. SUSTC in Shenzhen, China, in close collaboration with Geoazur (France), will launch the first stage of a large scale, global network of floating seismometers in the oceans named EarthScope-Oceans in 2017 by setting afloat 50 Mermaids in the Indian Ocean. Japan and other European nations may join the effort, which should reach 500 sensors by 2019 covering the entire world oceans. After that, the robots will be equipped with sophisticated software currently under development, which adds the capacity to juggle up to eight sensors and that has a reprogramming ability even during missions. We then expect the network to become multi-disciplinary and be able to host instruments not only for global seismology but also for biologists, oceanographers, geochemists, meteorologists and others. This new monitoring network will greatly improve our knowledge of acoustic noise pollution, of cetacean populations and their interaction with noise and meteorological conditions in all of the oceans by providing large and continuous data coverage. It will transform the discipline of seismic tomography at sea and improve our understanding of geodynamical processes operating in the deep mantle of the Earth by filling the data gap that currently exists in the oceanic domain.

Concepts for the Design of a Diagnostic Device to Detect Malignancies in Human Tissues Final Report CRADA No. TSB-2023-00

DOE Office of Scientific and Technical Information (OSTI.GOV)

DaSilva, L.; Marion, J.; Chase, C.

BioLuminate, Inc. planned to develop, produce and market a revolutionary diagnostic device for early breast cancer diagnosis. The device was originally invented by NASA; and exclusively licensed to BioLuminate for commercialization. At the time of the CRADA, eighty-five percent (85%) of all biopsies in the United States were found negative each year. The number of biopsies cost the health care system $23 billio n annually. A multi-sensor probe would allow surgeons to improve breast cancer scre ening and significantly reduce the number of biopsies. BioLuminate was developing an in-vivo system for the detection of cancer using a multi-sensor needle/probe. Themore » first system would be developed for the detection of breast cancer. LLNL, in collaboration with BioLuminate worked toward a detailed concept specification for the prototype multi-sensor needle/probe suitable for breast cancer analysis. BioLuminate in collaboration with LLNL, worked to develop a new version of the needle probe that would be the same size as needles commonly used to draw blood.« less

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method.

PubMed

Deng, Xinyang; Jiang, Wen

2017-09-12

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model.

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method

PubMed Central

Deng, Xinyang

2017-01-01

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model. PMID:28895905

Platinum decorated carbon nanotubes for highly sensitive amperometric glucose sensing

NASA Astrophysics Data System (ADS)

Xie, Jining; Wang, Shouyan; Aryasomayajula, L.; Varadan, V. K.

2007-02-01

Fine platinum nanoparticles (1-5 nm in diameter) were deposited on functionalized multi-walled carbon nanotubes (MWNTs) through a decoration technique. A novel type of enzymatic Pt/MWNTs paste-based mediated glucose sensor was fabricated. Electrochemical measurements revealed a significantly improved sensitivity (around 52.7 µA mM-1 cm-2) for glucose sensing without using any picoampere booster or Faraday cage. In addition, the calibration curve exhibited a good linearity in the range of 1-28 mM of glucose concentration. Transmission electron microscopy (TEM) and x-ray photoelectron spectroscopy (XPS) were performed to investigate the nanoscale structure and the chemical bonding information of the Pt/MWNTs paste-based sensing material, respectively. The improved sensitivity of this novel glucose sensor could be ascribed to its higher electroactive surface area, enhanced electron transfer, efficient enzyme immobilization, unique interaction in nanoscale and a synergistic effect on the current signal from possible multi-redox reactions.

Time-frequency analyses of tide-gauge sensor data.

PubMed

Erol, Serdar

2011-01-01

The real world phenomena being observed by sensors are generally non-stationary in nature. The classical linear techniques for analysis and modeling natural time-series observations are inefficient and should be replaced by non-linear techniques of whose theoretical aspects and performances are varied. In this manner adopting the most appropriate technique and strategy is essential in evaluating sensors' data. In this study, two different time-series analysis approaches, namely least squares spectral analysis (LSSA) and wavelet analysis (continuous wavelet transform, cross wavelet transform and wavelet coherence algorithms as extensions of wavelet analysis), are applied to sea-level observations recorded by tide-gauge sensors, and the advantages and drawbacks of these methods are reviewed. The analyses were carried out using sea-level observations recorded at the Antalya-II and Erdek tide-gauge stations of the Turkish National Sea-Level Monitoring System. In the analyses, the useful information hidden in the noisy signals was detected, and the common features between the two sea-level time series were clarified. The tide-gauge records have data gaps in time because of issues such as instrumental shortcomings and power outages. Concerning the difficulties of the time-frequency analysis of data with voids, the sea-level observations were preprocessed, and the missing parts were predicted using the neural network method prior to the analysis. In conclusion the merits and limitations of the techniques in evaluating non-stationary observations by means of tide-gauge sensors records were documented and an analysis strategy for the sequential sensors observations was presented.

Enhancement of NH3 Gas Sensitivity at Room Temperature by Carbon Nanotube-Based Sensor Coated with Co Nanoparticles

PubMed Central

Nguyen, Lich Quang; Phan, Pho Quoc; Duong, Huyen Ngoc; Nguyen, Chien Duc; Nguyen, Lam Huu

2013-01-01

Multi-walled carbon nanotube (MWCNT) film has been fabricated onto Pt-patterned alumina substrates using the chemical vapor deposition method for NH3 gas sensing applications. The MWCNT-based sensor is sensitive to NH3 gas at room temperature. Nanoclusters of Co catalysts have been sputtered on the surface of the MWCNT film to enhance gas sensitivity with respect to unfunctionalized CNT films. The gas sensitivity of Co-functionalized MWCNT-based gas sensors is thus significantly improved. The sensor exhibits good repeatability and high selectivity towards NH3, compared with alcohol and LPG. PMID:23364198

Development of Super-Ensemble techniques for ocean analyses: the Mediterranean Sea case

NASA Astrophysics Data System (ADS)

Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Korres, Gerasimos; Drillet, Yann

2017-04-01

Short-term ocean analyses for Sea Surface Temperature SST in the Mediterranean Sea can be improved by a statistical post-processing technique, called super-ensemble. This technique consists in a multi-linear regression algorithm applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset, a collection of different operational forecasting analyses together with ad-hoc simulations produced by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is capable to prevent overfitting problems, even if best performances are achieved when we add correlation to the super-ensemble structure using a simple spatial filter applied after the linear regression. Our outcomes show that super-ensemble performances depend on the selection of an unbiased operator and the length of the learning period, but the quality of the generating MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. Lower RMSE analysis estimates result from the following choices: 15 days training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.

Sperm whale assessment in the Western Ionian Sea using acoustic data from deep sea observatories

NASA Astrophysics Data System (ADS)

Caruso, Francesco; Bellia, Giorgio; Beranzoli, Laura; De Domenico, Emilio; Larosa, Giuseppina; Marinaro, Giuditta; Papale, Elena; Pavan, Gianni; Pellegrino, Carmelo; Pulvirenti, Sara; Riccobene, Giorgio; Scandura, Danila; Sciacca, Virginia; Viola, Salvatore

2015-04-01

The Italian National Institute of Nuclear Physics (INFN) operates two deep sea infrastructures: Capo Passero, Western Ionian Sea 3,600 meters of depth, and Catania Wester Ionian Sea 2,100 m depth. At the two sites, several research observatories have been run: OnDE, NEMO-SN1, SMO, KM3NeT-Italia most of them jointly operated between INFN and INGV. In all these observatories, passive acoustic sensors (hydrophones) have been installed. Passive Acoustics Monitoring (PAM) is nowadays the main tool of the bioacoustics to study marine mammals. In particular, receiving the sounds emitted by cetaceans from a multi-hydrophones array installed in a cabled seafloor observatory, a research about the ecological dynamics of the species may be performed. Data acquired with the hydrophones installed aboard the OnDE, SMO and KM3NeT-Italia observatories will be reported. Thanks to acquired data, the acoustic presence of the sperm whales was assessed and studied for several years (2005:2013). An "ad hoc" algorithm was also developed to allow the automatic identification of the "clicks" emitted by the sperm whales and measure the size of detected animals. According to the results obtained, the sperm whale population in the area is well-distributed in size, sex and sexual maturity. Although specimens more than 14 meters of length (old males) seem to be absent.

Controls on Arctic sea ice from first-year and multi-year survival rates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunke, Jes

2009-01-01

The recent decrease in Arctic sea ice cover has transpired with a significant loss of multi year ice. The transition to an Arctic that is populated by thinner first year sea ice has important implications for future trends in area and volume. Here we develop a reduced model for Arctic sea ice with which we investigate how the survivability of first year and multi year ice control the mean state, variability, and trends in ice area and volume.

Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil.

PubMed

Garfì, Marianna; Ferrer-Martí, Laia; Bonoli, Alessandra; Tondelli, Simona

2011-03-01

Multi-criteria analysis (MCA) is a family of decision-making tools that can be used in strategic environmental assessment (SEA) procedures to ensure that environmental, social and economic aspects are integrated into the design of human development strategies and planning, in order to increase the contribution of the environment and natural resources to poverty reduction. The aim of this paper is to highlight the contribution of a particular multi-criteria technique, the analytic hierarchy process (AHP), in two stages of the SEA procedure applied to water programmes in developing countries: the comparison of alternatives and monitoring. This proposal was validated through its application to a case study in Brazilian semi-arid region. The objective was to select and subsequently monitor the most appropriate programme for safe water availability. On the basis of the SEA results, a project was identified and implemented with successful results. In terms of comparisons of alternatives, AHP meets the requirements of human development programme assessment, including the importance of simplicity, a multidisciplinary and flexible approach, and a focus on the beneficiaries' concerns. With respect to monitoring, the study shows that AHP contributes to SEA by identifying the most appropriate indicators, in order to control the impacts of a project. Copyright © 2010 Elsevier Ltd. All rights reserved.

Validation of a novel Multi-Gas sensor for volcanic HCl alongside H2S and SO2 at Mt. Etna

NASA Astrophysics Data System (ADS)

Roberts, T. J.; Lurton, T.; Giudice, G.; Liuzzo, M.; Aiuppa, A.; Coltelli, M.; Vignelles, D.; Salerno, G.; Couté, B.; Chartier, M.; Baron, R.; Saffell, J. R.; Scaillet, B.

2017-05-01

Volcanic gas emission measurements inform predictions of hazard and atmospheric impacts. For these measurements, Multi-Gas sensors provide low-cost in situ monitoring of gas composition but to date have lacked the ability to detect halogens. Here, two Multi-Gas instruments characterized passive outgassing emissions from Mt. Etna's (Italy) three summit craters, Voragine (VOR), North-east Crater (NEC) and Bocca Nuova (BN) on 2 October 2013. Signal processing (Sensor Response Model, SRM) approaches are used to analyse H2S/SO2 and HCl/SO2 ratios. A new ability to monitor volcanic HCl using miniature electrochemical sensors is here demonstrated. A "direct-exposure" Multi-Gas instrument contained SO2, H2S and HCl sensors, whose sensitivities, cross-sensitivities and response times were characterized by laboratory calibration. SRM analysis of the field data yields H2S/SO2 and HCl/SO2 molar ratios, finding H2S/SO2 = 0.02 (0.01-0.03), with distinct HCl/SO2 for the VOR, NEC and BN crater emissions of 0.41 (0.38-0.43), 0.58 (0.54-0.60) and 0.20 (0.17-0.33). A second Multi-Gas instrument provided CO2/SO2 and H2O/SO2 and enabled cross-comparison of SO2. The Multi-Gas-measured SO2-HCl-H2S-CO2-H2O compositions provide insights into volcanic outgassing. H2S/SO2 ratios indicate gas equilibration at slightly below magmatic temperatures, assuming that the magmatic redox state is preserved. Low SO2/HCl alongside low CO2/SO2 indicates a partially outgassed magma source. We highlight the potential for low-cost HCl sensing of H2S-poor HCl-rich volcanic emissions elsewhere. Further tests are needed for H2S-rich plumes and for long-term monitoring. Our study brings two new advances to volcano hazard monitoring: real-time in situ measurement of HCl and improved Multi-Gas SRM measurements of gas ratios.

Progress Report on the GROWTH (GNSS Reflectometry for Ocean Waves, Tides, and Height) Research Project

NASA Astrophysics Data System (ADS)

Kitazawa, Y.; Ichikawa, K.; Akiyama, H.; Ebinuma, T.; Isoguchi, O.; Kimura, N.; Konda, M.; Kouguchi, N.; Tamura, H.; Tomita, H.; Yoshikawa, Y.; Waseda, T.

2016-12-01

Global Navigation Satellite Systems (GNSS), such as GPS is a system of satellites that provide autonomous geo-spatial positioning with global coverage. It allows small electronic receivers to determine their location to high precision using radio signals transmitted from satellites, GNSS reflectometry (GNSS-R) involves making measurements from the reflections from the Earth of navigation signals from GNSS satellites. Reflected signals from sea surface are considered that those are useful to observe sea state and sea surface height. We have started a research program for GNSS-R applications on oceanographic observations under the contract with MEXT (Ministry of Education Culture, Sports, Science and Technology, JAPAN) and launched a Japanese research consortium, GROWTH (GNSS Reflectometry for Ocean Waves, Tides, and Height). It is aiming to evaluate the capabilities of GNSS-R observations for oceanographic phenomena with different time scales, such as ocean waves (1/10 to tens of seconds), tides (one or half days), and sea surface dynamic height (a few days to years). In situ observations of ocean wave spectrum, wind speed vertical profile, and sea surface height will be quantitatively compared with equivalent estimates from simultaneous GNSS-R measurements. The GROWTH project will utilize different types of observation platforms; marine observation towers (about 20 m height), multi-copters (about 100 to 150 m height), and much higher-altitude CYGNSS data. Cross-platform data, together with in situ oceanographic observations, will be compared after adequate temporal averaging that accounts differences of the footprint sizes and temporal and spatial scales of oceanographic phenomena. This paper will provide overview of the GROWTH project, preliminary test results, obtained by the multi-sensor platform at observation towers, suggest actual footprint sizes and identification of swell. Preparation status of a ground station which will be supplied to receive CYGNSS data at Japan, is also reported. Compatibility tests to CYGNSS data and refurbishment of the ground station were completed.

Multi-objective spatial tools to inform maritime spatial planning in the Adriatic Sea.

PubMed

Depellegrin, Daniel; Menegon, Stefano; Farella, Giulio; Ghezzo, Michol; Gissi, Elena; Sarretta, Alessandro; Venier, Chiara; Barbanti, Andrea

2017-12-31

This research presents a set of multi-objective spatial tools for sea planning and environmental management in the Adriatic Sea Basin. The tools address four objectives: 1) assessment of cumulative impacts from anthropogenic sea uses on environmental components of marine areas; 2) analysis of sea use conflicts; 3) 3-D hydrodynamic modelling of nutrient dispersion (nitrogen and phosphorus) from riverine sources in the Adriatic Sea Basin and 4) marine ecosystem services capacity assessment from seabed habitats based on an ES matrix approach. Geospatial modelling results were illustrated, analysed and compared on country level and for three biogeographic subdivisions, Northern-Central-Southern Adriatic Sea. The paper discusses model results for their spatial implications, relevance for sea planning, limitations and concludes with an outlook towards the need for more integrated, multi-functional tools development for sea planning. Copyright © 2017. Published by Elsevier B.V.

Integrated Multidisciplinary Fault Observation System in the western part of the main Marmara Fault in the frame of an EU-FP7 project, titled as MARSITE

NASA Astrophysics Data System (ADS)

Ozel, Oguz; Guralp, Cansun; Tunc, Suleyman; Yalcinkaya, Esref; Meral Ozel, Nurcan

2015-04-01

The main objective of this study is to install a multi-parameter borehole system and surface array consisting of eight broadband sensors as close to the main Marmara Fault (MMF) in the western Marmara Sea as possible, and measure continuously the evolution of the state of the fault zone surrounding the MMF and to detect any anomaly or change which may occur before earthquakes by making use of the data from these arrays. The multi-parameter borehole system is composed of very wide dynamic range and stable borehole (VBB) broad band seismic sensor, and incorporate 3-D strain meter, tilt meter, and temperature and local hydrostatic pressure measuring devices. All these sensors are installed in 146m-deep borehole. All the sensor outputs are digitized; total of 11*24 bit-channels and 6*20 bit-channels. Real-time data transmission to the main server of the Marsite Project at Kandilli Observatory in Istanbul is accomplished. The multi-parameter borehole seismic station uses the latest update technologies and design ideas to record "Earth tides" signals to the smallest magnitude -3 events, as the innovative part of the Marsite Project. Bringing face to face the seismograms of microearthquakes recorded by borehole and surface instruments portrays quite different contents. The shorter recording duration and nearly flat frequency spectrum up to the Nyquist frequencies of borehole records are faced with longer recording duration and rapid decay of spectral amplitudes at higher frequencies of a surface seismogram. The main causative of the observed differences are near surface geology effects that mask most of the source related information the seismograms include, and that give rise to scattering, generating longer duration seismograms. In view of these circumstances, studies on microearthquakes employing surface seismograms may bring on misleading results. Particularly, the works on earthquake physics and nucleation process of earthquakes requires elaborate analysis of tiny events. It is obvious from the studies on the nucleation process of the 1999 earthquake that tens of minutes before the major rupture initiate noteworthy microearthquake activity happened. The starting point of the 1999 rupture was a site of swarm activity noticed a few decades prior the main shock. Nowadays, analogous case is probable in western Marmara Sea region, prone to a major event in near future where the seismic activity is prevailing along the impending rupture zone. Having deployed a borehole system at the eastern end of the Ganos fault zone will yield invaluable data to closely inspect and monitor the last stages of the preparation stage of major rupture.

Canadian Arctic sea ice reconstructed from bromine in the Greenland NEEM ice core.

PubMed

Spolaor, Andrea; Vallelonga, Paul; Turetta, Clara; Maffezzoli, Niccolò; Cozzi, Giulio; Gabrieli, Jacopo; Barbante, Carlo; Goto-Azuma, Kumiko; Saiz-Lopez, Alfonso; Cuevas, Carlos A; Dahl-Jensen, Dorthe

2016-09-21

Reconstructing the past variability of Arctic sea ice provides an essential context for recent multi-year sea ice decline, although few quantitative reconstructions cover the Holocene period prior to the earliest historical records 1,200 years ago. Photochemical recycling of bromine is observed over first-year, or seasonal, sea ice in so-called "bromine explosions" and we employ a 1-D chemistry transport model to quantify processes of bromine enrichment over first-year sea ice and depositional transport over multi-year sea ice and land ice. We report bromine enrichment in the Northwest Greenland Eemian NEEM ice core since the end of the Eemian interglacial 120,000 years ago, finding the maximum extension of first-year sea ice occurred approximately 9,000 years ago during the Holocene climate optimum, when Greenland temperatures were 2 to 3 °C above present values. First-year sea ice extent was lowest during the glacial stadials suggesting complete coverage of the Arctic Ocean by multi-year sea ice. These findings demonstrate a clear relationship between temperature and first-year sea ice extent in the Arctic and suggest multi-year sea ice will continue to decline as polar amplification drives Arctic temperatures beyond the 2 °C global average warming target of the recent COP21 Paris climate agreement.

Utilizing a suite of satellite missions to address poorly constrained hydrological fluxes

NASA Astrophysics Data System (ADS)

Singh, A.; Behrangi, A.; Fisher, J.; Reager, J. T., II; Gardner, A. S.

2017-12-01

The amount of water stored in a given region (total water storage) changes in response to changes in the hydrologic balance (inputs minus outputs). Closing this balance is exceedingly difficult due to the sparsity of field observation, large uncertainties in satellite derived estimates and model limitation. Different regions have distinct reliability on different hydrological parameters. For example, at a higher latitude precipitation is more uncertain than evapotranspiration (ET) while at lower/middle latitude the opposite is true. This study explores alternative estimates of regional hydrological fluxes by integrating the total water storage estimated by the GRACE gravity fields, and improved estimates lake storage variation by Landsat based land-water classification and satellite altimetry based water height measurements. In particular, an alternative ET estimate is generated for the Aral Sea region by integrating multi-sensor remote sensing data. In an endorheic lake like the Aral Sea, its volumetric variations are predominately governed by changes in inflow, evaporation from the water body and precipitation on the lake. The Aral Sea water volume is estimated at a monthly time step by the combination of Landsat land-water classification and ocean radar altimetry (Jason 1 and Jason 2) observations using truncated pyramid method. Considering gauge based river runoff as a true observation and given the fact that there is less variability between multiple precipitation datasets (TRMM, GPCP, GPCC, and ERA), ET can be considered as a most uncertain parameter in this region. The estimated lake volume acts as a controlling factor to estimate ET as the residual of the changes in TWS minus inflow plus precipitation. The estimated ET is compared with the MODIS-based evaporation observations.

Utilizing a suite of satellite missions to address poorly constrained hydrological fluxes

NASA Astrophysics Data System (ADS)

Shukla, S.; Hobbins, M.; McEvoy, D.; Husak, G. J.; Dewes, C.; McNally, A.; Huntington, J. L.; Funk, C. C.; Verdin, J. P.

2016-12-01

The amount of water stored in a given region (total water storage) changes in response to changes in the hydrologic balance (inputs minus outputs). Closing this balance is exceedingly difficult due to the sparsity of field observation, large uncertainties in satellite derived estimates and model limitation. Different regions have distinct reliability on different hydrological parameters. For example, at a higher latitude precipitation is more uncertain than evapotranspiration (ET) while at lower/middle latitude the opposite is true. This study explores alternative estimates of regional hydrological fluxes by integrating the total water storage estimated by the GRACE gravity fields, and improved estimates lake storage variation by Landsat based land-water classification and satellite altimetry based water height measurements. In particular, an alternative ET estimate is generated for the Aral Sea region by integrating multi-sensor remote sensing data. In an endorheic lake like the Aral Sea, its volumetric variations are predominately governed by changes in inflow, evaporation from the water body and precipitation on the lake. The Aral Sea water volume is estimated at a monthly time step by the combination of Landsat land-water classification and ocean radar altimetry (Jason 1 and Jason 2) observations using truncated pyramid method. Considering gauge based river runoff as a true observation and given the fact that there is less variability between multiple precipitation datasets (TRMM, GPCP, GPCC, and ERA), ET can be considered as a most uncertain parameter in this region. The estimated lake volume acts as a controlling factor to estimate ET as the residual of the changes in TWS minus inflow plus precipitation. The estimated ET is compared with the MODIS-based evaporation observations.

Iterative matrix algorithm for high precision temperature and force decoupling in multi-parameter FBG sensing.

PubMed

Hopf, Barbara; Dutz, Franz J; Bosselmann, Thomas; Willsch, Michael; Koch, Alexander W; Roths, Johannes

2018-04-30

A new iterative matrix algorithm has been applied to improve the precision of temperature and force decoupling in multi-parameter FBG sensing. For the first time, this evaluation technique allows the integration of nonlinearities in the sensor's temperature characteristic and the temperature dependence of the sensor's force sensitivity. Applied to a sensor cable consisting of two FBGs in fibers with 80 µm and 125 µm cladding diameter installed in a 7 m-long coiled PEEK capillary, this technique significantly reduced the uncertainties in friction-compensated temperature measurements. In the presence of high friction-induced forces of up to 1.6 N the uncertainties in temperature evaluation were reduced from several degrees Celsius if using a standard linear matrix approach to less than 0.5°C if using the iterative matrix approach in an extended temperature range between -35°C and 125°C.

Hyperspectral imaging simulation of object under sea-sky background

NASA Astrophysics Data System (ADS)

Wang, Biao; Lin, Jia-xuan; Gao, Wei; Yue, Hui

2016-10-01

Remote sensing image simulation plays an important role in spaceborne/airborne load demonstration and algorithm development. Hyperspectral imaging is valuable in marine monitoring, search and rescue. On the demand of spectral imaging of objects under the complex sea scene, physics based simulation method of spectral image of object under sea scene is proposed. On the development of an imaging simulation model considering object, background, atmosphere conditions, sensor, it is able to examine the influence of wind speed, atmosphere conditions and other environment factors change on spectral image quality under complex sea scene. Firstly, the sea scattering model is established based on the Philips sea spectral model, the rough surface scattering theory and the water volume scattering characteristics. The measured bi directional reflectance distribution function (BRDF) data of objects is fit to the statistical model. MODTRAN software is used to obtain solar illumination on the sea, sky brightness, the atmosphere transmittance from sea to sensor and atmosphere backscattered radiance, and Monte Carlo ray tracing method is used to calculate the sea surface object composite scattering and spectral image. Finally, the object spectrum is acquired by the space transformation, radiation degradation and adding the noise. The model connects the spectrum image with the environmental parameters, the object parameters, and the sensor parameters, which provide a tool for the load demonstration and algorithm development.

SIMBIOS Normalized Water-Leaving Radiance Calibration and Validation: Sensor Response, Atmospheric Corrections, Stray Light and Sun Glint. Chapter 14

NASA Technical Reports Server (NTRS)

Mueller, James L.

2001-01-01

This Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) contract supports acquisition of match up radiometric and bio-optical data for validation of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and other ocean color satellites, and evaluation of uncertainty budgets and protocols for in situ measurements of normalized water leaving radiances.

Use of multiple sensor technologies for quality control of in situ biogeochemical measurements: A SeaCycler case study

NASA Astrophysics Data System (ADS)

Atamanchuk, Dariia; Koelling, Jannes; Lai, Jeremy; Send, Uwe; Wallace, Douglas

2017-04-01

Over the last two decades observing capacity for the global ocean has increased dramatically. Emerging sensor technologies for dissolved gases, nutrients and bio-optical properties in seawater are allowing extension of in situ observations beyond the traditionally measured salinity, temperature and pressure (CTD). However the effort to extend observations using autonomous instruments and platforms carries the risk of losing the level of data quality achievable through conventional water sampling techniques. We will present results from a case study with the SeaCycler profiling winch focusing on quality control of the in-situ measurements. A total of 13 sensors were deployed from May 2016 to early 2017 on SeaCycler's profiling sensor float, including CTD, dissolved oxygen (O2, 3 sensors), carbon dioxide (pCO2, 2 sensors), nutrients, velocity sensors, fluorometer, transmissometer, single channel PAR sensor, and others. We will highlight how multiple measurement technologies (e.g. for O2 and CO2) complement each other and result in a high quality data product. We will also present an initial assessment of the bio-optical data, their implications for seasonal phytoplankton dynamics and comparisons to climatologies and ocean-color data products obtained from the MODIS satellite.

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement, and Transition to MODIS

NASA Technical Reports Server (NTRS)

Fowler, Charles; Maslanik, James; Stone, Robert; Stroeve, Julienne; Emery, William

2001-01-01

The AVHRR-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and a cloud mask composited into twice- per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 deg. latitude. Our goals under this grant, in general, are four-fold: 1. To quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements. 2. To determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output. 3. To investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program. 4. To compare an annual cycle of the AVHRR Pathfinder products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period. Year One tasks include intercomparisons of the Pathfinder products with field measurements, testing of algorithm assumptions, collection of field data, and further validation and possible improvement of the multi-sensor ice motion fields. Achievements for these tasks are summarized below.

Space-borne polarimetric SAR sensors or the golden age of radar polarimetry

NASA Astrophysics Data System (ADS)

Pottier, E.

2010-06-01

SAR Polarimetry represents an active area of research in Active Earth Remote Sensing. This interest is clearly supported by the fact that nowadays there exists, or there will exist in a very next future, a non negligible quantity of launched Polarimetric SAR Spaceborne sensors. The ENVISAT satellite, developed by ESA, was launched on March 2002, and was the first Spaceborne sensor offering an innovative dualpolarization Advanced Synthetic Aperture Radar (ASAR) system operating at C-band. The second Polarimetric Spaceborne sensor is ALOS, a Japanese Earth-Observation satellite, developed by JAXA and was launched in January 2006. This mission includes an active L-band polarimetric radar sensor (PALSAR) whose highresolution data may be used for environmental and hazard monitoring. The third Polarimetric Spaceborne sensor is TerraSAR-X, a new German radar satellite, developed by DLR, EADS-Astrium and Infoterra GmbH, was launched on June 2007. This sensor carries a dual-polarimetric and high frequency X-Band SAR sensor that can be operated in different modes and offers features that were not available from space before. At least, the Polarimetric Spaceborne sensor, developed by CSA and MDA, and named RADARSAT-2 was launched in December 2007 The Radarsat program was born out the need for effective monitoring of Canada’s icy waters, and some Radarsat-2 capabilities that benefit sea- and river ice applications are the multi-polarization options that will improve ice-edge detection, ice-type discrimination and structure information. The many advances in these different Polarimetric Spaceborne platforms were developed to respond to specific needs for radar data in environmental monitoring applications around the world, like : sea- and river-ice monitoring, marine surveillance, disaster management, oil spill detection, snow monitoring, hydrology, mapping, geology, agriculture, soil characterisation, forestry applications (biomass, allometry, height…), urban mapping etc…. In order to promote the exploitation of Polarimetric Spaceborne data, as it is starting today to proliferate with the launch of these Polarimetric SAR sensors, the PolSARpro Software, developed under contract to ESA and that is a toolbox for the scientific exploitation of Polarimetric SAR and Polarimetric-Interferometric data and a tool for high-level education in radar polarimetry, has been expanded and refined to include all elements necessary for the demonstration of a number of key applications. The PolSARpro Software, that already was supporting an important range of airborne and spaceborne polarimetric data sources, supports now the following additional data sources: ALOS-PALSAR (Dual-Pol fine mode and Quad-Pol mode), TerraSAR-X (Dual-pol mode) and Radarsat-2 (Dual-Pol fine mode and Quad-Pol fine and standard modes), by offering a platform dedicated interface for E.O Scientific Investigator. A number of illustrations of key applications has been developed for the demonstration and the promotion of the Polarimetric Spaceborne missions, that are consistent with the activities incorporated in the GMES Services Element (GSE). The aim of this communication is to present the current state of the art in SAR Polarimetry ranging from theory to applications, with special emphasis in the analysis of data provided by the new Polarimetric Spaceborne SAR sensors, and samples of real polarimetric data will be presented for use in real-life examples of key applications.

Fast Measurement and Reconstruction of Large Workpieces with Freeform Surfaces by Combining Local Scanning and Global Position Data

PubMed Central

Chen, Zhe; Zhang, Fumin; Qu, Xinghua; Liang, Baoqiu

2015-01-01

In this paper, we propose a new approach for the measurement and reconstruction of large workpieces with freeform surfaces. The system consists of a handheld laser scanning sensor and a position sensor. The laser scanning sensor is used to acquire the surface and geometry information, and the position sensor is utilized to unify the scanning sensors into a global coordinate system. The measurement process includes data collection, multi-sensor data fusion and surface reconstruction. With the multi-sensor data fusion, errors accumulated during the image alignment and registration process are minimized, and the measuring precision is significantly improved. After the dense accurate acquisition of the three-dimensional (3-D) coordinates, the surface is reconstructed using a commercial software piece, based on the Non-Uniform Rational B-Splines (NURBS) surface. The system has been evaluated, both qualitatively and quantitatively, using reference measurements provided by a commercial laser scanning sensor. The method has been applied for the reconstruction of a large gear rim and the accuracy is up to 0.0963 mm. The results prove that this new combined method is promising for measuring and reconstructing the large-scale objects with complex surface geometry. Compared with reported methods of large-scale shape measurement, it owns high freedom in motion, high precision and high measurement speed in a wide measurement range. PMID:26091396

An Automated Method for Navigation Assessment for Earth Survey Sensors Using Island Targets

NASA Technical Reports Server (NTRS)

Patt, F. S.; Woodward, R. H.; Gregg, W. W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalogue of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean colour sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Automated navigation assessment for earth survey sensors using island targets

NASA Technical Reports Server (NTRS)

Patt, Frederick S.; Woodward, Robert H.; Gregg, Watson W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalog of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean color sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Identification of Hot Moments and Hot Spots for Real-Time Adaptive Control of Multi-scale Environmental Sensor Networks

NASA Astrophysics Data System (ADS)

Wietsma, T.; Minsker, B. S.

2012-12-01

Increased sensor throughput combined with decreasing hardware costs has led to a disruptive growth in data volume. This disruption, popularly termed "the data deluge," has placed new demands for cyberinfrastructure and information technology skills among researchers in many academic fields, including the environmental sciences. Adaptive sampling has been well established as an effective means of improving network resource efficiency (energy, bandwidth) without sacrificing sample set quality relative to traditional uniform sampling. However, using adaptive sampling for the explicit purpose of improving resolution over events -- situations displaying intermittent dynamics and unique hydrogeological signatures -- is relatively new. In this paper, we define hot spots and hot moments in terms of sensor signal activity as measured through discrete Fourier analysis. Following this frequency-based approach, we apply the Nyquist-Shannon sampling theorem, a fundamental contribution from signal processing that led to the field of information theory, for analysis of uni- and multivariate environmental signal data. In the scope of multi-scale environmental sensor networks, we present several sampling control algorithms, derived from the Nyquist-Shannon theorem, that operate at local (field sensor), regional (base station for aggregation of field sensor data), and global (Cloud-based, computationally intensive models) scales. Evaluated over soil moisture data, results indicate significantly greater sample density during precipitation events while reducing overall sample volume. Using these algorithms as indicators rather than control mechanisms, we also discuss opportunities for spatio-temporal modeling as a tool for planning/modifying sensor network deployments. Locally adaptive model based on Nyquist-Shannon sampling theorem Pareto frontiers for local, regional, and global models relative to uniform sampling. Objectives are (1) overall sampling efficiency and (2) sampling efficiency during hot moments as identified using heuristic approach.

A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

NASA Astrophysics Data System (ADS)

Li, Jing; Xie, Weixin; Pei, Jihong

2018-03-01

Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

Multi-decadal Arctic sea ice roughness.

NASA Astrophysics Data System (ADS)

Tsamados, M.; Stroeve, J.; Kharbouche, S.; Muller, J. P., , Prof; Nolin, A. W.; Petty, A.; Haas, C.; Girard-Ardhuin, F.; Landy, J.

2017-12-01

The transformation of Arctic sea ice from mainly perennial, multi-year ice to a seasonal, first-year ice is believed to have been accompanied by a reduction of the roughness of the ice cover surface. This smoothening effect has been shown to (i) modify the momentum and heat transfer between the atmosphere and ocean, (ii) to alter the ice thickness distribution which in turn controls the snow and melt pond repartition over the ice cover, and (iii) to bias airborne and satellite remote sensing measurements that depend on the scattering and reflective characteristics over the sea ice surface topography. We will review existing and novel remote sensing methodologies proposed to estimate sea ice roughness, ranging from airborne LIDAR measurement (ie Operation IceBridge), to backscatter coefficients from scatterometers (ASCAT, QUICKSCAT), to multi angle maging spectroradiometer (MISR), and to laser (Icesat) and radar altimeters (Envisat, Cryosat, Altika, Sentinel-3). We will show that by comparing and cross-calibrating these different products we can offer a consistent multi-mission, multi-decadal view of the declining sea ice roughness. Implications for sea ice physics, climate and remote sensing will also be discussed.

Cloud Forecasting and 3-D Radiative Transfer Model Validation using Citizen-Sourced Imagery

NASA Astrophysics Data System (ADS)

Gasiewski, A. J.; Heymsfield, A.; Newman Frey, K.; Davis, R.; Rapp, J.; Bansemer, A.; Coon, T.; Folsom, R.; Pfeufer, N.; Kalloor, J.

2017-12-01

Cloud radiative feedback mechanisms are one of the largest sources of uncertainty in global climate models. Variations in local 3D cloud structure impact the interpretation of NASA CERES and MODIS data for top-of-atmosphere radiation studies over clouds. Much of this uncertainty results from lack of knowledge of cloud vertical and horizontal structure. Surface-based data on 3-D cloud structure from a multi-sensor array of low-latency ground-based cameras can be used to intercompare radiative transfer models based on MODIS and other satellite data with CERES data to improve the 3-D cloud parameterizations. Closely related, forecasting of solar insolation and associated cloud cover on time scales out to 1 hour and with spatial resolution of 100 meters is valuable for stabilizing power grids with high solar photovoltaic penetrations. Data for cloud-advection based solar insolation forecasting with requisite spatial resolution and latency needed to predict high ramp rate events obtained from a bottom-up perspective is strongly correlated with cloud-induced fluctuations. The development of grid management practices for improved integration of renewable solar energy thus also benefits from a multi-sensor camera array. The data needs for both 3D cloud radiation modelling and solar forecasting are being addressed using a network of low-cost upward-looking visible light CCD sky cameras positioned at 2 km spacing over an area of 30-60 km in size acquiring imagery on 30 second intervals. Such cameras can be manufactured in quantity and deployed by citizen volunteers at a marginal cost of 200-400 and operated unattended using existing communications infrastructure. A trial phase to understand the potential utility of up-looking multi-sensor visible imagery is underway within this NASA Citizen Science project. To develop the initial data sets necessary to optimally design a multi-sensor cloud camera array a team of 100 citizen scientists using self-owned PDA cameras is being organized to collect distributed cloud data sets suitable for MODIS-CERES cloud radiation science and solar forecasting algorithm development. A low-cost and robust sensor design suitable for large scale fabrication and long term deployment has been developed during the project prototyping phase.

Wireless Sensors and Networks for Advanced Energy Management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hardy, J.E.

Numerous national studies and working groups have identified low-cost, very low-power wireless sensors and networks as a critical enabling technology for increasing energy efficiency, reducing waste, and optimizing processes. Research areas for developing such sensor and network platforms include microsensor arrays, ultra-low power electronics and signal conditioning, data/control transceivers, and robust wireless networks. A review of some of the research in the following areas will be discussed: (1) Low-cost, flexible multi-sensor array platforms (CO{sub 2}, NO{sub x}, CO, humidity, NH{sub 3}, O{sub 2}, occupancy, etc.) that enable energy and emission reductions in applications such as buildings and manufacturing; (2) Modelingmore » investments (energy usage and savings to drive capital investment decisions) and estimated uptime improvements through pervasive gathering of equipment and process health data and its effects on energy; (3) Robust, self-configuring wireless sensor networks for energy management; and (4) Quality-of-service for secure and reliable data transmission from widely distributed sensors. Wireless communications is poised to support technical innovations in the industrial community, with widespread use of wireless sensors forecasted to improve manufacturing production and energy efficiency and reduce emissions. Progress being made in wireless system components, as described in this paper, is helping bring these projected improvements to reality.« less

A New Multifunctional Sensor for Measuring Oil/Water Two-phase State in Pipelines

NASA Astrophysics Data System (ADS)

Sun, Jinwei; Shida, Katsunori

2001-03-01

This paper presents a non-contact U form multi-functional sensor for the oil pipeline flow measurement. Totally four thin and narrow copper plates are twined on both sides of the sensor, from which two variables (capacitance, self inductance) are to be examined as the two functional outputs of the sensor. Thus, the liquid concentration (oil and water), temperature are finally evaluated. The flow velocity inside the pipeline could also be estimated by computing the cross correlation of the capacitance-pair. To restrain the effects of parasitic parameters and improve the dynamic response of the sensor, a proper shielding strategy is considered. A suitable algorithm for data reconstruction is also presented in the system design.

Earth Science Data Fusion with Event Building Approach

NASA Technical Reports Server (NTRS)

Lukashin, C.; Bartle, Ar.; Callaway, E.; Gyurjyan, V.; Mancilla, S.; Oyarzun, R.; Vakhnin, A.

2015-01-01

Objectives of the NASA Information And Data System (NAIADS) project are to develop a prototype of a conceptually new middleware framework to modernize and significantly improve efficiency of the Earth Science data fusion, big data processing and analytics. The key components of the NAIADS include: Service Oriented Architecture (SOA) multi-lingual framework, multi-sensor coincident data Predictor, fast into-memory data Staging, multi-sensor data-Event Builder, complete data-Event streaming (a work flow with minimized IO), on-line data processing control and analytics services. The NAIADS project is leveraging CLARA framework, developed in Jefferson Lab, and integrated with the ZeroMQ messaging library. The science services are prototyped and incorporated into the system. Merging the SCIAMACHY Level-1 observations and MODIS/Terra Level-2 (Clouds and Aerosols) data products, and ECMWF re- analysis will be used for NAIADS demonstration and performance tests in compute Cloud and Cluster environments.

Probing the Hydrogen Enhanced Near-Field Emission of ITO without a Vacuum-Gap

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poole, Jacob L.; Yu, Yang; Ohodnicki, Paul R.

In-situ monitoring of the multi-component gas streams in high temperature energy conversion devices offer the promises to higher efficiency via improved understanding of the chemical environments during device operation. While conventional resistive based metal oxide semiconductor gas sensors suffer from strong cross-sensitivity, optical sensing approaches offer intrinsic advantages to achieve gas selectivity based on wavelength specific interactions. This manuscript describes a novel method to achieve multicomponent gas sensing during gas exposure of H2, CO2, CH4and CO in humid high temperature environments. A single sensor element comprised of a perovskite La0.3Sr0.7TiO3(LSTO) oxide thin film layer coated on silica optical fiber wasmore » used. The sensing responses consisted of two wavelength-specific near infrared (NIR) mechanisms, namely broadband absorption associated with the metal oxide layer, and wavelength localized thermal emission responses associated with the hydroxyl defects within the silica fiber. Principal component analysis (PCA) was applied to couple the two mechanisms to achieve selective gas identification. Successful discrimination of H2and CO2on a single fiber sensor was achieved, where the results are both stable and reversible. This design demonstrates that by coupling multiple optical mechanisms on a single oxide coated fiber sensor, simple platforms can also achieve multi-component sensing functionality without the added complexity of a sensor array. Thus, it suggests a new approach to construct simple, robust and functional sensor designs capable of gas discrimination and quantification in multi-component gas streams.« less

Optimum Sensors Integration for Multi-Sensor Multi-Target Environment for Ballistic Missile Defense Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Imam, Neena; Barhen, Jacob; Glover, Charles Wayne

2012-01-01

Multi-sensor networks may face resource limitations in a dynamically evolving multiple target tracking scenario. It is necessary to task the sensors efficiently so that the overall system performance is maximized within the system constraints. The central sensor resource manager may control the sensors to meet objective functions that are formulated to meet system goals such as minimization of track loss, maximization of probability of target detection, and minimization of track error. This paper discusses the variety of techniques that may be utilized to optimize sensor performance for either near term gain or future reward over a longer time horizon.

Advancing an In situ Laser Spectrometer for Carbon Isotope Analyses in the Deep Ocean

NASA Astrophysics Data System (ADS)

Michel, A.; Wankel, S. D.; Kapit, J.; Girguis, P. R.

2016-02-01

Development of in situ chemical sensors is critical for improving our understanding of deep-ocean biogeochemistry and recent advances in chemical sensors are already expanding the breadth and depth of deep sea/seafloor exploration and research. Although initially developed for high sensitivity measurements of atmospheric gases, laser-based spectroscopic sensors are now being developed for research in the deep sea by incorporating the use of semi-permeable membranes. Here we present on recent deep-sea deployments of an in situ laser-based analyzer of carbon isotopes of methane (δ13CH4), highlighting several advances including a new capability for also measuring δ13C of DIC or CO2 by incorporating a second laser and an in line acidification module. A bubble trapping approach was designed and implemented for the collection and analysis of both CH4 and CO2 from deep-sea bubbles. The newly advanced laser spectrometer was deployed at both Kick `Em Jenny volcano off of the island of Grenada and in a brine pool in the western Gulf of Mexico ("The Jacuzzi of Despair") using the E/V Nautilus and the ROV Hercules. At Kick `Em Jenny, seafloor measurements were made of both emanating fluids and bubbles from within and around the crater - revealing high levels of magmatic CO2 with minor amounts of CH4 and hydrogen sulfide. At the brine pool, spot measurements and depth profile measurements into the brine pool were made for chemical mapping, revealing fluids that were saturated with respect to methane. New technologies such as the laser spectrometer will enable us to obtain high resolution and near real-time, in situ chemical and isotopic data and to make geochemical maps over a range of spatial and temporal scales.

Improved thermal neutron activation sensor for detection of bulk explosives

NASA Astrophysics Data System (ADS)

McFee, John E.; Faust, Anthony A.; Andrews, H. Robert; Clifford, Edward T. H.; Mosquera, Cristian M.

2012-06-01

Defence R&D Canada - Suffield and Bubble Technology Industries have been developing thermal neutron activation (TNA) sensors for detection of buried bulk explosives since 1994. First generation sensors, employing an isotopic source and NaI(Tl) gamma ray detectors, were deployed by Canadian Forces in 2002 as confirmation sensors on the ILDS teleoperated, vehicle-mounted, multi-sensor anti-tank landmine detection systems. The first generation TNA could detect anti-tank mines buried 10 cm or less in no more than a minute, but deeper mines and those significantly displaced horizontally required considerably longer times. Mines as deep as 30 cm could be detected with long counting times (1000 s). The second generation TNA detector is being developed with a number of improvements aimed at increasing sensitivity and facilitating ease of operation. Among these are an electronic neutron generator to increase sensitivity for deeper and horizontally displaced explosives; LaBr3(Ce) scintillators, to improve time response and energy resolution; improved thermal and electronic stability; improved sensor head geometry to minimize spatial response nonuniformity; and more robust data processing. This improved sensitivity can translate to either decreased counting times, decreased minimum detectable explosive quantities, increased maximum sensor-to-target displacement, or a trade off among all three. Experiments to characterize the performance of the latest generation TNA in detecting buried landmines and IEDs hidden in culverts were conducted during 2011. This paper describes the second generation system. The experimental setup and methodology are detailed and preliminary comparisons between the performance of first and second generation systems are presented.

NASA COAST and OCEANIA Airborne Missions Support Ecosystem and Water Quality Research in the Coastal Zone

NASA Technical Reports Server (NTRS)

Guild, Liane; Kudela, Raphael; Hooker, Stanford; Morrow, John; Russell, Philip; Palacios, Sherry; Livingston, John M.; Negrey, Kendra; Torres-Perez, Juan; Broughton, Jennifer

2014-01-01

NASA has a continuing requirement to collect high-quality in situ data for the vicarious calibration of current and next generation ocean color satellite sensors and to validate the algorithms that use the remotely sensed observations. Recent NASA airborne missions over Monterey Bay, CA, have demonstrated novel above- and in-water measurement capabilities supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The results characterize coastal atmospheric and aquatic properties through an end-to-end assessment of image acquisition, atmospheric correction, algorithm application, plus sea-truth observations from state-of-the-art instrument systems. The primary goal is to demonstrate the following in support of calibration and validation exercises for satellite coastal ocean color products: 1) the utility of a multi-sensor airborne instrument suite to assess the bio-optical properties of coastal California, including water quality; and 2) the importance of contemporaneous atmospheric measurements to improve atmospheric correction in the coastal zone. The imaging spectrometer (Headwall) is optimized in the blue spectral domain to emphasize remote sensing of marine and freshwater ecosystems. The novel airborne instrument, Coastal Airborne In-situ Radiometers (C-AIR) provides measurements of apparent optical properties with high dynamic range and fidelity for deriving exact water leaving radiances at the land-ocean boundary, including radiometrically shallow aquatic ecosystems. Simultaneous measurements supporting empirical atmospheric correction of image data are accomplished using the Ames Airborne Tracking Sunphotometer (AATS-14). Flight operations are presented for the instrument payloads using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter flown over Monterey Bay during the seasonal fall algal bloom in 2011 (COAST) and 2013 (OCEANIA) to support bio-optical measurements of phytoplankton for coastal zone research.

Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network.

PubMed

Han, Changcai; Yang, Jinsheng

2017-10-30

The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes.

Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network

PubMed Central

Han, Changcai; Yang, Jinsheng

2017-01-01

The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes. PMID:29084155

Recent progress in millimeter-wave sensor system capabilities for enhanced (synthetic) vision

NASA Astrophysics Data System (ADS)

Hellemann, Karlheinz; Zachai, Reinhard

1999-07-01

Weather- and daylight independent operation of modern traffic systems is strongly required for an optimized and economic availability. Mainly helicopters, small aircraft and military transport aircraft operating frequently close to the ground have a need for effective and cost-effective Enhanced Vision sensors. The technical progress in sensor technology and processing speed offer today the possibility for new concepts to be realized. Derived from this background the paper reports on the improvements which are under development within the HiVision program at DaimlerChrysler Aerospace. A sensor demonstrator based on FMCW radar technology with high information update-rate and operating in the mm-wave band, has been up-graded to improve performance and fitted to fly on an experimental base. The results achieved so far demonstrate the capability to produce a weather independent enhanced vision. In addition the demonstrator has been tested on board a high- speed ferry at the Baltic sea, because fast vessels have a similar need for weather-independent operation and anti- collision measures. In the future one sensor type may serve both 'worlds' and help ease and save traffic. The described demonstrator fills up the technology gap between optical sensors (Infrared) and standard pulse radars with its specific features such as high speed scanning and weather penetration with the additional benefit of cost-effectiveness.

SeaWiFS technical report series. Volume 15: The simulated SesWiFS data set, version 2

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Gregg, Watson W.; Patt, Frederick S.; Woodward, Robert H.

1994-01-01

This document describes the second version of the simulated SeaWiFS data set. A realistic simulated data set is essential for mission readiness preparations and can potentially assist in all phases of ground support for a future mission. The second version improves on the first version primarily through additional realism and complexity. This version incorporates a representation of virtually every aspect of the flight mission. Thus, it provides a high-fidelity data set for testing several aspects of the ground system, including data acquisition, data processing, data transfers, calibration and validation, quality control, and mission operations. The data set is constructed for a seven-day period, 25-31 March 1994. Specific features of the data set include Global Area coverage (GAC), recorded Local Area Coverage (LAC), and realtime High Resolution Picture Transmission (HRPT) data for the seven-day period. A realistic orbit, which is propagated using a Brouwer-Lyddane model with drag, is used to simulate orbit positions. The simulated data corresponds to the command schedule based on the orbit for this seven-day period. It includes total (at-satellite) radiances not only for ocean, but for land, clouds, and ice. The simulation also utilizes a high-resolution land-sea mask. It includes the April 1993 SeaWiFS spectral responses and sensor saturation responses. The simulation is formatted according to July 1993 onboard data structures, which include corresponding telemetry (instrument and spacecraft) data. The methods are described and some examples of the output are given. The instrument response functions made available in April 1993 have been used to produce the Version 2 simulated data. These response functions will change as part of the sensor improvements initiated in July-August 1993.

Environmental Measurements in the Beaufort Sea, Spring 1988

DTIC Science & Technology

1989-03-01

electrical cable. The sensor package consisted of a thermistor (Sea-Bird), a conductivity cell (Sea-Bird), a pressure sensor (Paroscientific Digiquartz), and... Frankenstein and Garner9 based on the measured temperature (0Q and salinity (%o): Vb = S (-52.56/T - 2.28) for -0.5 >T >-2.06 Vb =S (-45.917/T + 0.93...Science and Engineering Monograph II-C3, Cold Regions Research and Engineer- ing Laboratory, Hanover, NH, 1967. 9. F. Frankenstein and R. Garner

Frequency domain surface EMG sensor fusion for estimating finger forces.

PubMed

Potluri, Chandrasekhar; Kumar, Parmod; Anugolu, Madhavi; Urfer, Alex; Chiu, Steve; Naidu, D; Schoen, Marco P

2010-01-01

Extracting or estimating skeletal hand/finger forces using surface electro myographic (sEMG) signals poses many challenges due to cross-talk, noise, and a temporal and spatially modulated signal characteristics. Normal sEMG measurements are based on single sensor data. In this paper, array sensors are used along with a proposed sensor fusion scheme that result in a simple Multi-Input-Single-Output (MISO) transfer function. Experimental data is used along with system identification to find this MISO system. A Genetic Algorithm (GA) approach is employed to optimize the characteristics of the MISO system. The proposed fusion-based approach is tested experimentally and indicates improvement in finger/hand force estimation.

Multi-interface level in oil tanks and applications of optical fiber sensors

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Marques, Carlos; Frizera, Anselmo; Pontes, Maria José

2018-01-01

On the oil production also involves the production of water, gas and suspended solids, which are separated from the oil on three-phase separators. However, the control strategies of an oil separator are limited due to unavailability of suitable multi-interface level sensors. This paper presents a description of the multi-phase level problem on the oil industry and a review of the current technologies for multi-interface level assessment. Since optical fiber sensors present chemical stability, intrinsic safety, electromagnetic immunity, lightweight and multiplexing capabilities, it can be an alternative for multi-interface level measurement that can overcome some of the limitations of the current technologies. For this reason, Fiber Bragg Gratings (FBGs) based optical fiber sensor system for multi-interface level assessment is proposed, simulated and experimentally assessed. The results show that the proposed sensor system is capable of measuring interface level with a relative error of only 2.38%. Furthermore, the proposed sensor system is also capable of measuring the oil density with an error of 0.8 kg/m3.

Smart chemical sensors using ZnO semiconducting thin films for freshness detection of foods and beverages

NASA Astrophysics Data System (ADS)

Nanto, Hidehito; Kobayashi, Toshiki; Dougami, Naganori; Habara, Masaaki; Yamamoto, Hajime; Kusano, Eiji; Kinbara, Akira; Douguchi, Yoshiteru

1998-07-01

The sensitivity of the chemical sensor, based on the resistance change of Al2O3-doped and SnO2-doped ZnO (ZnO:Al and ZnO:SnO2) thin film, is studied for exposure to various gases. It is found that the ZnO:Al and ZnO:Sn thin film chemical sensor has a high sensitivity and excellent selectivity for amine (TMA and DMA) gas and ethanol gas, respectively. The ZnO:Al (5.0 wt%) thin film chemical sensor which exhibit a high sensitivity for exposure to odors from rotten sea foods, such as salmon, sea bream, oyster, squid and sardine, responds to the freshness change of these sea foods. The ZnO:SnO2 (78 wt%) thin film chemical sensor which exhibit a high sensitivity for exposure to aroma from alcohols, such as wine, Japanese sake, and whisky, responds to the freshness change of these alcohols.

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas

DTIC Science & Technology

2014-09-30

developed by incorporating the proposed IR sensors and ground-sky temperature difference algorithm into a tethered balloon borne payload (Figure 3...into the cloud base. RESULTS FROM FY 2014 • A second flight of the tethered balloon -borne IR cloud margin sensor was conducted in Colorado on...Figure 3: Tethered balloon -borne IR sensing payload IR Cloud Margin Sensor Figure 4: First successful flight validation of the IR cloud

SCHeMA web-based observation data information system

NASA Astrophysics Data System (ADS)

Novellino, Antonio; Benedetti, Giacomo; D'Angelo, Paolo; Confalonieri, Fabio; Massa, Francesco; Povero, Paolo; Tercier-Waeber, Marie-Louise

2016-04-01

It is well recognized that the need of sharing ocean data among non-specialized users is constantly increasing. Initiatives that are built upon international standards will contribute to simplify data processing and dissemination, improve user-accessibility also through web browsers, facilitate the sharing of information across the integrated network of ocean observing systems; and ultimately provide a better understanding of the ocean functioning. The SCHeMA (Integrated in Situ Chemical MApping probe) Project is developing an open and modular sensing solution for autonomous in situ high resolution mapping of a wide range of anthropogenic and natural chemical compounds coupled to master bio-physicochemical parameters (www.schema-ocean.eu). The SCHeMA web system is designed to ensure user-friendly data discovery, access and download as well as interoperability with other projects through a dedicated interface that implements the Global Earth Observation System of Systems - Common Infrastructure (GCI) recommendations and the international Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE) standards. This approach will insure data accessibility in compliance with major European Directives and recommendations. Being modular, the system allows the plug-and-play of commercially available probes as well as new sensor probess under development within the project. The access to the network of monitoring probes is provided via a web-based system interface that, being implemented as a SOS (Sensor Observation Service), is providing standard interoperability and access tosensor observations systems through O&M standard - as well as sensor descriptions - encoded in Sensor Model Language (SensorML). The use of common vocabularies in all metadatabases and data formats, to describe data in an already harmonized and common standard is a prerequisite towards consistency and interoperability. Therefore, the SCHeMA SOS has adopted the SeaVox common vocabularies populated by SeaDataNet network of National Oceanographic Data Centres. The SCHeMA presentation layer, a fundamental part of the software architecture, offers to the user a bidirectional interaction with the integrated system allowing to manage and configure the sensor probes; view the stored observations and metadata, and handle alarms. The overall structure of the web portal developed within the SCHeMA initiative (Sensor Configuration, development of Core Profile interface for data access via OGC standard, external services such as web services, WMS, WFS; and Data download and query manager) will be presented and illustrated with examples of ongoing tests in costal and open sea.

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

On-Orbit Cross-Calibration of AM Satellite Remote Sensing Instruments using the Moon

NASA Technical Reports Server (NTRS)

Butler, James J.; Kieffer, Hugh H.; Barnes, Robert A.; Stone, Thomas C.

2003-01-01

On April 14,2003, three Earth remote sensing spacecraft were maneuvered enabling six satellite instruments operating in the visible through shortwave infrared wavelength region to view the Moon for purposes of on-orbit cross-calibration. These instruments included the Moderate Resolution Imaging Spectroradiometer (MODIS), the Multi-angle Imaging SpectroRadiometer (MISR), the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer on the Earth Observing System (EOS) Terra spacecraft, the Advanced Land Imager (ALI) and Hyperion instrument on Earth Observing-1 (EO-1) spacecraft, and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on the SeaStar spacecraft. Observations of the Moon were compared using a spectral photometric mode for lunar irradiance developed by the Robotic Lunar Observatory (ROLO) project located at the United States Geological Survey in Flagstaff, Arizona. The ROLO model effectively accounts for variations in lunar irradiance corresponding to lunar phase and libration angles, allowing intercomparison of observations made by instruments on different spacecraft under different time and location conditions. The spacecraft maneuvers necessary to view the Moon are briefly described and results of using the lunar irradiance model in comparing the radiometric calibration scales of the six satellite instruments are presented here.

A new EMI system for detection and classification of challenging targets

NASA Astrophysics Data System (ADS)

Shubitidze, F.; Fernández, J. P.; Barrowes, B. E.; O'Neill, K.

2013-06-01

Advanced electromagnetic induction (EMI) sensors currently feature multi-axis illumination of targets and tri-axial vector sensing (e.g., MetalMapper), or exploit multi-static array data acquisition (e.g., TEMTADS). They produce data of high density, quality, and diversity, and have been combined with advanced EMI models to provide superb classification performance relative to the previous generation of single-axis, monostatic sensors. However, these advances yet have to improve significantly our ability to classify small, deep, and otherwise challenging targets. Particularly, recent live-site discrimination studies at Camp Butner, NC and Camp Beale, CA have revealed that it is more challenging to detect and discriminate small munitions (with calibers ranging from 20 mm to 60 mm) than larger ones. In addition, a live-site test at the Massachusetts Military Reservation, MA highlighted the difficulties for current sensors to classify large, deep, and overlapping targets with high confidence. There are two main approaches to overcome these problems: 1) adapt advanced EMI models to the existing systems and 2) improve the detection limits of current sensors by modifying their hardware. In this paper we demonstrate a combined software/hardware approach that will provide extended detection range and spatial resolution to next-generation EMI systems; we analyze and invert EMI data to extract classification features for small and deep targets; and we propose a new system that features a large transmitter coil.

A Tactile Sensor Network System Using a Multiple Sensor Platform with a Dedicated CMOS-LSI for Robot Applications †

PubMed Central

Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki; Bartley, Travis; Muroyama, Masanori

2017-01-01

Robot tactile sensation can enhance human–robot communication in terms of safety, reliability and accuracy. The final goal of our project is to widely cover a robot body with a large number of tactile sensors, which has significant advantages such as accurate object recognition, high sensitivity and high redundancy. In this study, we developed a multi-sensor system with dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) circuit chips (referred to as “sensor platform LSI”) as a framework of a serial bus-based tactile sensor network system. The sensor platform LSI supports three types of sensors: an on-chip temperature sensor, off-chip capacitive and resistive tactile sensors, and communicates with a relay node via a bus line. The multi-sensor system was first constructed on a printed circuit board to evaluate basic functions of the sensor platform LSI, such as capacitance-to-digital and resistance-to-digital conversion. Then, two kinds of external sensors, nine sensors in total, were connected to two sensor platform LSIs, and temperature, capacitive and resistive sensing data were acquired simultaneously. Moreover, we fabricated flexible printed circuit cables to demonstrate the multi-sensor system with 15 sensor platform LSIs operating simultaneously, which showed a more realistic implementation in robots. In conclusion, the multi-sensor system with up to 15 sensor platform LSIs on a bus line supporting temperature, capacitive and resistive sensing was successfully demonstrated. PMID:29061954

A Tactile Sensor Network System Using a Multiple Sensor Platform with a Dedicated CMOS-LSI for Robot Applications.

PubMed

Shao, Chenzhong; Tanaka, Shuji; Nakayama, Takahiro; Hata, Yoshiyuki; Bartley, Travis; Nonomura, Yutaka; Muroyama, Masanori

2017-08-28

Robot tactile sensation can enhance human-robot communication in terms of safety, reliability and accuracy. The final goal of our project is to widely cover a robot body with a large number of tactile sensors, which has significant advantages such as accurate object recognition, high sensitivity and high redundancy. In this study, we developed a multi-sensor system with dedicated Complementary Metal-Oxide-Semiconductor (CMOS) Large-Scale Integration (LSI) circuit chips (referred to as "sensor platform LSI") as a framework of a serial bus-based tactile sensor network system. The sensor platform LSI supports three types of sensors: an on-chip temperature sensor, off-chip capacitive and resistive tactile sensors, and communicates with a relay node via a bus line. The multi-sensor system was first constructed on a printed circuit board to evaluate basic functions of the sensor platform LSI, such as capacitance-to-digital and resistance-to-digital conversion. Then, two kinds of external sensors, nine sensors in total, were connected to two sensor platform LSIs, and temperature, capacitive and resistive sensing data were acquired simultaneously. Moreover, we fabricated flexible printed circuit cables to demonstrate the multi-sensor system with 15 sensor platform LSIs operating simultaneously, which showed a more realistic implementation in robots. In conclusion, the multi-sensor system with up to 15 sensor platform LSIs on a bus line supporting temperature, capacitive and resistive sensing was successfully demonstrated.

A precision multi-sampler for deep-sea hydrothermal microbial mat studies

NASA Astrophysics Data System (ADS)

Breier, J. A.; Gomez-Ibanez, D.; Reddington, E.; Huber, J. A.; Emerson, D.

2012-12-01

A new tool was developed for deep-sea microbial mat studies by remotely operated vehicles and was successfully deployed during a cruise to the hydrothermal vent systems of the Mid-Cayman Rise. The Mat Sampler allows for discrete, controlled material collection from complex microbial structures, vertical-profiling within thick microbial mats and particulate and fluid sample collection from venting seafloor fluids. It has a reconfigurable and expandable sample capacity based on magazines of 6 syringes, filters, or water bottles. Multiple magazines can be used such that 12-36 samples can be collected routinely during a single dive; several times more if the dive is dedicated for this purpose. It is capable of hosting in situ physical, electrochemical, and optical sensors, including temperature and oxygen probes in order to guide sampling and to record critical environmental parameters at the time and point of sample collection. The precision sampling capability of this instrument will greatly enhance efforts to understand the structured, delicate, microbial mat communities that grow in diverse benthic habitats.

Arctic Sea Ice Classification and Mapping for Surface Albedo Parameterization in Sea Ice Modeling

NASA Astrophysics Data System (ADS)

Nghiem, S. V.; Clemente-Colón, P.; Perovich, D. K.; Polashenski, C.; Simpson, W. R.; Rigor, I. G.; Woods, J. E.; Nguyen, D. T.; Neumann, G.

2016-12-01

A regime shift of Arctic sea ice from predominantly perennial sea ice (multi-year ice or MYI) to seasonal sea ice (first-year ice or FYI) has occurred in recent decades. This shift has profoundly altered the proportional composition of different sea ice classes and the surface albedo distribution pertaining to each sea ice class. Such changes impacts physical, chemical, and biological processes in the Arctic atmosphere-ice-ocean system. The drastic changes upset the traditional geophysical representation of surface albedo of the Arctic sea ice cover in current models. A critical science issue is that these profound changes must be rigorously and systematically observed and characterized to enable a transformative re-parameterization of key model inputs, such as ice surface albedo, to ice-ocean-atmosphere climate modeling in order to obtain re-analyses that accurately reproduce Arctic changes and also to improve sea ice and weather forecast models. Addressing this challenge is a strategy identified by the National Research Council study on "Seasonal to Decadal Predictions of Arctic Sea Ice - Challenges and Strategies" to replicate the new Arctic reality. We review results of albedo characteristics associated with different sea ice classes such as FYI and MYI. Then we demonstrate the capability for sea ice classification and mapping using algorithms developed by the Jet Propulsion Laboratory and by the U.S. National Ice Center for use with multi-sourced satellite radar data at L, C, and Ku bands. Results obtained with independent algorithms for different radar frequencies consistently identify sea ice classes and thereby cross-verify the sea ice classification methods. Moreover, field observations obtained from buoy webcams and along an extensive trek across Elson Lagoon and a sector of the Beaufort Sea during the BRomine, Ozone, and Mercury EXperiment (BROMEX) in March 2012 are used to validate satellite products of sea ice classes. This research enables the mapping of Arctic sea ice classes over multiple decades using multiple satellite radar datasets with both coarse resolution for synoptic scales and high resolution for local and regional scales, which are crucial for realistic surface albedo parameterization to significantly advance sea ice forecast and projection models.

Using Ensemble Decisions and Active Selection to Improve Low-Cost Labeling for Multi-View Data

NASA Technical Reports Server (NTRS)

Rebbapragada, Umaa; Wagstaff, Kiri L.

2011-01-01

This paper seeks to improve low-cost labeling in terms of training set reliability (the fraction of correctly labeled training items) and test set performance for multi-view learning methods. Co-training is a popular multiview learning method that combines high-confidence example selection with low-cost (self) labeling. However, co-training with certain base learning algorithms significantly reduces training set reliability, causing an associated drop in prediction accuracy. We propose the use of ensemble labeling to improve reliability in such cases. We also discuss and show promising results on combining low-cost ensemble labeling with active (low-confidence) example selection. We unify these example selection and labeling strategies under collaborative learning, a family of techniques for multi-view learning that we are developing for distributed, sensor-network environments.

A system for activity recognition using multi-sensor fusion.

PubMed

Gao, Lei; Bourke, Alan K; Nelson, John

2011-01-01

This paper proposes a system for activity recognition using multi-sensor fusion. In this system, four sensors are attached to the waist, chest, thigh, and side of the body. In the study we present two solutions for factors that affect the activity recognition accuracy: the calibration drift and the sensor orientation changing. The datasets used to evaluate this system were collected from 8 subjects who were asked to perform 8 scripted normal activities of daily living (ADL), three times each. The Naïve Bayes classifier using multi-sensor fusion is adopted and achieves 70.88%-97.66% recognition accuracies for 1-4 sensors.

FM-UWB: Towards a Robust, Low-Power Radio for Body Area Networks

PubMed Central

Kopta, Vladimir; Farserotu, John; Enz, Christian

2017-01-01

The Frequency Modulated Ultra-Wideband (FM-UWB) is known as a low-power, low-complexity modulation scheme targeting low to moderate data rates in applications such as wireless body area networks. In this paper, a thorough review of all FM-UWB receivers and transmitters reported in literature is presented. The emphasis is on trends in power reduction that exhibit an improvement by a factor 20 over the past eight years, showing the high potential of FM-UWB. The main architectural and circuit techniques that have led to this improvement are highlighted. Seldom explored potential of using higher data rates and more complex modulations is demonstrated as a way to increase energy efficiency of FM-UWB. Multi-user communication over a single Radio Frequency (RF) channel is explored in more depth and multi-channel transmission is proposed as an extension of standard FM-UWB. The two techniques provide means of decreasing network latency, improving performance, and allow the FM-UWB to accommodate the increasing number of sensor nodes in the emerging applications such as High-Density Wireless Sensor Networks. PMID:28481248

Sensor-scheduling simulation of disparate sensors for Space Situational Awareness

NASA Astrophysics Data System (ADS)

Hobson, T.; Clarkson, I.

2011-09-01

The art and science of space situational awareness (SSA) has been practised and developed from the time of Sputnik. However, recent developments, such as the accelerating pace of satellite launch, the proliferation of launch capable agencies, both commercial and sovereign, and recent well-publicised collisions involving man-made space objects, has further magnified the importance of timely and accurate SSA. The United States Strategic Command (USSTRATCOM) operates the Space Surveillance Network (SSN), a global network of sensors tasked with maintaining SSA. The rapidly increasing number of resident space objects will require commensurate improvements in the SSN. Sensors are scarce resources that must be scheduled judiciously to obtain measurements of maximum utility. Improvements in sensor scheduling and fusion, can serve to reduce the number of additional sensors that may be required. Recently, Hill et al. [1] have proposed and developed a simulation environment named TASMAN (Tasking Autonomous Sensors in a Multiple Application Network) to enable testing of alternative scheduling strategies within a simulated multi-sensor, multi-target environment. TASMAN simulates a high-fidelity, hardware-in-the-loop system by running multiple machines with different roles in parallel. At present, TASMAN is limited to simulations involving electro-optic sensors. Its high fidelity is at once a feature and a limitation, since supercomputing is required to run simulations of appreciable scale. In this paper, we describe an alternative, modular and scalable SSA simulation system that can extend the work of Hill et al with reduced complexity, albeit also with reduced fidelity. The tool has been developed in MATLAB and therefore can be run on a very wide range of computing platforms. It can also make use of MATLAB’s parallel processing capabilities to obtain considerable speed-up. The speed and flexibility so obtained can be used to quickly test scheduling algorithms even with a relatively large number of space objects. We further describe an application of the tool by exploring how the relative mixture of electro-optical and radar sensors can impact the scheduling, fusion and achievable accuracy of an SSA system. By varying the mixture of sensor types, we are able to characterise the main advantages and disadvantages of each configuration.

Region-confined restoration method for motion-blurred star image of the star sensor under dynamic conditions.

PubMed

Ma, Liheng; Bernelli-Zazzera, Franco; Jiang, Guangwen; Wang, Xingshu; Huang, Zongsheng; Qin, Shiqiao

2016-06-10

Under dynamic conditions, the centroiding accuracy of the motion-blurred star image decreases and the number of identified stars reduces, which leads to the degradation of the attitude accuracy of the star sensor. To improve the attitude accuracy, a region-confined restoration method, which concentrates on the noise removal and signal to noise ratio (SNR) improvement of the motion-blurred star images, is proposed for the star sensor under dynamic conditions. A multi-seed-region growing technique with the kinematic recursive model for star image motion is given to find the star image regions and to remove the noise. Subsequently, a restoration strategy is employed in the extracted regions, taking the time consumption and SNR improvement into consideration simultaneously. Simulation results indicate that the region-confined restoration method is effective in removing noise and improving the centroiding accuracy. The identification rate and the average number of identified stars in the experiments verify the advantages of the region-confined restoration method.

Time-Frequency Analyses of Tide-Gauge Sensor Data

PubMed Central

Erol, Serdar

2011-01-01

The real world phenomena being observed by sensors are generally non-stationary in nature. The classical linear techniques for analysis and modeling natural time-series observations are inefficient and should be replaced by non-linear techniques of whose theoretical aspects and performances are varied. In this manner adopting the most appropriate technique and strategy is essential in evaluating sensors’ data. In this study, two different time-series analysis approaches, namely least squares spectral analysis (LSSA) and wavelet analysis (continuous wavelet transform, cross wavelet transform and wavelet coherence algorithms as extensions of wavelet analysis), are applied to sea-level observations recorded by tide-gauge sensors, and the advantages and drawbacks of these methods are reviewed. The analyses were carried out using sea-level observations recorded at the Antalya-II and Erdek tide-gauge stations of the Turkish National Sea-Level Monitoring System. In the analyses, the useful information hidden in the noisy signals was detected, and the common features between the two sea-level time series were clarified. The tide-gauge records have data gaps in time because of issues such as instrumental shortcomings and power outages. Concerning the difficulties of the time-frequency analysis of data with voids, the sea-level observations were preprocessed, and the missing parts were predicted using the neural network method prior to the analysis. In conclusion the merits and limitations of the techniques in evaluating non-stationary observations by means of tide-gauge sensors records were documented and an analysis strategy for the sequential sensors observations was presented. PMID:22163829

Multi-site evaluation of IKONOS data for classification of tropical coral reef environments

USGS Publications Warehouse

Andrefouet, S.; Kramer, Philip; Torres-Pulliza, D.; Joyce, K.E.; Hochberg, E.J.; Garza-Perez, R.; Mumby, P.J.; Riegl, Bernhard; Yamano, H.; White, W.H.; Zubia, M.; Brock, J.C.; Phinn, S.R.; Naseer, A.; Hatcher, B.G.; Muller-Karger, F. E.

2003-01-01

Ten IKONOS images of different coral reef sites distributed around the world were processed to assess the potential of 4-m resolution multispectral data for coral reef habitat mapping. Complexity of reef environments, established by field observation, ranged from 3 to 15 classes of benthic habitats containing various combinations of sediments, carbonate pavement, seagrass, algae, and corals in different geomorphologic zones (forereef, lagoon, patch reef, reef flats). Processing included corrections for sea surface roughness and bathymetry, unsupervised or supervised classification, and accuracy assessment based on ground-truth data. IKONOS classification results were compared with classified Landsat 7 imagery for simple to moderate complexity of reef habitats (5-11 classes). For both sensors, overall accuracies of the classifications show a general linear trend of decreasing accuracy with increasing habitat complexity. The IKONOS sensor performed better, with a 15-20% improvement in accuracy compared to Landsat. For IKONOS, overall accuracy was 77% for 4-5 classes, 71% for 7-8 classes, 65% in 9-11 classes, and 53% for more than 13 classes. The Landsat classification accuracy was systematically lower, with an average of 56% for 5-10 classes. Within this general trend, inter-site comparisons and specificities demonstrate the benefits of different approaches. Pre-segmentation of the different geomorphologic zones and depth correction provided different advantages in different environments. Our results help guide scientists and managers in applying IKONOS-class data for coral reef mapping applications. ?? 2003 Elsevier Inc. All rights reserved.

Inertial sensor self-calibration in a visually-aided navigation approach for a micro-AUV.

PubMed

Bonin-Font, Francisco; Massot-Campos, Miquel; Negre-Carrasco, Pep Lluis; Oliver-Codina, Gabriel; Beltran, Joan P

2015-01-16

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time.

Inertial Sensor Self-Calibration in a Visually-Aided Navigation Approach for a Micro-AUV

PubMed Central

Bonin-Font, Francisco; Massot-Campos, Miquel; Negre-Carrasco, Pep Lluis; Oliver-Codina, Gabriel; Beltran, Joan P.

2015-01-01

This paper presents a new solution for underwater observation, image recording, mapping and 3D reconstruction in shallow waters. The platform, designed as a research and testing tool, is based on a small underwater robot equipped with a MEMS-based IMU, two stereo cameras and a pressure sensor. The data given by the sensors are fused, adjusted and corrected in a multiplicative error state Kalman filter (MESKF), which returns a single vector with the pose and twist of the vehicle and the biases of the inertial sensors (the accelerometer and the gyroscope). The inclusion of these biases in the state vector permits their self-calibration and stabilization, improving the estimates of the robot orientation. Experiments in controlled underwater scenarios and in the sea have demonstrated a satisfactory performance and the capacity of the vehicle to operate in real environments and in real time. PMID:25602263

ABS-FishCount: An Agent-Based Simulator of Underwater Sensors for Measuring the Amount of Fish.

PubMed

García-Magariño, Iván; Lacuesta, Raquel; Lloret, Jaime

2017-11-13

Underwater sensors provide one of the possibilities to explore oceans, seas, rivers, fish farms and dams, which all together cover most of our planet's area. Simulators can be helpful to test and discover some possible strategies before implementing these in real underwater sensors. This speeds up the development of research theories so that these can be implemented later. In this context, the current work presents an agent-based simulator for defining and testing strategies for measuring the amount of fish by means of underwater sensors. The current approach is illustrated with the definition and assessment of two strategies for measuring fish. One of these two corresponds to a simple control mechanism, while the other is an experimental strategy and includes an implicit coordination mechanism. The experimental strategy showed a statistically significant improvement over the control one in the reduction of errors with a large Cohen's d effect size of 2.55.

Smart Sensors: Why and when the origin was and why and where the future will be

NASA Astrophysics Data System (ADS)

Corsi, C.

2013-12-01

Smart Sensors is a technique developed in the 70's when the processing capabilities, based on readout integrated with signal processing, was still far from the complexity needed in advanced IR surveillance and warning systems, because of the enormous amount of noise/unwanted signals emitted by operating scenario especially in military applications. The Smart Sensors technology was kept restricted within a close military environment exploding in applications and performances in the 90's years thanks to the impressive improvements in the integrated signal read-out and processing achieved by CCD-CMOS technologies in FPA. In fact the rapid advances of "very large scale integration" (VLSI) processor technology and mosaic EO detector array technology allowed to develop new generations of Smart Sensors with much improved signal processing by integrating microcomputers and other VLSI signal processors. inside the sensor structure achieving some basic functions of living eyes (dynamic stare, non-uniformity compensation, spatial and temporal filtering). New and future technologies (Nanotechnology, Bio-Organic Electronics, Bio-Computing) are lightning a new generation of Smart Sensors extending the Smartness from the Space-Time Domain to Spectroscopic Functional Multi-Domain Signal Processing. History and future forecasting of Smart Sensors will be reported.

East Asian Haze

NASA Technical Reports Server (NTRS)

2002-01-01

Korea and the Sea of Japan are obscured by swirls of pollution in this image taken by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) on November 23, 2001. Image courtesy the SeaWiFS Project, NASA/Goddard Space Flight Center, and ORBIMAGE

Potential inundated coastal area estimation in Shanghai with multi-platform SAR and altimetry data

NASA Astrophysics Data System (ADS)

Ma, Guanyu; Yang, Tianliang; Zhao, Qing; Kubanek, Julia; Pepe, Antonio; Dong, Hongbin; Sun, Zhibin

2017-09-01

As global warming problem is becoming serious in recent decades, the global sea level is continuously rising. This will cause damages to the coastal deltas with the characteristics of low-lying land, dense population, and developed economy. Continuously reclamation costal intertidal and wetland areas are making Shanghai, the mega city of Yangtze River Delta, more vulnerable to sea level rise. In this paper, we investigate the land subsidence temporal evolution of patterns and processes on a stretch of muddy coast located between the Yangtze River Estuary and Hangzou Bay with differential synthetic aperture radar interferometry (DInSAR) analyses. By exploiting a set of 31 SAR images acquired by the ENVISAT/ASAR from February 2007 to May 2010 and a set of 48 SAR images acquired by the COSMO-SkyMed (CSK) sensors from December 2013 to March 2016, coherent point targets as long as land subsidence velocity maps and time series are identified by using the Small Baseline Subset (SBAS) algorithm. With the DInSAR constrained land subsidence model, we predict the land subsidence trend and the expected cumulative subsidence in 2020, 2025 and 2030. Meanwhile, we used altimetrydata and densely distributed in the coastal region are identified (EEMD) algorithm to obtain the average sea level rise rate in the East China Sea. With the land subsidence predictions, sea level rise predictions, and high-precision digital elevation model (DEM), we analyze the combined risk of land subsidence and sea level rise on the coastal areas of Shanghai. The potential inundated areas are mapped under different scenarios.

Integration of an Emerging Highly Sensitive Optical CO2 Sensor for Ocean Monitoring on an Existing Data Acquisition System SeaKeeper 1000 (trademark)

DTIC Science & Technology

2012-09-30

be deployed in geat numbers to autonomously monitor the overall patterns of CO2 emissions and ocean acidification . OBJECTIVES  Meet the...Integration of an Emerging Highly Sensitive Optical CO2 Sensor for Ocean Monitoring on an Existing Data Acquisition System SeaKeeper 1000TM Annual...challenging requirements for ocean pCO2 monitoring using an innovative sensor design based on high sensitivity fluorescence detection.  Assemble the system

Integration of an Emerging Highly Sensitive Optical CO2 Sensor for Ocean Monitoring on an Existing Data Acquisition System SeaKeeper 1000(TM)

DTIC Science & Technology

2011-09-30

be deployed in geat numbers to autonomously monitor the overall patterns of CO2 emissions and ocean acidification . OBJECTIVES  Meet the...Integration of an Emerging Highly Sensitive Optical CO2 Sensor for Ocean Monitoring on an Existing Data Acquisition System SeaKeeper 1000TM Annual...challenging requirements for ocean pCO2 monitoring using an innovative sensor design based on high sensitivity fluorescence detection.  Assemble the system

The ODAS Italia 1 buoy: More than forty years of activity in the Ligurian Sea

NASA Astrophysics Data System (ADS)

Canepa, Elisa; Pensieri, Sara; Bozzano, Roberto; Faimali, Marco; Traverso, Pierluigi; Cavaleri, Luigi

2015-06-01

The Ligurian Sea plays a relevant role in driving both the circulation of the Western Mediterranean Sea and the weather and climate of the area. In order to better understand the peculiarities of this basin, the Oceanographic Data Acquisition System (ODAS) Italia 1 buoy was developed and deployed in the early '70s. Throughout the years, the buoy has been fitted with updated measuring and data acquiring systems. Since 2003 the buoy has been part of the Mediterranean Moored Multi-sensor Array network of fixed open ocean observatories with the W1-M3A identifier and presently constitutes one of the Mediterranean sites of the European FixO3 network. Recently, a deep-ocean sub-surface mooring line was, and is, deployed close to it in relation to specific projects. This multidisciplinary observing system is able to perform both long-term operational and ad-hoc monitoring from the lower atmosphere to the deep ocean. It is used for analysis of air-sea interaction processes, study of the physical proprieties of the water column, bio-geo-chemical monitoring of the sea, meteorological and oceanographic model evaluation, calibration of remotely sensed measurements, and development of innovative marine monitoring technologies. After reporting some historical notes and the description of the observing system, this paper summarises and reviews the main oceanographic and atmospheric studies performed during the last 15 years using the data acquired on board.

Enhancing the capability of the research fleet.

NASA Astrophysics Data System (ADS)

Pinkel, R.

2012-12-01

While the performance and economics of our vessels and manned platforms are fixed by fundamental principles, their scientific capabilities can be considerably extended through the development of new technology. Potential future systems include multi-beam swath- mapping sonars for 3-D imaging of plankton patchiness, wire-guided profiling velocity sensors for establishing full-ocean-depth velocity profiles, shipboard HF radar (CODAR) for mapping energetic currents, and shipboard Doppler radar for mapping the surface wave spectrum. Research vessel users should have access to undersea gliders and autonomous aircraft as well as the current AUVs. In addition, the use of manned stable platforms in an observatory setting deserves further consideration. As well as providing an ideal mount for meteorological and oceanographic sensors, the platforms can provide electrical power and a "heavy lift" capability for sea floor and water column studies. Concerted community effort will be required to develop these new technologies, not all of which will be commercially viable. A strong academic technology base is necessary.

Waveform identification and retracking analyses of Jason-2 altimeter satellite data for improving sea surface height estimation in Southern Java Island Waters and Java Sea, Indonesia

NASA Astrophysics Data System (ADS)

Nababan, Bisman; Hakim, Muhammad R.; Panjaitan, James P.

2018-05-01

Indonesian waters containing many small islands and shallow waters leads to a less accurate of sea surface height (SSH) estimation from satellite altimetry. Little efforts are also given for the validation of SSH estimation from the satellite in Indonesian waters. The purpose of this research was to identify and retrack waveforms of Jason-2 altimeter satellite data in southern Java island waters and Java Sea using several retrackers and performed improvement percentage analyses for new SSH estimation. The study used data of the Sensor Geophysical Data Record type D (SGDR-D) of Jason-2 satellite altimeter of the year 2010 in the southern Java island waters and 2012-2014 in Java Sea. Waveform retracking analyses were conducted using several retrackers (Offset Center of Gravity, Ice, Threshold, and Improved Threshold) and examined using a world reference undulation geoid of EGM08 and Oceanic retracker. Result showed that shape and pattern of waveforms were varied in all passes, seasons, and locations specifically along the coastal regions. In general, non-Brownish and complex waveforms were identified along coastal region specifically within the distance of 0-10 km from the shoreline. In contrary, generally Brownish waveforms were found in offshore. However, Brownish waveform can also be found within coastal region and non-Brownish waveforms within offshore region. The results were also showed that the four retrackers produced a better SSH estimation in coastal region. However, there was no dominant retracker to improve the accuracy of the SSH estimate.

SeaWiFS technical report series. Volume 25: Ocean optics protocols for SeaWiFS validation, revision 1

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Acker, James G. (Editor); Mueller, James L.; Austin, Roswell W.

1995-01-01

This report presents protocols for measuring optical properties, and other environmental variables, to validate the radiometric performance of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and to develop and validate bio-optical algorithms for use with SeaWiFS data. The protocols are intended to establish foundations for a measurement strategy to verify the challenging SeaWiFS uncertainty goals of 5 percent in water-leaving radiances and 35 percent in chlorophyll alpha concentration. The protocols first specify the variables which must be measured, and briefly review the rationale for measuring each variable. Subsequent chapters cover detailed protocols for instrument performance specifications, characterizing and calibrating instruments, methods of making measurements in the field, and methods of data analysis. These protocols were developed at a workshop sponsored by the SeaWiFS Project Office (SPO) and held at the Naval Postgraduate School in Monterey, California (9-12 April 1991). This report began as the proceedings of the workshop, as interpreted and expanded by the authors and reviewed by workshop participants and other members of the bio-optical research community. The protocols are an evolving prescription to allow the research community to approach the unprecedented measurement uncertainties implied by the SeaWiFS goals; research and development are needed to improve the state-of-the-art in specific areas. These protocols should be periodically revised to reflect technical advances during the SeaWiFS Project cycle. The present edition (Revision 1) incorporates new protocols in several areas, including expanded protocol descriptions for Case-2 waters and other improvements, as contributed by several members of the SeaWiFS Science Team.

A multi-core fiber based interferometer for high temperature sensing

NASA Astrophysics Data System (ADS)

Zhou, Song; Huang, Bo; Shu, Xuewen

2017-04-01

In this paper, we have verified and implemented a Mach-Zehnder interferometer based on seven-core fiber for high temperature sensing application. This proposed structure is based on a multi-mode-multi-core-multi-mode fiber structure sandwiched by a single mode fiber. Between the single-mode and multi-core fiber, a 3 mm long multi-mode fiber is formed for lead-in and lead-out light. The basic operation principle of this device is the use of multi-core modes, single-mode and multi-mode interference coupling is also utilized. Experimental results indicate that this interferometer sensor is capable of accurate measurements of temperatures up to 800 °C, and the temperature sensitivity of the proposed sensor is as high as 170.2 pm/°C, which is much higher than the current existing MZI based temperature sensors (109 pm/°C). This type of sensor is promising for practical high temperature applications due to its advantages including high sensitivity, simple fabrication process, low cost and compactness.

Design and evaluation of a sensor fail-operational control system for a digitally controlled turbofan engine

NASA Technical Reports Server (NTRS)

Hrach, F. J.; Arpasi, D. J.; Bruton, W. M.

1975-01-01

A self-learning, sensor fail-operational, control system for the TF30-P-3 afterburning turbofan engine was designed and evaluated. The sensor fail-operational control system includes a digital computer program designed to operate in conjunction with the standard TF30-P-3 bill-of-materials control. Four engine measurements and two compressor face measurements are tested. If any engine measurements are found to have failed, they are replaced by values synthesized from computer-stored information. The control system was evaluated by using a realtime, nonlinear, hybrid computer engine simulation at sea level static condition, at a typical cruise condition, and at several extreme flight conditions. Results indicate that the addition of such a system can improve the reliability of an engine digital control system.

Multi-azimuth 3D Seismic Exploration and Processing in the Jeju Basin, the Northern East China Sea

NASA Astrophysics Data System (ADS)

Yoon, Youngho; Kang, Moohee; Kim, Jin-Ho; Kim, Kyong-O.

2015-04-01

Multi-azimuth(MAZ) 3D seismic exploration is one of the most advanced seismic survey methods to improve illumination and multiple attenuation for better image of the subsurface structures. 3D multi-channel seismic data were collected in two phases during 2012, 2013, and 2014 in Jeju Basin, the northern part of the East China Sea Basin where several oil and gas fields were discovered. Phase 1 data were acquired at 135° and 315° azimuths in 2012 and 2013 comprised a full 3D marine seismic coverage of 160 km2. In 2014, phase 2 data were acquired at the azimuths 45° and 225°, perpendicular to those of phase 1. These two datasets were processed through the same processing workflow prior to velocity analysis and merged to one MAZ dataset. We performed velocity analysis on the MAZ dataset as well as two phases data individually and then stacked these three datasets separately. We were able to pick more accurate velocities in the MAZ dataset compare to phase 1 and 2 data while velocity picking. Consequently, the MAZ seismic volume provide us better resolution and improved images since different shooting directions illuminate different parts of the structures and stratigraphic features.

Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility

PubMed Central

Jin, Yichao; Vural, Serdar; Gluhak, Alexander; Moessner, Klaus

2013-01-01

This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines. PMID:24135992

Performance Evaluation of Fusing Protected Fingerprint Minutiae Templates on the Decision Level

PubMed Central

Yang, Bian; Busch, Christoph; de Groot, Koen; Xu, Haiyun; Veldhuis, Raymond N. J.

2012-01-01

In a biometric authentication system using protected templates, a pseudonymous identifier is the part of a protected template that can be directly compared. Each compared pair of pseudonymous identifiers results in a decision testing whether both identifiers are derived from the same biometric characteristic. Compared to an unprotected system, most existing biometric template protection methods cause to a certain extent degradation in biometric performance. Fusion is therefore a promising way to enhance the biometric performance in template-protected biometric systems. Compared to feature level fusion and score level fusion, decision level fusion has not only the least fusion complexity, but also the maximum interoperability across different biometric features, template protection and recognition algorithms, templates formats, and comparison score rules. However, performance improvement via decision level fusion is not obvious. It is influenced by both the dependency and the performance gap among the conducted tests for fusion. We investigate in this paper several fusion scenarios (multi-sample, multi-instance, multi-sensor, multi-algorithm, and their combinations) on the binary decision level, and evaluate their biometric performance and fusion efficiency on a multi-sensor fingerprint database with 71,994 samples. PMID:22778583

Hierarchical inorganic-organic multi-shell nanospheres for intervention and treatment of lead-contaminated blood

NASA Astrophysics Data System (ADS)

Khairy, Mohamed; El-Safty, Sherif A.; Shenashen, Mohamed. A.; Elshehy, Emad A.

2013-08-01

The highly toxic properties, bioavailability, and adverse effects of Pb2+ species on the environment and living organisms necessitate periodic monitoring and removal whenever possible of Pb2+ concentrations in the environment. In this study, we designed a novel optical multi-shell nanosphere sensor that enables selective recognition, unrestrained accessibility, continuous monitoring, and efficient removal (on the order of minutes) of Pb2+ ions from water and human blood, i.e., red blood cells (RBCs). The consequent decoration of the mesoporous core/double-shell silica nanospheres through a chemically responsive azo-chromophore with a long hydrophobic tail enabled us to create a unique hierarchical multi-shell sensor. We examined the efficiency of the multi-shell sensor in removing lead ions from the blood to ascertain the potential use of the sensor in medical applications. The lead-induced hemolysis of RBCs in the sensing/capture assay was inhibited by the ability of the hierarchical sensor to remove lead ions from blood. The results suggest the higher flux and diffusion of Pb2+ ions into the mesopores of the core/multi-shell sensor than into the RBC membranes. These findings indicate that the sensor could be used in the prevention of health risks associated with elevated blood lead levels such as anemia.The highly toxic properties, bioavailability, and adverse effects of Pb2+ species on the environment and living organisms necessitate periodic monitoring and removal whenever possible of Pb2+ concentrations in the environment. In this study, we designed a novel optical multi-shell nanosphere sensor that enables selective recognition, unrestrained accessibility, continuous monitoring, and efficient removal (on the order of minutes) of Pb2+ ions from water and human blood, i.e., red blood cells (RBCs). The consequent decoration of the mesoporous core/double-shell silica nanospheres through a chemically responsive azo-chromophore with a long hydrophobic tail enabled us to create a unique hierarchical multi-shell sensor. We examined the efficiency of the multi-shell sensor in removing lead ions from the blood to ascertain the potential use of the sensor in medical applications. The lead-induced hemolysis of RBCs in the sensing/capture assay was inhibited by the ability of the hierarchical sensor to remove lead ions from blood. The results suggest the higher flux and diffusion of Pb2+ ions into the mesopores of the core/multi-shell sensor than into the RBC membranes. These findings indicate that the sensor could be used in the prevention of health risks associated with elevated blood lead levels such as anemia. Electronic supplementary information (ESI) available: The experimental procedures for synthesis of AC-LHT, mesoporous core/double shell silica, and optical core/multi-shell sensors. The adsorption capacity, optical recognition of Pb ions, colorimetric response of Pb ions in ethanol medium, Langmuir adsorption isotherm and reusability of captor are addressed. See DOI: 10.1039/c3nr02403b

Survey of Fire Detection Technologies and System Evaluation/Certification Methodologies and Their Suitability for Aircraft Cargo Compartments

NASA Technical Reports Server (NTRS)

Cleary, T.; Grosshandler, W.

1999-01-01

As part of the National Aeronautics and Space Administration (NASA) initiated program on global civil aviation, NIST is assisting Federal Aviation Administration in its research to improve fire detection in aircraft cargo compartments. Aircraft cargo compartment detection certification methods have been reviewed. The Fire Emulator-Detector Evaluator (FE/DE) has been designed to evaluate fire detection technologies such as new sensors, multi-element detectors, and detectors that employ complex algorithms. The FE/DE is a flow tunnel that can reproduce velocity, temperature, smoke, and Combustion gas levels to which a detector might be exposed during a fire. A scientific literature survey and patent search have been conducted relating to existing and emerging fire detection technologies, and the potential use of new fire detection strategies in cargo compartment areas has been assessed. In the near term, improved detector signal processing and multi-sensor detectors based on combinations of smoke measurements, combustion gases and temperature are envisioned as significantly impacting detector system performance.

Wearable Wireless Sensor for Multi-Scale Physiological Monitoring

DTIC Science & Technology

2013-10-01

AD_________________ Award Number: W81XWH-12-1-0541 TITLE: Wearable Wireless Sensor for Multi-Scale...TYPE Annual 3. DATES COVERED 25 12- 13 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Wearable Wireless Sensor for Multi-Scale Physiological...peripheral management • Procedures for low power mode activation and wake - up • Routines for start- up state detection • Flash memory management

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

PubMed

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Performance and utility of satellite telemetry during field studies of free-ranging polar bears in Alaska

USGS Publications Warehouse

Garner, Gerald W.; Amstrup, Steven C.; Douglas, David C.; Gardner, Craig L.; Amlaner, Charles J.

1989-01-01

Satellite telemetry technology has been used during field studies of polar bears in Alaska since 1985. A total of 109 Platform Transmitter Terminals (PTT) have been deployed on free-ranging female polar bears that seasonally inhabit waters adjacent to the Alaskan coast. The PTTs transmitted locational and sensor data to TIROS-N polar-orbiting satellites during a duty cycle of 12 hours on/60 hours off in 1985, 1986, and 1987. Expected battery life was 13.8 months, and collars were normally removed and replaced with new or refurbished PTTs at 11-13 month intervals. Duty cycles were altered to 7-8 hours on/64-65 hours off in 1988 to prolong expected battery life to 19-21 months. Sensor data transmitted included PTT internal temperature, short term activity counts recorded at 60 second intervals, and long term activity counts for the preceding 24 or 72-hour period. Early failures of PTTs to fix location (less than 75% of expected battery life) were as high as 53% during 198501986. Subsequent improvements in battery design, including better shock insulation, improved electronic, and an improved battery system have reduced early failures to 27% in 1987-1988. The harsh environment and the degree of abuse observed in recovered collars indicate that an unavoidable failure rate of 8-10% is inherent within 60 days after deployment on polar bears. A total of 18,000 locations and 201,000 sensor messages were received from female polar bears between May 1985 and June 1988. Polar bears that were marked in Alaskan waters have been located as far south as 60°N 168°W, and as far east as 70°N 127°W in the Beaufort Sea. Polar bears in the Beaufort Sea are shared with Canada, while polar bears in the Chukchi and Bering seas are shared with the Soviet Union. The international ranges of the two hypothesized populations have been documented. Satellite telemetry has detailed the large movement patterns of polar bear over these vast areas that were previously not available using other techniques.

Analysis of RFI Statistics for Aquarius RFI Detection and Mitigation Improvements

NASA Technical Reports Server (NTRS)

de Matthaeis, Paolo; Soldo, Yan; Le Vine, David M.

2016-01-01

Aquarius is an L-band active/passive sensor designed to globally map sea surface salinity from space. Two instruments, a radar scatterometer and a radiometer, observe the same surface footprint almost simultaneously. The radiometer is the primary instrument for sensing sea surface salinity (SSS), while the scatterometer is included to provide a correction for sea surface roughness, which is a primary source of error in the salinity retrieval. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. An important feature of the data processing includes detection and mitigation of Radio Frequency Interference (RFI) which is done separately for both active and passive instruments. Correcting for RFI is particularly critical over ocean because of the high accuracy required in the brightness temperature measurements for SSS retrieval. It is also necessary for applications of the Aquarius data over land, where man-made interference is widespread, even though less accuracy is required in this case. This paper will provide an overview of the current status of the Aquarius RFI processing and an update on the ongoing work on the improvement of the RFI detection and mitigation performance.

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments.

PubMed

Roy, Nirmalya; Misra, Archan; Cook, Diane

2016-02-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional 'hidden' context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions.

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments

PubMed Central

Misra, Archan; Cook, Diane

2016-01-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional ‘hidden’ context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions. PMID:27042240

A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems

PubMed Central

Park, Kyeonghwan; Kim, Seung Mok; Eom, Won-Jin; Kim, Jae Joon

2017-01-01

This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC) for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR) of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS) process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors. PMID:28368355

A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems.

PubMed

Park, Kyeonghwan; Kim, Seung Mok; Eom, Won-Jin; Kim, Jae Joon

2017-04-03

This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC) for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR) of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS) process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors.

Modeling Primary Productivity in the Margin Ice Zone from Glider-Based Measurements of Chlorophyll and Light during the 2014 Miz Program

NASA Astrophysics Data System (ADS)

Perry, M. J.; Lee, C.; Rainville, L.; Cetinic, I.; Yang, E. J.; Kang, S. H.

2016-02-01

In late summer 2014 during the Marginal Ice Zone (MIZ) Experiment, an international project sponsored by ONR, four Seagliders transited open water, through the marginal ice zone, and under ice-covered regions in the Beaufort Sea, penetrating as far as 100 km into the ice pack. The gliders navigated either by GPS in open water or, when under the ice, by acoustics from sound sources embedded in the MIZ autonomous observing array. The glider sensor suite included temperature, temperature microstructure, salinity, oxygen, chlorophyll fluorescence, optical backscatter, and multi-spectral downwelling irradiance. Cruises on the IBRV Araon operating in the open Beaufort Sea and on the R/V Ukpik and Norseman operating in continental shelf waters off Alaska's north slope allowed us to construct proxy libraries for converting chlorophyll fluorescence to chlorophyll concentration and optical backscatter to particulate organic carbon concentration. Water samples were collected for chlorophyll and particulate organic carbon analysis on the cruises and aligned with optical profiles of fluorescence and backscatter using sensors that were factory calibrated at the same time as the glider sensors. Fields of chlorophyll, particulate organic carbon, light, and primary productivity are constructed from the glider data. Productivity is modeled as a function of chlorophyll and light, using photosynthesis-light (PE) models with available PE parameters from Arctic measurements. During August the region under the ice was characterized by a deep chlorophyll maximum layer with low rates of production in overlying waters. A phytoplankton bloom developed in open water at the end of September, preceding the rapid reformation of ice, despite shorter days and reduce irradiation.

A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

PubMed

Chi, Taiyun; Park, Jong Seok; Butts, Jessica C; Hookway, Tracy A; Su, Amy; Zhu, Chengjie; Styczynski, Mark P; McDevitt, Todd C; Wang, Hua

2015-12-01

In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 μm × 100 μm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.

An overview of the SeaWiFS project and strategies for producing a climate research quality global ocean bio-optical time series

NASA Astrophysics Data System (ADS)

McClain, Charles R.; Feldman, Gene C.; Hooker, Stanford B.

2004-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project Office was formally initiated at the NASA Goddard Space Flight Center in 1990. Seven years later, the sensor was launched by Orbital Sciences Corporation under a data-buy contract to provide 5 years of science quality data for global ocean biogeochemistry research. To date, the SeaWiFS program has greatly exceeded the mission goals established over a decade ago in terms of data quality, data accessibility and usability, ocean community infrastructure development, cost efficiency, and community service. The SeaWiFS Project Office and its collaborators in the scientific community have made substantial contributions in the areas of satellite calibration, product validation, near-real time data access, field data collection, protocol development, in situ instrumentation technology, operational data system development, and desktop level-0 to level-3 processing software. One important aspect of the SeaWiFS program is the high level of science community cooperation and participation. This article summarizes the key activities and approaches the SeaWiFS Project Office pursued to define, achieve, and maintain the mission objectives. These achievements have enabled the user community to publish a large and growing volume of research such as those contributed to this special volume of Deep-Sea Research. Finally, some examples of major geophysical events (oceanic, atmospheric, and terrestrial) captured by SeaWiFS are presented to demonstrate the versatility of the sensor.

Evaluation of radiative fluxes over the north Indian Ocean

NASA Astrophysics Data System (ADS)

Ramesh Kumar, M. R.; Pinker, Rachel T.; Mathew, Simi; Venkatesan, R.; Chen, W.

2018-05-01

Radiative fluxes are a key component of the surface heat budget of the oceans. Yet, observations over oceanic region are sparse due to the complexity of radiation measurements; moreover, certain oceanic regions are substantially under-sampled, such as the north Indian Ocean. The National Institute of Ocean Technology, Chennai, India, under its Ocean Observation Program has deployed an Ocean Moored Network for the Northern Indian Ocean (OMNI) both in the Arabian Sea and the Bay of Bengal. These buoys are equipped with sensors to measure radiation and rainfall, in addition to other basic meteorological parameters. They are also equipped with sensors to measure sub-surface currents, temperature, and conductivity from the surface up to a depth of 500 m. Observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the National Aeronautics and Space Administration (NASA) AQUA and TERRA satellites have been used to infer surface radiation over the north Indian Ocean. In this study, we focus only on the shortwave (SW↓) fluxes. The evaluations of the MODIS-based SW↓ fluxes against the RAMA observing network have shown a very good agreement between them, and therefore, we use the MODIS-derived fluxes as a reference for the evaluation of the OMNI observations. In an early deployment of the OMNI buoys, the radiation sensors were placed at 2 m above the sea surface; subsequently, the height of the sensors was raised to 3 m. In this study, we show that there was a substantial improvement in the agreement between the buoy observations and the satellite estimates, once the sensors were raised to higher levels. The correlation coefficient increased from 0.87 to 0.93, and both the bias and standard deviations decreased substantially.

Metal Oxide Gas Sensor Drift Compensation Using a Two-Dimensional Classifier Ensemble

PubMed Central

Liu, Hang; Chu, Renzhi; Tang, Zhenan

2015-01-01

Sensor drift is the most challenging problem in gas sensing at present. We propose a novel two-dimensional classifier ensemble strategy to solve the gas discrimination problem, regardless of the gas concentration, with high accuracy over extended periods of time. This strategy is appropriate for multi-class classifiers that consist of combinations of pairwise classifiers, such as support vector machines. We compare the performance of the strategy with those of competing methods in an experiment based on a public dataset that was compiled over a period of three years. The experimental results demonstrate that the two-dimensional ensemble outperforms the other methods considered. Furthermore, we propose a pre-aging process inspired by that applied to the sensors to improve the stability of the classifier ensemble. The experimental results demonstrate that the weight of each multi-class classifier model in the ensemble remains fairly static before and after the addition of new classifier models to the ensemble, when a pre-aging procedure is applied. PMID:25942640

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Extratropical Influence of Sea Surface Temperature and Wind on Water Recycling Rate Over Oceans and Coastal Lands

NASA Technical Reports Server (NTRS)

Hu, Hua; Liu, W. Timothy

1999-01-01

Water vapor and precipitation are two important parameters confining the hydrological cycle in the atmosphere and over the ocean surface. In the extratropical areas, due to variations of midlatitude storm tracks and subtropical jetstreams, water vapor and precipitation have large variability. Recently, a concept of water recycling rate defined previously by Chahine et al. (GEWEX NEWS, August, 1997) has drawn increasing attention. The recycling rate of moisture is calculated as the ratio of precipitation to total precipitable water (its inverse is the water residence time). In this paper, using multi-sensor spacebased measurements we will study the role of sea surface temperature and ocean surface wind in determining the water recycling rate over oceans and coastal lands. Response of water recycling rate in midlatitudes to the El Nino event will also be discussed. Sea surface temperature data are derived from satellite observations from the Advanced Very High Resolution Radiometer (AVHRR) blended with in situ measurements, available for the period 1982-1998. Global sea surface wind observations are obtained from spaceborne scatterometers aboard on the European Remote-Sensing Satellite (ERS1 and 2), available for the period 1991-1998. Global total precipitable water provided by the NASA Water Vapor Project (NVAP) is available for the period 1988-1995. Global monthly mean precipitation provided by the Global Precipitation Climatology Project (GPCP) is available for the period 1987-1998.

Velocity Profile measurements in two-phase flow using multi-wave sensors

NASA Astrophysics Data System (ADS)

Biddinika, M. K.; Ito, D.; Takahashi, H.; Kikura, H.; Aritomi, M.

2009-02-01

Two-phase flow has been recognized as one of the most important phenomena in fluid dynamics. In addition, gas-liquid two-phase flow appears in various industrial fields such as chemical industries and power generations. In order to clarify the flow structure, some flow parameters have been measured by using many effective measurement techniques. The velocity profile as one of the important flow parameter, has been measured by using ultrasonic velocity profile (UVP) technique. This technique can measure velocity distributions along a measuring line, which is a beam formed by pulse ultrasounds. Furthermore, a multi-wave sensor can measure the velocity profiles of both gas and liquid phase using UVP method. In this study, two types of multi-wave sensors are used. A sensor has cylindrical shape, and another one has square shape. The piezoelectric elements of each sensor have basic frequencies of 8 MHz for liquid phase and 2 MHz for gas phase, separately. The velocity profiles of air-water bubbly flow in a vertical rectangular channel were measured by using these multi-wave sensors, and the validation of the measuring accuracy was performed by the comparison between the velocity profiles measured by two multi-wave sensors.

Combining engineered cell-sensors with multi-agent systems to realize smart environment

NASA Astrophysics Data System (ADS)

Chen, Mei

2013-03-01

The connection of everything in a sensory and an intelligent way is a pursuit in smart environment. This paper introduces the engineered cell-sensors into the multi-agent systems to realize the smart environment. The seamless interface with the natural environment and strong information-processing ability of cell with the achievements of synthetic biology make the construction of engineered cell-sensors possible. However, the engineered cell-sensors are only simple-functional and unreliable computational entities. Therefore how to combine engineered cell-sensors with digital device is a key problem in order to realize the smart environment. We give the abstract structure and interaction modes of the engineered cell-sensors in order to introduce engineered cell-sensors into multi-agent systems. We believe that the introduction of engineered cell-sensors will push forward the development of the smart environment.

Multi-capillary based optical sensors for highly sensitive protein detection

NASA Astrophysics Data System (ADS)

Okuyama, Yasuhira; Katagiri, Takashi; Matsuura, Yuji

2017-04-01

A fluorescence measuring method based on glass multi-capillary for detecting trace amounts of proteins is proposed. It promises enhancement of sensitivity due to effects of the adsorption area expansion and the longitudinal excitation. The sensitivity behavior of this method was investigated by using biotin-streptavidin binding. According to experimental examinations, it was found that the sensitivity was improved by a factor of 70 from common glass wells. We also confirmed our measuring system could detect 1 pg/mL of streptavidin. These results suggest that multi-capillary has a potential as a high-sensitive biosensor.

Powering embedded electronics for wind turbine monitoring using multi-source energy harvesting techniques

NASA Astrophysics Data System (ADS)

Anton, S. R.; Taylor, S. G.; Raby, E. Y.; Farinholt, K. M.

2013-03-01

With a global interest in the development of clean, renewable energy, wind energy has seen steady growth over the past several years. Advances in wind turbine technology bring larger, more complex turbines and wind farms. An important issue in the development of these complex systems is the ability to monitor the state of each turbine in an effort to improve the efficiency and power generation. Wireless sensor nodes can be used to interrogate the current state and health of wind turbine structures; however, a drawback of most current wireless sensor technology is their reliance on batteries for power. Energy harvesting solutions present the ability to create autonomous power sources for small, low-power electronics through the scavenging of ambient energy; however, most conventional energy harvesting systems employ a single mode of energy conversion, and thus are highly susceptible to variations in the ambient energy. In this work, a multi-source energy harvesting system is developed to power embedded electronics for wind turbine applications in which energy can be scavenged simultaneously from several ambient energy sources. Field testing is performed on a full-size, residential scale wind turbine where both vibration and solar energy harvesting systems are utilized to power wireless sensing systems. Two wireless sensors are investigated, including the wireless impedance device (WID) sensor node, developed at Los Alamos National Laboratory (LANL), and an ultra-low power RF system-on-chip board that is the basis for an embedded wireless accelerometer node currently under development at LANL. Results indicate the ability of the multi-source harvester to successfully power both sensors.

Intensive time series data exploitation: the Multi-sensor Evolution Analysis (MEA) platform

NASA Astrophysics Data System (ADS)

Mantovani, Simone; Natali, Stefano; Folegani, Marco; Scremin, Alessandro

2014-05-01

The monitoring of the temporal evolution of natural phenomena must be performed in order to ensure their correct description and to allow improvements in modelling and forecast capabilities. This assumption, that is obvious for ground-based measurements, has not always been true for data collected through space-based platforms: except for geostationary satellites and sensors, that allow providing a very effective monitoring of phenomena with geometric scale from regional to global; smaller phenomena (with characteristic dimension lower than few kilometres) have been monitored with instruments that could collect data only with a time interval in the order of several days; bi-temporal techniques have been the most used ones for years, in order to characterise temporal changes and try identifying specific phenomena. The more the number of flying sensor has grown and their performance improved, the more their capability of monitoring natural phenomena at a smaller geographic scale has grown: we can now count on tenth of years of remotely sensed data, collected by hundreds of sensors that are now accessible from a wide users' community, and the techniques for data processing have to be adapted to move toward a data intensive exploitation. Starting from 2008, the European Space Agency has initiated the development of the Multi-sensor Evolution Analysis (MEA) platform (https://mea.eo.esa.int), whose first aim was to permit the access and exploitation of long term remotely sensed satellite data from different platforms: 15 years of global (A)ATSR data together with 5 years of regional AVNIR-2 data were loaded into the system and were used, through a web-based graphic user interface, for land cover change analysis. The MEA data availability has grown during years integrating multi-disciplinary data that feature spatial and temporal dimensions: so far tenths of Terabytes of data in the land and atmosphere domains are available and can be visualized and exploited, keeping the time dimension as the most relevant one (https://mea.eo.esa.int/data_availability.html). MEA is also used as Climate Data gateway in the framework of the FP7 EarthServer Project. In the present work, principles of the MEA platform are presented, emphasizing the general concept and the methods that have been implemented for data access (including OGC standard data access) and exploitation. In order to show its effectiveness, use cases focused on multi-field and multi-temporal data analysis are shown.

Improving PERSIANN-CCS rain estimation using probabilistic approach and multi-sensors information

NASA Astrophysics Data System (ADS)

Karbalaee, N.; Hsu, K. L.; Sorooshian, S.; Kirstetter, P.; Hong, Y.

2016-12-01

This presentation discusses the recent implemented approaches to improve the rainfall estimation from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Cloud Classification System (PERSIANN-CCS). PERSIANN-CCS is an infrared (IR) based algorithm being integrated in the IMERG (Integrated Multi-Satellite Retrievals for the Global Precipitation Mission GPM) to create a precipitation product in 0.1x0.1degree resolution over the chosen domain 50N to 50S every 30 minutes. Although PERSIANN-CCS has a high spatial and temporal resolution, it overestimates or underestimates due to some limitations.PERSIANN-CCS can estimate rainfall based on the extracted information from IR channels at three different temperature threshold levels (220, 235, and 253k). This algorithm relies only on infrared data to estimate rainfall indirectly from this channel which cause missing the rainfall from warm clouds and false estimation for no precipitating cold clouds. In this research the effectiveness of using other channels of GOES satellites such as visible and water vapors has been investigated. By using multi-sensors the precipitation can be estimated based on the extracted information from multiple channels. Also, instead of using the exponential function for estimating rainfall from cloud top temperature, the probabilistic method has been used. Using probability distributions of precipitation rates instead of deterministic values has improved the rainfall estimation for different type of clouds.

Advances in Rotational Seismic Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pierson, Robert; Laughlin, Darren; Brune, Robert

2016-10-19

Rotational motion is increasingly understood to be a significant part of seismic wave motion. Rotations can be important in earthquake strong motion and in Induced Seismicity Monitoring. Rotational seismic data can also enable shear selectivity and improve wavefield sampling for vertical geophones in 3D surveys, among other applications. However, sensor technology has been a limiting factor to date. The US Department of Energy (DOE) and Applied Technology Associates (ATA) are funding a multi-year project that is now entering Phase 2 to develop and deploy a new generation of rotational sensors for validation of rotational seismic applications. Initial focus is onmore » induced seismicity monitoring, particularly for Enhanced Geothermal Systems (EGS) with fracturing. The sensors employ Magnetohydrodynamic (MHD) principles with broadband response, improved noise floors, robustness, and repeatability. This paper presents a summary of Phase 1 results and Phase 2 status.« less

Bridging the divide between theory and guidance in strategic environmental assessment: A path for Italian regions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baresi, Umberto, E-mail: u.baresi@uq.edu.au

Clear and effective legislation is a requisite to bring sustainable development from theory into practice. This paper develops a methodology to investigate how Italian regional legislation disciplines the use of Strategic Environmental Assessment (SEA), the procedure used in the European Union (EU) to pursue sustainable development of policies, plans, and programs (PPPs). Our case study is the Italian regional level, examined to identify eventual flaws and areas for improvement for each regional legislative framework. For this purpose, this study refers to a selection of analytical criteria recurring in the international debate on sustainability assessments. Statistical multi-dimensional analysis is used tomore » identify Italian regions with similar SEA legislation. We recognize four taxonomies, depending on the way regional legislation provides information about i) legislation and guidelines, ii) integration between SEA and PPPs, iii) sustainability goals, iv) technical organization, v) participatory organization, and vi) monitoring. The results suggest that Italian administrators should cooperate to improve legislation at the regional level. Acknowledging the institution-centred nature of SEA, this methodology could drive the EU to better support SEA development in countries with diversified traditions.« less

Smart spectroscopy sensors: II. Narrow-band laser systems

NASA Astrophysics Data System (ADS)

Matharoo, Inderdeep; Peshko, Igor

2013-03-01

This paper describes the principles of operation of a miniature multifunctional optical sensory system based on laser technology and spectroscopic principles of analysis. The operation of the system as a remote oxygen sensor has been demonstrated. The multi-component alarm sensor has been designed to recognise gases and to measure gas concentration (O2, CO2, CO, CH4, N2O, C2H2, HI, OH radicals and H2O vapour, including semi-heavy water), temperature, pressure, humidity, and background radiation from the environment. Besides gas sensing, the same diode lasers are used for range-finding and to provide sensor self-calibration. The complete system operates as an inhomogeneous sensory network: the laser sensors are capable of using information received from environmental sensors for improving accuracy and reliability of gas concentration measurement. The sources of measurement errors associated with hardware and algorithms of operation and data processing have been analysed in detail.

Multi-hop routing mechanism for reliable sensor computing.

PubMed

Chen, Jiann-Liang; Ma, Yi-Wei; Lai, Chia-Ping; Hu, Chia-Cheng; Huang, Yueh-Min

2009-01-01

Current research on routing in wireless sensor computing concentrates on increasing the service lifetime, enabling scalability for large number of sensors and supporting fault tolerance for battery exhaustion and broken nodes. A sensor node is naturally exposed to various sources of unreliable communication channels and node failures. Sensor nodes have many failure modes, and each failure degrades the network performance. This work develops a novel mechanism, called Reliable Routing Mechanism (RRM), based on a hybrid cluster-based routing protocol to specify the best reliable routing path for sensor computing. Table-driven intra-cluster routing and on-demand inter-cluster routing are combined by changing the relationship between clusters for sensor computing. Applying a reliable routing mechanism in sensor computing can improve routing reliability, maintain low packet loss, minimize management overhead and save energy consumption. Simulation results indicate that the reliability of the proposed RRM mechanism is around 25% higher than that of the Dynamic Source Routing (DSR) and ad hoc On-demand Distance Vector routing (AODV) mechanisms.

Determination of Primary Spectral Bands for Remote Sensing of Aquatic Environments

PubMed Central

Lee, ZhongPing; Carder, Kendall; Arnone, Robert; He, MingXia

2007-01-01

About 30 years ago, NASA launched the first ocean-color observing satellite: the Coastal Zone Color Scanner. CZCS had 5 bands in the visible-infrared domain with an objective to detect changes of phytoplankton (measured by concentration of chlorophyll) in the oceans. Twenty years later, for the same objective but with advanced technology, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 7 bands), the Moderate-Resolution Imaging Spectrometer (MODIS, 8 bands), and the Medium Resolution Imaging Spectrometer (MERIS, 12 bands) were launched. The selection of the number of bands and their positions was based on experimental and theoretical results achieved before the design of these satellite sensors. Recently, Lee and Carder (2002) demonstrated that for adequate derivation of major properties (phytoplankton biomass, colored dissolved organic matter, suspended sediments, and bottom properties) in both oceanic and coastal environments from observation of water color, it is better for a sensor to have ∼15 bands in the 400 – 800 nm range. In that study, however, it did not provide detailed analyses regarding the spectral locations of the 15 bands. Here, from nearly 400 hyperspectral (∼ 3-nm resolution) measurements of remote-sensing reflectance (a measure of water color) taken in both coastal and oceanic waters covering both optically deep and optically shallow waters, first- and second-order derivatives were calculated after interpolating the measurements to 1-nm resolution. From these derivatives, the frequency of zero values for each wavelength was accounted for, and the distribution spectrum of such frequencies was obtained. Furthermore, the wavelengths that have the highest appearance of zeros were identified. Because these spectral locations indicate extrema (a local maximum or minimum) of the reflectance spectrum or inflections of the spectral curvature, placing the bands of a sensor at these wavelengths maximizes the potential of capturing (and then restoring) the spectral curve, and thus maximizes the potential of accurately deriving properties of the water column and/or bottom of various aquatic environments with a multi-band sensor. PMID:28903303

Progress Report on the GROWTH (GNSS Reflectometry for Ocean Waves, Tides, and Height) Research Project

NASA Astrophysics Data System (ADS)

Ichikawa, Kaoru; Akiyama, Hiroaki; Ebinuma, Takuji; Isoguchi, Osamu; Kimura, Noriaki; Kitazawa, Yukihito; Konda, Masanori; Kouguchi, Nobuyuki; Tamura, Hitoshi; Tomita, Hiroyuki; Yoshikawa, Yutaka; Waseda, Takuji

2016-04-01

There has been considerable interest in GNSS Reflectometry (GNSS-R) as a new remote-sensing method. We have started a research program for GNSS-R applications on oceanographic observations under the contract with MEXT (Ministry of Education Culture, Sports, Science and Technology, JAPAN) and launched a Japanese research consortium, GROWTH. It is aiming to evaluate the capabilities of GNSS-R observations for oceanographic phenomena with different time scales, such as ocean waves (1/10 to tens of seconds), tides (one or half days), and sea surface dynamic height (a few days to years). In situ observations of ocean wave spectrum, wind speed vertical profile, and sea surface height will be quantitatively compared with equivalent estimates from simultaneous GNSS-R measurements. The GROWTH project will utilize different types of observation platforms; marine observation towers (about 20 m height), multi-copters (about 100 to 200 m height), and much higher-altitude CYGNSS data. Cross-platform data, together with in situ oceanographic observations, will be compared after adequate temporal averaging that accounts differences of the footprint sizes and temporal and spatial scales of oceanographic phenomena. This paper will provide overview of the GROWTH project, preliminary test results obtained by the multi-sensor platform at observation towers, and preparation status of a ground station that will be supplied to receive CYGNSS data at Japan.

Toward a Tighter Coupling between Models and Observations of Arctic Energy Balance

NASA Astrophysics Data System (ADS)

L'Ecuyer, T. S.

2016-12-01

The Arctic climate is changing more rapidly than almost anywhere else on Earth owing to a number of unique feedbacks that locally amplify the effects of increased greenhouse gas concentrations. While the basic theory behind these feedback mechanisms has been known for a long time, current climate models still struggle to capture observed rates of sea ice decline and ice sheet melt. This may be explained, at least partially, by a lack of observational constraints on cloud and precipitation processes owing to the challenges of making sustained, high quality atmospheric measurements in this inhospitable region. This presentation will introduce a new multi-satellite, multi-model combined Arctic dataset for probing the state of the Arctic climate and documenting and improving prediction models. Recent satellite-based reconstructions of the Arctic energy budget and its annual cycle contained within this dataset will used to demonstrate that many climate models exhibit significant biases in several key energy flows in the region. These biases, in turn, lead to discrepancies in both the magnitude and seasonality of the implied heat transport into the Arctic from lower latitudes. The potential impacts of these biases on the surface mass balance of the Greenland Ice Sheet will be explored. New estimates of downwelling radiative fluxes that explicitly account for the effects of super-cooled liquid water observed by new active satellite sensors will be used to drive a regional ice sheet model to assess the sensitivity of ice sheet dynamical processes to uncertainties in surface radiation balance.

ENSO Simulation in Coupled Ocean-Atmosphere Models: Are the Current Models Better?

DOE Office of Scientific and Technical Information (OSTI.GOV)

AchutaRao, K; Sperber, K R

Maintaining a multi-model database over a generation or more of model development provides an important framework for assessing model improvement. Using control integrations, we compare the simulation of the El Nino/Southern Oscillation (ENSO), and its extratropical impact, in models developed for the 2007 Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report with models developed in the late 1990's (the so-called Coupled Model Intercomparison Project-2 [CMIP2] models). The IPCC models tend to be more realistic in representing the frequency with which ENSO occurs, and they are better at locating enhanced temperature variability over the eastern Pacific Ocean. When compared withmore » reanalyses, the IPCC models have larger pattern correlations of tropical surface air temperature than do the CMIP2 models during the boreal winter peak phase of El Nino. However, for sea-level pressure and precipitation rate anomalies, a clear separation in performance between the two vintages of models is not as apparent. The strongest improvement occurs for the modeling groups whose CMIP2 model tended to have the lowest pattern correlations with observations. This has been checked by subsampling the multi-century IPCC simulations in a manner to be consistent with the single 80-year time segment available from CMIP2. Our results suggest that multi-century integrations may be required to statistically assess model improvement of ENSO. The quality of the El Nino precipitation composite is directly related to the fidelity of the boreal winter precipitation climatology, highlighting the importance of reducing systematic model error. Over North America distinct improvement of El Nino forced boreal winter surface air temperature, sea-level pressure, and precipitation rate anomalies in the IPCC models occurs. This improvement, is directly proportional to the skill of the tropical El Nino forced precipitation anomalies.« less

NASA sea ice and snow validation plan for the Defense Meteorological Satellite Program special sensor microwave/imager

NASA Technical Reports Server (NTRS)

Cavalieri, Donald J. (Editor); Swift, Calvin T. (Editor)

1987-01-01

This document addresses the task of developing and executing a plan for validating the algorithm used for initial processing of sea ice data from the Special Sensor Microwave/Imager (SSMI). The document outlines a plan for monitoring the performance of the SSMI, for validating the derived sea ice parameters, and for providing quality data products before distribution to the research community. Because of recent advances in the application of passive microwave remote sensing to snow cover on land, the validation of snow algorithms is also addressed.

Ocean Dynamics in the Key Regions of North Atlantic-Arctic Exchanges: Evaluation of Global Multi-Resolution FESOM and CMIP-type INMCM Models with Long-Term Observations

NASA Astrophysics Data System (ADS)

Beszczynska-Moeller, A.; Gürses, Ö.; Sidorenko, D.; Goessling, H.; Volodin, E. M.; Gritsun, A.; Iakovlev, N. G.; Andrzejewski, J.

2017-12-01

Enhancing the fidelity of climate models in the Arctic and North Atlantic in order to improve Arctic predictions requires better understanding of the underlying causes of common biases. The main focus of the ERA.Net project NAtMAP (Amending North Atlantic Model Biases to Improve Arctic Predictions) is on the dynamics of the key regions connecting the Arctic and the North Atlantic climate. The study aims not only at increased model realism, but also at a deeper understanding of North Atlantic-Arctic links and their contribution to Arctic predictability. Two complementary approaches employing different global coupled climate models, ECHAM6-FESOM and INMCM4/5, were adopted. The first approach is based on a recent development of climate models with ocean components based on unstructured meshes, allowing to resolve eddies and narrow boundary currents in the most crucial regions while keeping a moderate resolution elsewhere. The multi-resolution sea ice-ocean component of ECHAM6-FESOM allows studying the benefits of very high resolution in key areas of the North Atlantic. An alternative approach to address the North Atlantic and Arctic biases is also tried by tuning the performance of the relevant sub-grid-scale parameterizations in eddy resolving version the CMIP5 climate model INMCM4. Using long-term in situ and satellite observations and available climatologies we attempt to evaluate to what extent a higher resolution, allowing the explicit representation of eddies and narrow boundary currents in the North Atlantic and Nordic Seas, can alleviate the common model errors. The effects of better resolving the Labrador Sea area on reducing the model bias in surface hydrography and improved representation of ocean currents are addressed. Resolving eddy field in the Greenland Sea is assessed in terms of reducing the deep thermocline bias. The impact of increased resolution on the modeled characteristics of Atlantic water transport into the Arctic is examined with a special focus on separation of Atlantic inflow between Fram Strait and the Barents Sea, lateral exchanges in the Nordic Seas, and a role of eddies in modulating the poleward flow of Atlantic water. We also explore the effects of resolving boundary currents in the Arctic basin on the representation of the adjacent sea ice.

Identifying Decadal to Multi-decadal Variability in the Pacific by Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Sommers, L. A.; Hamlington, B.; Cheon, S. H.

2016-12-01

Large scale climate variability in the Pacific Ocean like that associated with ENSO and the Pacific Decadal Oscillation (PDO) has been shown to have a significant impact on climate and sea level across a range of timescales. The changes related to these climate signals have worldwide impacts on fisheries, weather, and precipitation patterns among others. Understanding these inter-annual to multi-decadal oscillations is imperative to longer term climate forecasts and understanding how climate will behave, and its effect on changes in sea level. With a 110-year reconstruction of sea level, we examine decadal to multi-decadal variability seen in the sea level fluctuations in the Pacific Ocean. Using empirical mode decomposition (EMD), we break down regional sea level into a series of intrinsic mode functions (IMFs) and attempt attribution of these IMFs to specific climate modes of variability. In particular, and not unexpectedly, we identify IMFs associated with the PDO, finding correlations between the PDO Index and IMFs in the Pacific Ocean upwards of 0.6-0.8 over the 110-year reconstructed record. Perhaps more significantly, we also find evidence of a longer multi-decadal signal ( 50-60 years) in the higher order IMFs. This lower frequency variability has been suggested in previous literature as influencing GMSL, but here we find a regional pattern associated with this multi-decadal signal. By identifying and separating these periodic climate signals, we can gain a better understanding of how the sea level variability associated with these modes can impact sea level on short timescales and serve to exacerbate the effects of long-term sea level change.

Dim target detection method based on salient graph fusion

NASA Astrophysics Data System (ADS)

Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun

2018-02-01

Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.

Collar temperature sensor data reveal long-term patterns in southern Beaufort Sea polar bear den distribution on pack ice and land

USGS Publications Warehouse

Olson, Jay W; Rode, Karyn D.; Eggett, Dennis L.; Smith, T.S.; Wilson, R. R.; Durner, George M.; Fischbach, Anthony S.; Atwood, Todd C.; Douglas, David C.

2017-01-01

In response to a changing climate, many species alter habitat use. Polar bears Ursus maritimus in the southern Beaufort Sea have increasingly used land for maternal denning. To aid in detecting denning behavior, we developed an objective method to identify polar bear denning events using temperature sensor data collected by satellite-linked transmitters deployed on adult females between 1985 and 2013. We then applied this method to determine whether southern Beaufort Sea polar bears have continued to increase land denning with recent sea-ice loss and examined whether sea-ice conditions affect the distribution of dens between pack-ice and coastal substrates. Because land use in summer and autumn has also increased, we examined potential associations between summering substrate and denning substrate. Statistical process control methods applied to temperature-sensor data identified denning events with 94.5% accuracy in comparison to direct observations (n = 73) and 95.7% accuracy relative to subjective classifications based on temperature, location, and activity sensor data (n = 116). We found an increase in land-based denning during the study period. The frequency of land denning was directly related to the distance that sea ice retreated from the coast. Among females that denned, all 14 that summered on land subsequently denned there, whereas 29% of the 69 bears summering on ice denned on land. These results suggest that denning on land may continue to increase with further loss of sea ice. While the effects that den substrate have on nutrition, energetics, and reproduction are unclear, more polar bears denning onshore will likely increase human-bear interactions.

Multi-Directional Environmental Sensors

NASA Technical Reports Server (NTRS)

Manohara, Harish (Inventor); Del Castillo, Linda Y. (Inventor); Mojarradi, Mohammed M. (Inventor)

2016-01-01

Systems and methods in accordance with embodiments of the invention implement multi-directional environmental sensors. In one embodiment, a multi-directional environmental sensor includes: an inner conductive element that is substantially symmetrical about three orthogonal planes; an outer conductive element that is substantially symmetrical about three orthogonal planes; and a device that measures the electrical characteristics of the multi-directional environmental sensor, the device having a first terminal and a second terminal; where the inner conductive element is substantially enclosed within the outer conductive element; where the inner conductive element is electrically coupled to the first terminal of the device; and where the outer conductive element is electrically coupled to the second terminal of the device.

Multi-Mission Remote Sensing of Suspended Particulate Matter and Diffuse Attenuation Coefficient in the Yangtze Estuarine and Coastal Waters

NASA Astrophysics Data System (ADS)

Yu, X.; Salama, S.; Shen, F.

2016-08-01

During the Dragon-3 project (ID: 10555) period, we developed and improved the atmospheric correction algorithms (AC) and retrieval models of suspended sediment concentration ( ) and diffuse attenuation coefficient ( ) for the Yangtze estuarine and coastal waters. The developed models were validated by measurements with consistently stable and fairly accurate estimations, reproducing reasonable distribution maps of and over the study area. Spatial-temporal variations of were presented and the mechanisms of the sediment transport were discussed. We further examined the compatibility of the developed AC algorithms and retrieval model and the consistency of satellite products for multi-sensor such as MODIS/Terra/Aqua, MERIS/Envisat, MERSI/ FY-3 and GOCI. The inter-comparison of multi- sensor suggested that different satellite products can be combined to increase revisit frequency and complement a temporal gap of time series satellites that may exist between on-orbit and off- orbit, facilitating a better monitor on the spatial- temporal dynamics of .

Heimdall System for MSSS Sensor Tasking

NASA Astrophysics Data System (ADS)

Herz, A.; Jones, B.; Herz, E.; George, D.; Axelrad, P.; Gehly, S.

In Norse Mythology, Heimdall uses his foreknowledge and keen eyesight to keep watch for disaster from his home near the Rainbow Bridge. Orbit Logic and the Colorado Center for Astrodynamics Research (CCAR) at the University of Colorado (CU) have developed the Heimdall System to schedule observations of known and uncharacterized objects and search for new objects from the Maui Space Surveillance Site. Heimdall addresses the current need for automated and optimized SSA sensor tasking driven by factors associated with improved space object catalog maintenance. Orbit Logic and CU developed an initial baseline prototype SSA sensor tasking capability for select sensors at the Maui Space Surveillance Site (MSSS) using STK and STK Scheduler, and then added a new Track Prioritization Component for FiSST-inspired computations for predicted Information Gain and Probability of Detection, and a new SSA-specific Figure-of-Merit (FOM) for optimized SSA sensor tasking. While the baseline prototype addresses automation and some of the multi-sensor tasking optimization, the SSA-improved prototype addresses all of the key elements required for improved tasking leading to enhanced object catalog maintenance. The Heimdall proof-of-concept was demonstrated for MSSS SSA sensor tasking for a 24 hour period to attempt observations of all operational satellites in the unclassified NORAD catalog, observe a small set of high priority GEO targets every 30 minutes, make a sky survey of the GEO belt region accessible to MSSS sensors, and observe particular GEO regions that have a high probability of finding new objects with any excess sensor time. This Heimdall prototype software paves the way for further R&D that will integrate this technology into the MSSS systems for operational scheduling, improve the software's scalability, and further tune and enhance schedule optimization. The Heimdall software for SSA sensor tasking provides greatly improved performance over manual tasking, improved coordinated sensor usage, and tasking schedules driven by catalog improvement goals (reduced overall covariance, etc.). The improved performance also enables more responsive sensor tasking to address external events, newly detected objects, newly detected object activity, and sensor anomalies. Instead of having to wait until the next day's scheduling phase, events can be addressed with new tasking schedules immediately (within seconds or minutes). Perhaps the most important benefit is improved SSA based on an overall improvement to the quality of the space catalog. By driving sensor tasking and scheduling based on predicted Information Gain and other relevant factors, better decisions are made in the application of available sensor resources, leading to an improved catalog and better information about the objects of most interest. The Heimdall software solution provides a configurable, automated system to improve sensor tasking efficiency and responsiveness for SSA applications. The FISST algorithms for Track Prioritization, SSA specific task and resource attributes, Scheduler algorithms, and configurable SSA-specific Figure-of-Merit together provide optimized and tunable scheduling for the Maui Space Surveillance Site and possibly other sites and organizations across the U.S. military and for allies around the world.

Assessment of Arctic and Antarctic Sea Ice Predictability in CMIP5 Decadal Hindcasts

NASA Technical Reports Server (NTRS)

Yang, Chao-Yuan; Liu, Jiping (Inventor); Hu, Yongyun; Horton, Radley M.; Chen, Liqi; Cheng, Xiao

2016-01-01

This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea ice. We analyze decadal hindcasts/predictions of 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Decadal hindcasts exhibit a large multimodel spread in the simulated sea ice extent, with some models deviating significantly from the observations as the predicted ice extent quickly drifts away from the initial constraint. The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Sea ice extent in the North Pacific has better predictive skill than that in the North Atlantic (particularly at a lead time of 3-7 years), but there is a reemerging predictive skill in the North Atlantic at a lead time of 6-8 years. In contrast to the Arctic, Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales, and there is no obvious improvement linking the areal extent of significant predictive skill to lead time increase. This might be because nearly all the models predict a retreating Antarctic sea ice cover, opposite to the observations. For the Arctic, the predictive skill of the multi-model ensemble mean outperforms most models and the persistence prediction at longer timescales, which is not the case for the Antarctic. Overall, for the Arctic, initialized decadal hindcasts show improved predictive skill compared to uninitialized simulations, although this improvement is not present in the Antarctic.

SeaWiFS Technical Report Series. Volume 41; Case Studies for SeaWiFS Calibration and Validation

NASA Technical Reports Server (NTRS)

Yeh, Eueng-nan; Barnes, Robert A.; Darzi, Michael; Kumar, Lakshmi; Early, Edward A.; Johnson, B. Carol; Mueller, James L.; Trees, Charles C.

1997-01-01

This document provides brief reports, or case studies, on a number of investigations sponsored by the Calibration and Validation Team (CVT) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. Chapter I describes the calibration and characterization of the GSFC sphere, which was used in the recent recalibration of the SeaWiFS instrument. Chapter 2 presents a revision of the diffuse attenuation coefficient, K(490), algorithm based on the SeaWiFS wavelengths. Chapter 3 provides an implementation scheme for an algorithm to remove out-of-band radiance when using a sensor calibration based on a finite width (truncated) spectral response function, e.g., between the 1% transmission points. Chapter 4 describes the implementation schemes for the stray light quality flag (local area coverage [LAC] and global area coverage [GAC]) and the LAC stray light correction.

A multisensor approach to sea ice classification for the validation of DMSP-SSM/I passive microwave derived sea ice products

NASA Technical Reports Server (NTRS)

Steffen, K.; Schweiger, A. J.

1990-01-01

The validation of sea ice products derived from the Special Sensor Microwave Imager (SSM/I) on board a DMSP platform is examined using data from the Landsat MSS and NOAA-AVHRR sensors. Image processing techniques for retrieving ice concentrations from each type of imagery are developed and results are intercompared to determine the ice parameter retrieval accuracy of the SSM/I NASA-Team algorithm. For case studies in the Beaufort Sea and East Greenland Sea, average retrieval errors of the SSM/I algorithm are between 1.7 percent for spring conditions and 4.3 percent during freeze up in comparison with Landsat derived ice concentrations. For a case study in the East Greenland Sea, SSM/I derived ice concentration in comparison with AVHRR imagery display a mean error of 9.6 percent.

Tracking Dissolved Methane Concentrations near Active Seeps and Gas Hydrates: Sea of Japan.

NASA Astrophysics Data System (ADS)

Snyder, G. T.; Aoki, S.; Matsumoto, R.; Tomaru, H.; Owari, S.; Nakajima, R.; Doolittle, D. F.; Brant, B.

2015-12-01

A number of regions in the Sea of Japan are known for active gas venting and for gas hydrate exposures on the sea floor. In this investigation we employed several gas sensors mounted on a ROV in order to determine the concentrations of dissolved methane in the water near these sites. Methane concentrations were determined during two-second intervals throughout each ROV deployment during the cruise. The methane sensor deployments were coupled with seawater sampling using Niskin bottles. Dissolved gas concentrations were later measured using gas chromatography in order to compare with the sensor results taken at the same time. The observed maximum dissolved methane concentrations were much lower than saturation values, even when the ROV manipulators were in contact with gas hydrate. Nonetheless, dissolved concentrations did reach several thousands of nmol/L near gas hydrate exposures and gas bubbles, more than two orders of magnitude over the instrumental detection limits. Most of the sensors tested were able to detect dissolved methane concentrations as low as 10 nmol/L which permitted detection when the ROV approached methane plume sites, even from several tens of meters above the sea floor. Despite the low detection limits, the methane sensors showed variable response times when returning to low-background seawater (~5nM). For some of the sensors, the response time necessary to return to background values occurred in a matter of minutes, while for others it took several hours. Response time, as well as detection limit, should be an important consideration when selecting methane sensors for ROV or AUV investigations. This research was made possible, in part, through funding provided by the Japanese Ministry of Economy, Trade and Industry (METI).

A New Multi-Sensor Track Fusion Architecture for Multi-Sensor Information Integration

DTIC Science & Technology

2004-09-01

NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION ...NAME(S) AND ADDRESS(ES) Lockheed Martin Aeronautical Systems Company,Marietta,GA,3063 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING...tracking process and degrades the track accuracy. ARCHITECHTURE OF MULTI-SENSOR TRACK FUSION MODEL The Alpha

Wireless Sensor Network Optimization: Multi-Objective Paradigm

PubMed Central

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Multi-Sensor Methods for Mobile Radar Motion Capture and Compensation

NASA Astrophysics Data System (ADS)

Nakata, Robert

Remote sensing has many applications, including surveying and mapping, geophysics exploration, military surveillance, search and rescue and counter-terrorism operations. Remote sensor systems typically use visible image, infrared or radar sensors. Camera based image sensors can provide high spatial resolution but are limited to line-of-sight capture during daylight. Infrared sensors have lower resolution but can operate during darkness. Radar sensors can provide high resolution motion measurements, even when obscured by weather, clouds and smoke and can penetrate walls and collapsed structures constructed with non-metallic materials up to 1 m to 2 m in depth depending on the wavelength and transmitter power level. However, any platform motion will degrade the target signal of interest. In this dissertation, we investigate alternative methodologies to capture platform motion, including a Body Area Network (BAN) that doesn't require external fixed location sensors, allowing full mobility of the user. We also investigated platform stabilization and motion compensation techniques to reduce and remove the signal distortion introduced by the platform motion. We evaluated secondary ultrasonic and radar sensors to stabilize the platform resulting in an average 5 dB of Signal to Interference Ratio (SIR) improvement. We also implemented a Digital Signal Processing (DSP) motion compensation algorithm that improved the SIR by 18 dB on average. These techniques could be deployed on a quadcopter platform and enable the detection of respiratory motion using an onboard radar sensor.

Flexible quality of service model for wireless body area sensor networks.

PubMed

Liao, Yangzhe; Leeson, Mark S; Higgins, Matthew D

2016-03-01

Wireless body area sensor networks (WBASNs) are becoming an increasingly significant breakthrough technology for smart healthcare systems, enabling improved clinical decision-making in daily medical care. Recently, radio frequency ultra-wideband technology has developed substantially for physiological signal monitoring due to its advantages such as low-power consumption, high transmission data rate, and miniature antenna size. Applications of future ubiquitous healthcare systems offer the prospect of collecting human vital signs, early detection of abnormal medical conditions, real-time healthcare data transmission and remote telemedicine support. However, due to the technical constraints of sensor batteries, the supply of power is a major bottleneck for healthcare system design. Moreover, medium access control (MAC) needs to support reliable transmission links that allow sensors to transmit data safely and stably. In this Letter, the authors provide a flexible quality of service model for ad hoc networks that can support fast data transmission, adaptive schedule MAC control, and energy efficient ubiquitous WBASN networks. Results show that the proposed multi-hop communication ad hoc network model can balance information packet collisions and power consumption. Additionally, wireless communications link in WBASNs can effectively overcome multi-user interference and offer high transmission data rates for healthcare systems.

The multi-queue model applied to random access protocol

NASA Astrophysics Data System (ADS)

Fan, Xinlong

2013-03-01

The connection of everything in a sensory and an intelligent way is a pursuit in smart environment. This paper introduces the engineered cell-sensors into the multi-agent systems to realize the smart environment. The seamless interface with the natural environment and strong information-processing ability of cell with the achievements of synthetic biology make the construction of engineered cell-sensors possible. However, the engineered cell-sensors are only simple-functional and unreliable computational entities. Therefore how to combine engineered cell-sensors with digital device is a key problem in order to realize the smart environment. We give the abstract structure and interaction modes of the engineered cell-sensors in order to introduce engineered cell-sensors into multi-agent systems. We believe that the introduction of engineered cell-sensors will push forward the development of the smart environment.

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

PubMed Central

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-01-01

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective. PMID:25207870

Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

PubMed

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-09-09

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective.

A Study of Tropical thin Cirrus Clouds with Supervised Learning

NASA Astrophysics Data System (ADS)

Rodier, S. D.; Hu, Y.; Vaughan, M. A.

2007-12-01

ABSTRACT Accurate knowledge of the temporal frequency and spatial extent of optically thin cirrus is crucial to climate feedback analysis. Current global warming theory asserts that when the atmospheric concentration of CO2 increases, the outgoing longwave radiation at non-window wavelengths is reduced. If the Earth's net radiative balance is to remain stable, ground temperatures must rise in response, thereby increasing thermal emission to space. Current models do not account for subsequent changes in cloud cover, because this aspect of the climate feedback system is so poorly understood. One possible response of the cloud-climate feedback process is an increase in the global occurrence of thin cirrus clouds, driven by the increase in longwave cooling in the upper troposphere that results from higher CO2 concentrations. Exacerbating the difficulty of assessing the situation is the fact that passive remote sensing instruments cannot reliably detect cirrus clouds with optical depths less than ~0.3, because these clouds do not reflect enough sunlight to create a sufficient contrast with the Earth's surface. Now, however, the presence of thin cirrus can for the first time be accurately detected and systematically monitored by the combination of active and passive sensors onboard the CALIPSO satellite. Nevertheless, the data record is still quite limited, as CALIPSO has been in orbit for only 16 months. We have therefore initiated a multi-platform data fusion study to establish a methodology for extending the limited set of CALIPSO measurements to the existing 30-year record of passive remote sensing data, and thus improve our understanding of cloud feedback mechanisms. Using nighttime data from the first 10 days in April 2007 as a training set, we applied a general regression neural network (GRNN) to collocated samples of sea surface temperature (SST) reported by AMSR, brightness temperatures (BT) from the CALIPSO imaging infrared radiometer (IIR), and optical depths (OD) derived from the CALIPSO lidar measurements. The result is an accurate mapping of the optical depths derived from the active sensors to the brightness temperatures computed from the passive sensor measurements. Applying the trained network to this combination of passive sensor parameters, optical depths as small as 0.1 can be reliably retrieved. The relative uncertainties in the retrieval are reasonable, and can be improved significantly by use of a much larger training set.

Global mapping of sea-ice production from the satellite microwaves

NASA Astrophysics Data System (ADS)

Ohshima, K. I.; Nihashi, S.; Iwamoto, K.; Tamaru, N.; Nakata, K.; Tamura, T.

2016-12-01

Global overturning circulation is driven by density differences. Saline water rejected by sea-ice production in coastal polynyas is the main source of dense water, and thus sea-ice production is a key factor in the overturning circulation. However, until recently sea-ice production and its interannual variability have not been well understood due to difficulties of in situ observation. The most effective means of detection of thin-ice area and estimation of sea-ice production on large scales is satellite remote sensing using passive microwave sensors, specifically the Special Sensor Microwave/Imager and Advanced Microwave Scanning Radiometer. This is based upon their ability to gain complete polar coverage on a daily basis irrespective of clouds and darkness. We have estimated sea-ice production globally based on heat flux calculations using the satellite-derived thin ice thickness data. The mapping demonstrates that ice production rate is high in Antarctic coastal polynyas, in contrast to Arctic coastal polynyas. This is consistent with the formation of Antarctic Bottom Water (AABW). The Ross Ice Shelf polynya has by far the highest ice production in the Southern Hemisphere. The mapping has revealed that the Cape Darnley polynya is the second highest production area, leading to the discovery of the missing (fourth) source of AABW in this region. In the region off the Mertz Glacier Tongue, sea-ice production decreased by as much as 40 %, due to the glacier calving in early 2010, resulting in a significant decrease in AABW production. The Okhotsk Northwestern polynya exhibits the highest ice production in the Northern Hemisphere, and the resultant dense water formation leads to overturning in the North Pacific. Estimates of its ice production show a significant decrease over the past 30-50 years, likely causing the weakening of the North Pacific overturning. The mapping also provides surface boundary conditions and validation data of heat- and salt-flux associated with sea-ice formation/melting for various ocean and coupled models. Improvement of thin ice microwave algorithm including the comparison with the polynya mooring data is now being made for higher accuracy estimate of sea-ice production.

Solar multi-conjugate adaptive optics performance improvement

NASA Astrophysics Data System (ADS)

Zhang, Zhicheng; Zhang, Xiaofang; Song, Jie

2015-08-01

In order to overcome the effect of the atmospheric anisoplanatism, Multi-Conjugate Adaptive Optics (MCAO), which was developed based on turbulence correction by means of several deformable mirrors (DMs) conjugated to different altitude and by which the limit of a small corrected FOV that is achievable with AO is overcome and a wider FOV is able to be corrected, has been widely used to widen the field-of-view (FOV) of a solar telescope. With the assistance of the multi-threaded Adaptive Optics Simulator (MAOS), we can make a 3D reconstruction of the distorted wavefront. The correction is applied by one or more DMs. This technique benefits from information about atmospheric turbulence at different layers, which can be used to reconstruct the wavefront extremely well. In MAOS, the sensors are either simulated as idealized wavefront gradient sensors, tip-tilt sensors based on the best Zernike fit, or a WFS using physical optics and incorporating user specified pixel characteristics and a matched filter pixel processing algorithm. Only considering the atmospheric anisoplanatism, we focus on how the performance of a solar MCAO system is related to the numbers of DMs and their conjugate heights. We theoretically quantify the performance of the tomographic solar MCAO system. The results indicate that the tomographic AO system can improve the average Strehl ratio of a solar telescope by only employing one or two DMs conjugated to the optimum altitude. And the S.R. has a significant increase when more deformable mirrors are used. Furthermore, we discuss the effects of DM conjugate altitude on the correction achievable by the MCAO system, and present the optimum DM conjugate altitudes.

Multi-spectral image analysis for improved space object characterization

NASA Astrophysics Data System (ADS)

Glass, William; Duggin, Michael J.; Motes, Raymond A.; Bush, Keith A.; Klein, Meiling

2009-08-01

The Air Force Research Laboratory (AFRL) is studying the application and utility of various ground-based and space-based optical sensors for improving surveillance of space objects in both Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO). This information can be used to improve our catalog of space objects and will be helpful in the resolution of satellite anomalies. At present, ground-based optical and radar sensors provide the bulk of remotely sensed information on satellites and space debris, and will continue to do so into the foreseeable future. However, in recent years, the Space-Based Visible (SBV) sensor was used to demonstrate that a synthesis of space-based visible data with ground-based sensor data could provide enhancements to information obtained from any one source in isolation. The incentives for space-based sensing include improved spatial resolution due to the absence of atmospheric effects and cloud cover and increased flexibility for observations. Though ground-based optical sensors can use adaptive optics to somewhat compensate for atmospheric turbulence, cloud cover and absorption are unavoidable. With recent advances in technology, we are in a far better position to consider what might constitute an ideal system to monitor our surroundings in space. This work has begun at the AFRL using detailed optical sensor simulations and analysis techniques to explore the trade space involved in acquiring and processing data from a variety of hypothetical space-based and ground-based sensor systems. In this paper, we briefly review the phenomenology and trade space aspects of what might be required in order to use multiple band-passes, sensor characteristics, and observation and illumination geometries to increase our awareness of objects in space.

Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors.

PubMed

Chowdhury, Enhad A; Western, Max J; Nightingale, Thomas E; Peacock, Oliver J; Thompson, Dylan

2017-01-01

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; P<0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; P<0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices are not yet equivalent to the best research-grade devices or indeed equivalent to each other. We propose independent quality standards and/or accuracy ratings for consumer devices are required.

Assessment of laboratory and daily energy expenditure estimates from consumer multi-sensor physical activity monitors

PubMed Central

Chowdhury, Enhad A.; Western, Max J.; Nightingale, Thomas E.; Peacock, Oliver J.; Thompson, Dylan

2017-01-01

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; P<0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; P<0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices are not yet equivalent to the best research-grade devices or indeed equivalent to each other. We propose independent quality standards and/or accuracy ratings for consumer devices are required. PMID:28234979

Recent Improvements in Retrieving Near-Surface Air Temperature and Humidity Using Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Roberts, J. Brent

2010-01-01

Detailed studies of the energy and water cycles require accurate estimation of the turbulent fluxes of moisture and heat across the atmosphere-ocean interface at regional to basin scale. Providing estimates of these latent and sensible heat fluxes over the global ocean necessitates the use of satellite or reanalysis-based estimates of near surface variables. Recent studies have shown that errors in the surface (10 meter)estimates of humidity and temperature are currently the largest sources of uncertainty in the production of turbulent fluxes from satellite observations. Therefore, emphasis has been placed on reducing the systematic errors in the retrieval of these parameters from microwave radiometers. This study discusses recent improvements in the retrieval of air temperature and humidity through improvements in the choice of algorithms (linear vs. nonlinear) and the choice of microwave sensors. Particular focus is placed on improvements using a neural network approach with a single sensor (Special Sensor Microwave/Imager) and the use of combined sensors from the NASA AQUA satellite platform. The latter algorithm utilizes the unique sampling available on AQUA from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A). Current estimates of uncertainty in the near-surface humidity and temperature from single and multi-sensor approaches are discussed and used to estimate errors in the turbulent fluxes.

Extracellular Bio-imaging of Acetylcholine-stimulated PC12 Cells Using a Calcium and Potassium Multi-ion Image Sensor.

PubMed

Matsuba, Sota; Kato, Ryo; Okumura, Koichi; Sawada, Kazuaki; Hattori, Toshiaki

2018-01-01

In biochemistry, Ca 2+ and K + play essential roles to control signal transduction. Much interest has been focused on ion-imaging, which facilitates understanding of their ion flux dynamics. In this paper, we report a calcium and potassium multi-ion image sensor and its application to living cells (PC12). The multi-ion sensor had two selective plasticized poly(vinyl chloride) membranes containing ionophores. Each region on the sensor responded to only the corresponding ion. The multi-ion sensor has many advantages including not only label-free and real-time measurement but also simultaneous detection of Ca 2+ and K + . Cultured PC12 cells treated with nerve growth factor were prepared, and a practical observation for the cells was conducted with the sensor. After the PC12 cells were stimulated by acetylcholine, only the extracellular Ca 2+ concentration increased while there was no increase in the extracellular K + concentration. Through the practical observation, we demonstrated that the sensor was helpful for analyzing the cell events with changing Ca 2+ and/or K + concentration.

Doppler effect for sound emitted by a moving airborne source and received by acoustic sensors located above and below the sea surface.

PubMed

Ferguson, B G

1993-12-01

The acoustic emissions from a propeller-driven aircraft are received by a microphone mounted just above ground level and then by a hydrophone located below the sea surface. The dominant feature in the output spectrum of each acoustic sensor is the spectral line corresponding to the propeller blade rate. A frequency estimation technique is applied to the acoustic data from each sensor so that the Doppler shift in the blade rate can be observed at short time intervals during the aircraft's transit overhead. For each acoustic sensor, the observed variation with time of the Doppler-shifted blade rate is compared with the variation predicted by a simple ray-theory model that assumes the atmosphere and the sea are distinct isospeed sound propagation media separated by a plane boundary. The results of the comparison are shown for an aircraft flying with a speed of about 250 kn at altitudes of 500, 700, and 1000 ft.

Characterization of zeolites using xenon-129 nuclear magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Jo, Young-Heon

This study focused on the following three aspects of thermal and thermohaline dynamics in the oceans using long-time series (January 1993 to December 1999) of multi-sensor data. They are (1) heat storage anomaly in the upper layer of the Pacific and the Atlantic using altimeter data; (2) heat and moisture transfer in the Tropical Pacific derived from Bowen ratio (Bo), sensible heat flux (SHF), and latent heat flux (LHF); (3) salt fluxes from the Mediterranean Sea into the North Atlantic through the Mediterranean Eddies (Meddies). The heat storage anomaly derived from XBT data (H' XBT) and altimeter data (H' T/P) was highly correlated, except in a few regions. The non-steric height signals in the altimeter measurements were analyzed. For the Pacific, the wiggle features across 20°N North Pacific caused by long baroclinic waves were found in the areas of low correlation between H'XBT and H' T/P, and were validated with a theoretical dispersion relation. For the Tropical Atlantic, three regions were investigated, i.e., near the Amazon River mouth; the North Equatorial Counter Current; the Guinea Dome. The equilibrium Bowen Ratio (Bo) can be estimated empirically from the sea surface temperature only when the air is saturated with water vapor at the sea surface. In order to estimate the discrepancy between the empirical Bo and the bulk formulated Bo and to correct for the wind-effect and the humidity-effect, the Tropical Atmosphere Ocean data were used. After computing SHF and Bo, the LHF were estimated. The SHF was estimated using wind divergence, which is caused by a convection of airflow. The root mean square of the SHF and LHF were estimated as 3.5Wm-2 and 39.3Wm-2 , respectively. The trajectories and evolution of the Meddies were studied using satellite multi-sensor data analyses. Two experiments, AMUSE and SEMAPHORE were used to directly validate my method. In order to analyze the Meddies' movements, the effect of baroclinic instability resulting from the surface air pressure variations and wind forcing on the Meddies was considered. Finally, the horizontal and vertical viscosity dissipation of the Meddies, using angular velocity measured by floats, was computed and compared with a theoretical model.

Mixed-spectrum generation mechanism analysis of dispersive hyperspectral imaging for improving environmental monitoring of coastal waters

NASA Astrophysics Data System (ADS)

Xie, Feng; Xiao, Gonghai; Qi, Hongxing; Shu, Rong; Wang, Jianyu; Xue, Yongqi

2010-11-01

At present, most part of coast zone in China belong to Case II waters with a large volume of shallow waters. Through theories and experiences of ocean water color remote sensing has a prominent improvement, there still exist many problems mainly as follows: (a) there is not a special sensor for heat pollution of coast water remote sensing up to now; (b) though many scholars have developed many water quality parameter retrieval models in the open ocean, there still exists a large gap from practical applications in turbid coastal waters. It is much more difficult due to the presence of high concentrations of suspended sediments and dissolved organic material, which overwhelm the spectral signal of sea water. Hyperspectral remote sensing allows a sensor on a moving platform to gather emitted radiation from the Earth's surface, which opens a way to reach a better analysis and understanding of coast water. Operative Modular Imaging Spectrometer (OMIS) is a type of representative imaging spectrometer developed by the Chinese Academy of Sciences. OMIS collects reflective and radiation light from ground by RC telescope with the scanning mirror cross track and flight of plane along track. In this paper, we explore the use of OMIS as the airborne sensor for the heat pollution monitoring in coast water, on the basis of an analysis on the mixed-spectrum arising from the image correcting process for geometric distortion. An airborne experiment was conducted in the winter of 2009 on the coast of the East Sea in China.

Sensor and information fusion for improved hostile fire situational awareness

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.; Ludwig, William D.

2010-04-01

A research-oriented Army Technology Objective (ATO) named Sensor and Information Fusion for Improved Hostile Fire Situational Awareness uniquely focuses on the underpinning technologies to detect and defeat any hostile threat; before, during, and after its occurrence. This is a joint effort led by the Army Research Laboratory, with the Armaments and the Communications and Electronics Research, Development, and Engineering Centers (CERDEC and ARDEC) partners. It addresses distributed sensor fusion and collaborative situational awareness enhancements, focusing on the underpinning technologies to detect/identify potential hostile shooters prior to firing a shot and to detect/classify/locate the firing point of hostile small arms, mortars, rockets, RPGs, and missiles after the first shot. A field experiment conducted addressed not only diverse modality sensor performance and sensor fusion benefits, but gathered useful data to develop and demonstrate the ad hoc networking and dissemination of relevant data and actionable intelligence. Represented at this field experiment were various sensor platforms such as UGS, soldier-worn, manned ground vehicles, UGVs, UAVs, and helicopters. This ATO continues to evaluate applicable technologies to include retro-reflection, UV, IR, visible, glint, LADAR, radar, acoustic, seismic, E-field, narrow-band emission and image processing techniques to detect the threats with very high confidence. Networked fusion of multi-modal data will reduce false alarms and improve actionable intelligence by distributing grid coordinates, detection report features, and imagery of threats.

Temperature and pressure fiber-optic sensors applied to minimally invasive diagnostics and therapies

NASA Astrophysics Data System (ADS)

Hamel, Caroline; Pinet, Éric

2006-02-01

We present how fiber-optic temperature or pressure sensors could be applied to minimally invasive diagnostics and therapies. For instance a miniature pressure sensor based on micro-optical mechanical systems (MOMS) could solve most of the problems associated with fluidic pressure transduction presently used for triggering purposes. These include intra-aortic balloon pumping (IABP) therapy and other applications requiring detection of fast and/or subtle fluid pressure variations such as for intracranial pressure monitoring or for urology diagnostics. As well, miniature temperature sensors permit minimally invasive direct temperature measurement in diagnostics or therapies requiring energy transfer to living tissues. The extremely small size of fiber-optic sensors that we have developed allows quick and precise in situ measurements exactly where the physical parameters need to be known. Furthermore, their intrinsic immunity to electromagnetic interference (EMI) allows for the safe use of EMI-generating therapeutic or diagnostic equipments without compromising the signal quality. With the trend of ambulatory health care and the increasing EMI noise found in modern hospitals, the use of multi-parameter fiber-optic sensors will improve constant patient monitoring without any concern about the effects of EMI disturbances. The advantages of miniature fiberoptic sensors will offer clinicians new monitoring tools that open the way for improved diagnostic accuracy and new therapeutic technologies.

Evaluation of Arctic Sea Ice Thickness Simulated by AOMIP Models

NASA Technical Reports Server (NTRS)

Johnson, Mark; Proshutinsky, Andrey; Aksenov, Yevgeny; Nguyen, An T.; Lindsay, Ron; Haas, Christian; Zhang, Jinlun; Diansky, Nimolay; Kwok, Ron; Maslowski, Wieslaw;

Accurate multi-robot targeting for keyhole neurosurgery based on external sensor monitoring.

PubMed

Comparetti, Mirko Daniele; Vaccarella, Alberto; Dyagilev, Ilya; Shoham, Moshe; Ferrigno, Giancarlo; De Momi, Elena

2012-05-01

Robotics has recently been introduced in surgery to improve intervention accuracy, to reduce invasiveness and to allow new surgical procedures. In this framework, the ROBOCAST system is an optically surveyed multi-robot chain aimed at enhancing the accuracy of surgical probe insertion during keyhole neurosurgery procedures. The system encompasses three robots, connected as a multiple kinematic chain (serial and parallel), totalling 13 degrees of freedom, and it is used to automatically align the probe onto a desired planned trajectory. The probe is then inserted in the brain, towards the planned target, by means of a haptic interface. This paper presents a new iterative targeting approach to be used in surgical robotic navigation, where the multi-robot chain is used to align the surgical probe to the planned pose, and an external sensor is used to decrease the alignment errors. The iterative targeting was tested in an operating room environment using a skull phantom, and the targets were selected on magnetic resonance images. The proposed targeting procedure allows about 0.3 mm to be obtained as the residual median Euclidean distance between the planned and the desired targets, thus satisfying the surgical accuracy requirements (1 mm), due to the resolution of the diffused medical images. The performances proved to be independent of the robot optical sensor calibration accuracy.

Improved prosthetic hand control with concurrent use of myoelectric and inertial measurements.

PubMed

Krasoulis, Agamemnon; Kyranou, Iris; Erden, Mustapha Suphi; Nazarpour, Kianoush; Vijayakumar, Sethu

2017-07-11

Myoelectric pattern recognition systems can decode movement intention to drive upper-limb prostheses. Despite recent advances in academic research, the commercial adoption of such systems remains low. This limitation is mainly due to the lack of classification robustness and a simultaneous requirement for a large number of electromyogram (EMG) electrodes. We propose to address these two issues by using a multi-modal approach which combines surface electromyography (sEMG) with inertial measurements (IMs) and an appropriate training data collection paradigm. We demonstrate that this can significantly improve classification performance as compared to conventional techniques exclusively based on sEMG signals. We collected and analyzed a large dataset comprising recordings with 20 able-bodied and two amputee participants executing 40 movements. Additionally, we conducted a novel real-time prosthetic hand control experiment with 11 able-bodied subjects and an amputee by using a state-of-the-art commercial prosthetic hand. A systematic performance comparison was carried out to investigate the potential benefit of incorporating IMs in prosthetic hand control. The inclusion of IM data improved performance significantly, by increasing classification accuracy (CA) in the offline analysis and improving completion rates (CRs) in the real-time experiment. Our findings were consistent across able-bodied and amputee subjects. Integrating the sEMG electrodes and IM sensors within a single sensor package enabled us to achieve high-level performance by using on average 4-6 sensors. The results from our experiments suggest that IMs can form an excellent complimentary source signal for upper-limb myoelectric prostheses. We trust that multi-modal control solutions have the potential of improving the usability of upper-extremity prostheses in real-life applications.

Operational multisensor sea ice concentration algorithm utilizing Sentinel-1 and AMSR2 data

NASA Astrophysics Data System (ADS)

Dinessen, Frode

2017-04-01

The Norwegian Ice Service provide ice charts of the European part of the Arctic every weekday. The charts are produced from a manually interpretation of satellite data where SAR (Synthetic Aperture Radar) data plays a central role because of its high spatial resolution and Independence of cloud cover. A new chart is produced every weekday and the charts are distributed through the CMEMS portal. After the launch of Sentinel-1A and B the number of available SAR data have significant increased making it difficult to utilize all the data in a manually process. This in combination with a user demand for a more frequent update of the ice conditions, also during the weekends, have made it important to focus the development on utilizing the high resolution Sentinel-1 data in an automatic sea ice concentration analysis. The algorithm developed here is based on a multi sensor approach using an optimal interpolation to combine sea ice concentration products derived from Sentinel-1 and passive microwave data from AMSR2. The Sentinel-1 data is classified with a Bayesian SAR classification algorithm using data in extra wide mode dual polarization (HH/HV) to separate ice and water in the full 40x40 meter spatial resolution. From the classification of ice/water the sea ice concentration is estimated by calculating amount of ice within an area of 1x1 km. The AMSR2 sea ice concentration are produced as part of the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) project and utilize the 89 GHz channel to produce a concentration product with a 3km spatial resolution. Results from the automatic classification will be presented.

Sensing Models and Sensor Network Architectures for Transport Infrastructure Monitoring in Smart Cities

NASA Astrophysics Data System (ADS)

Simonis, Ingo

2015-04-01

Transport infrastructure monitoring and analysis is one of the focus areas in the context of smart cities. With the growing number of people moving into densely populated urban metro areas, precise tracking of moving people and goods is the basis for profound decision-making and future planning. With the goal of defining optimal extensions and modifications to existing transport infrastructures, multi-modal transport has to be monitored and analysed. This process is performed on the basis of sensor networks that combine a variety of sensor models, types, and deployments within the area of interest. Multi-generation networks, consisting of a number of sensor types and versions, are causing further challenges for the integration and processing of sensor observations. These challenges are not getting any smaller with the development of the Internet of Things, which brings promising opportunities, but is currently stuck in a type of protocol war between big industry players from both the hardware and network infrastructure domain. In this paper, we will highlight how the OGC suite of standards, with the Sensor Web standards developed by the Sensor Web Enablement Initiative together with the latest developments by the Sensor Web for Internet of Things community can be applied to the monitoring and improvement of transport infrastructures. Sensor Web standards have been applied in the past to pure technical domains, but need to be broadened now in order to meet new challenges. Only cross domain approaches will allow to develop satisfying transport infrastructure approaches that take into account requirements coming form a variety of sectors such as tourism, administration, transport industry, emergency services, or private people. The goal is the development of interoperable components that can be easily integrated within data infrastructures and follow well defined information models to allow robust processing.

Interpreting Mobile and Handheld Air Sensor Readings in Relation to Air Quality Standards and Health Effect Reference Values: Tackling the Challenges.

PubMed

Woodall, George M; Hoover, Mark D; Williams, Ronald; Benedict, Kristen; Harper, Martin; Soo, Jhy-Charm; Jarabek, Annie M; Stewart, Michael J; Brown, James S; Hulla, Janis E; Caudill, Motria; Clements, Andrea L; Kaufman, Amanda; Parker, Alison J; Keating, Martha; Balshaw, David; Garrahan, Kevin; Burton, Laureen; Batka, Sheila; Limaye, Vijay S; Hakkinen, Pertti J; Thompson, Bob

2017-01-01

The US Environmental Protection Agency (EPA) and other federal agencies face a number of challenges in interpreting and reconciling short-duration (seconds to minutes) readings from mobile and handheld air sensors with the longer duration averages (hours to days) associated with the National Ambient Air Quality Standards (NAAQS) for the criteria pollutants-particulate matter (PM), ozone, carbon monoxide, lead, nitrogen oxides, and sulfur oxides. Similar issues are equally relevant to the hazardous air pollutants (HAPs) where chemical-specific health effect reference values are the best indicators of exposure limits; values which are often based on a lifetime of continuous exposure. A multi-agency, staff-level Air Sensors Health Group (ASHG) was convened in 2013. ASHG represents a multi-institutional collaboration of Federal agencies devoted to discovery and discussion of sensor technologies, interpretation of sensor data, defining the state of sensor-related science across each institution, and provides consultation on how sensors might effectively be used to meet a wide range of research and decision support needs. ASHG focuses on several fronts: improving the understanding of what hand-held sensor technologies may be able to deliver; communicating what hand-held sensor readings can provide to a number of audiences; the challenges of how to integrate data generated by multiple entities using new and unproven technologies; and defining best practices in communicating health-related messages to various audiences. This review summarizes the challenges, successes, and promising tools of those initial ASHG efforts and Federal agency progress on crafting similar products for use with other NAAQS pollutants and the HAPs. NOTE: The opinions expressed are those of the authors and do not necessary represent the opinions of their Federal Agencies or the US Government. Mention of product names does not constitute endorsement.

Monitoring of Carbon Fiber-Reinforced Old Timber Beams via Strain and Multiresonant Acoustic Emission Sensors

PubMed Central

Rescalvo, Francisco J.; Valverde-Palacios, Ignacio; Gallego, Antolino

2018-01-01

This paper proposes the monitoring of old timber beams with natural defects (knots, grain deviations, fissures and wanes), reinforced using carbon composite materials (CFRP). Reinforcement consisted of the combination of a CFRP laminate strip and a carbon fabric discontinuously wrapping the timber element. Monitoring considered the use and comparison of two types of sensors: strain gauges and multi-resonant acoustic emission (AE) sensors. Results demonstrate that: (1) the mechanical behavior of the beams can be considerably improved by means of the use of CFRP (160% in bending load capacity and 90% in stiffness); (2) Acoustic emission sensors provide comparable information to strain gauges. This fact points to the great potential of AE techniques for in-service damage assessment in real wood structures. PMID:29673155

Monitoring of Carbon Fiber-Reinforced Old Timber Beams via Strain and Multiresonant Acoustic Emission Sensors.

PubMed

Rescalvo, Francisco J; Valverde-Palacios, Ignacio; Suarez, Elisabet; Roldán, Andrés; Gallego, Antolino

2018-04-17

This paper proposes the monitoring of old timber beams with natural defects (knots, grain deviations, fissures and wanes), reinforced using carbon composite materials (CFRP). Reinforcement consisted of the combination of a CFRP laminate strip and a carbon fabric discontinuously wrapping the timber element. Monitoring considered the use and comparison of two types of sensors: strain gauges and multi-resonant acoustic emission (AE) sensors. Results demonstrate that: (1) the mechanical behavior of the beams can be considerably improved by means of the use of CFRP (160% in bending load capacity and 90% in stiffness); (2) Acoustic emission sensors provide comparable information to strain gauges. This fact points to the great potential of AE techniques for in-service damage assessment in real wood structures.

The SAVEMEDCOASTS Project

NASA Astrophysics Data System (ADS)

Anzidei, Marco; Patias, Petros; Forlenza, Giovanna; Trivigno, Maria Lucia; Michetti, Melania; Torresan, Silvia; Loizidou, Xenia; Petousis, Thanos; Doumaz, Fawzi; Lorito, Stefano; Brunori, Carlo Alberto; Pesci, Arianna; Carmisciano, Cosmo

2017-04-01

The SAVEMEDCOASTS Project (Sea Level Rise Scenarios along the Mediterranean Coasts), focuses on the Prevention Priority program of the European Commission ECHO A.5 "Civil protection policy, Prevention, Preparedness and Disaster Risk Reduction" and aims to respond to the need for people and assets prevention from natural disasters in Mediterranean coastal areas undergoing to increasing sea level rise and climate change impacts. The goals of the project are: i) to support civil protection at different levels and with different tools and methods to produce exhaustive risk assessments for different periods; ii) to improve governance and raise community awareness towards the impacts of sea level rise and related hazard; iii) to foster the cooperation amongst science, affected communities and civil protection organizations within and between targeted Mediterranean areas. Advanced methods are implied to develop multi-hazard assessments and existing databases for low-lying coastal areas already below or at less than 1 m above sea level, characterized by high economic and environmental value. The effects of sea level rise are assessed by mapping the multi-temporal scenarios of the inland extension of marine flooding and coastline position up to 2100, also temporarily increased during storms or tsunamis. They will result from i) the best available high resolution Digital Terrain Models (DTM); ii) known rates of land subsidence and iii) local sea level rise estimates. Finally, information is transferred to society, policy makers and stakeholders through an open web platform populated with collected information, videos and photo galleries, project results and guidelines. Here we show the strategy and goals of the SAVEMEDCOASTS Project.

Bayesian Hierarchical Air-Sea Interaction Modeling: Application to the Labrador Sea

NASA Technical Reports Server (NTRS)

Niiler, Pearn P.

2002-01-01

The objectives are to: 1) Organize data from 26 MINIMET drifters in the Labrador Sea, including sensor calibration and error checking of ARGOS transmissions. 2) Produce wind direction, barometer, and sea surface temperature time series. In addition, provide data from historical file of 150 SHARP drifters in the Labrador Sea. 3) Work with data interpretation and data-modeling assimilation issues.

High accuracy navigation information estimation for inertial system using the multi-model EKF fusing adams explicit formula applied to underwater gliders.

PubMed

Huang, Haoqian; Chen, Xiyuan; Zhang, Bo; Wang, Jian

2017-01-01

The underwater navigation system, mainly consisting of MEMS inertial sensors, is a key technology for the wide application of underwater gliders and plays an important role in achieving high accuracy navigation and positioning for a long time of period. However, the navigation errors will accumulate over time because of the inherent errors of inertial sensors, especially for MEMS grade IMU (Inertial Measurement Unit) generally used in gliders. The dead reckoning module is added to compensate the errors. In the complicated underwater environment, the performance of MEMS sensors is degraded sharply and the errors will become much larger. It is difficult to establish the accurate and fixed error model for the inertial sensor. Therefore, it is very hard to improve the accuracy of navigation information calculated by sensors. In order to solve the problem mentioned, the more suitable filter which integrates the multi-model method with an EKF approach can be designed according to different error models to give the optimal estimation for the state. The key parameters of error models can be used to determine the corresponding filter. The Adams explicit formula which has an advantage of high precision prediction is simultaneously fused into the above filter to achieve the much more improvement in attitudes estimation accuracy. The proposed algorithm has been proved through theory analyses and has been tested by both vehicle experiments and lake trials. Results show that the proposed method has better accuracy and effectiveness in terms of attitudes estimation compared with other methods mentioned in the paper for inertial navigation applied to underwater gliders. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Linear FBG Temperature Sensor Interrogation with Fabry-Perot ITU Multi-wavelength Reference.

PubMed

Park, Hyoung-Jun; Song, Minho

2008-10-29

The equidistantly spaced multi-passbands of a Fabry-Perot ITU filter are used as an efficient multi-wavelength reference for fiber Bragg grating sensor demodulation. To compensate for the nonlinear wavelength tuning effect in the FBG sensor demodulator, a polynomial fitting algorithm was applied to the temporal peaks of the wavelength-scanned ITU filter. The fitted wavelength values are assigned to the peak locations of the FBG sensor reflections, obtaining constant accuracy, regardless of the wavelength scan range and frequency. A linearity error of about 0.18% against a reference thermocouple thermometer was obtained with the suggested method.

SeaWiFS technical report series. Volume 5: Ocean optics protocols for SeaWiFS validation

NASA Technical Reports Server (NTRS)

Mueller, James L.; Austin, Roswell W.; Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor)

1992-01-01

Protocols are presented for measuring optical properties, and other environmental variables, to validate the radiometric performance of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and to develop and validate bio-optical algorithms for use with SeaWiFS data. The protocols are intended to establish foundations for a measurement strategy to verify the challenging SeaWiFS accuracy goals of 5 percent in water-leaving radiances and 35 percent in chlorophyll alpha concentration. The protocols first specify the variables which must be measured, and briefly review rationale. Subsequent chapters cover detailed protocols for instrument performance specifications, characterizing and calibration instruments, methods of making measurements in the field, and methods of data analysis. These protocols were developed at a workshop sponsored by the SeaWiFS Project Office (SPO) and held at the Naval Postgraduate School in Monterey, California (9-12 April, 1991). This report is the proceedings of that workshop, as interpreted and expanded by the authors and reviewed by workshop participants and other members of the bio-optical research community. The protocols are a first prescription to approach unprecedented measurement accuracies implied by the SeaWiFS goals, and research and development are needed to improve the state-of-the-art in specific areas. The protocols should be periodically revised to reflect technical advances during the SeaWiFS Project cycle.

SeaWiFS Technical Report Series. Volume 38; SeaWiFS Calibration and Validation Quality Control Procedures

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); McClain, Charles R.; Darzi, Michael; Barnes, Robert A.; Eplee, Robert E.; Firestone, James K.; Patt, Frederick S.; Robinson, Wayne D.; Schieber, Brian D.;

Using Multi-Angle WorldView-2 Imagery to Determine Ocean Depth Near Oahu, Hawaii

DTIC Science & Technology

2012-09-01

Reflection geometry used in the definition of BRDF (From McConnon [2010...Visible/InfraRed Imaging Spectrometer BRDF : Bidirectional Reflectance Distribution Function DHMs: Digital Height Maps DNs: Digital Numbers EM...navigation and fisheries management, and are also helpful for improving models of ocean circulation, air-sea interaction, weather forecasting, and

Implementation of Barcelona, L'estartit and Ibiza Sites for Altimeter Calibration

NASA Astrophysics Data System (ADS)

Martinez-Benjamin, J. J.; Gili, J.; Lopez, R.; Tapia, A.; Bosch, E.; Perez, B.; Pros, F.

2012-12-01

A marine campaign to compute the sea surface data along the Spanish Mediterranean coastline and Balearic Islands is being prepared for 2013. Jason-2 (period ~10 days) and Saral/AltiKa (period of 35 days and expected launch in 2012) altimetric data and on-board GPS data will be used. Many GPS Buoy sessions along the ship route will be performed.Sea height estimates (instantaneous and mean sea levels) will be compared. Recently some geodetic improvements has been made in specific coastal spanish sites in the NW Mediterranean Sea for monitoring sea level. The goal is to maintain and improve the quality of the observation of the sea level change in the three sites. The information is coming from Puertos del Estado www.puertos.es L'Estartit tide gauge has been co-located with geodetic techniques (GPS measurements of XU, Utilitary Network, and XdA, Levelling Network,) and it is tied to the SPGIC (Integrated Geodetic Positioning System of Catalonia) project of the Cartographic Institute of Catalunya (ICC). In the past three calibration campaigns for Topex/Poseidon and Jason-1 in March 1999, August 2000 and July 2002 near Cape of Begur. At Barcelona harbour there is one MIROS radar tide gauge belonging to Puertos del Estado (Spanish Harbours).The radar sensor is over the water surface, on a L-shaped structure which elevates it a few meters above the quay shelf. 1-min data are transmitted to the ENAGAS Control Center by cable and then sent each 1 min to Puertos del Estado by e-mail. The information includes wave forescast (mean period, significant wave height, sea level, etc.This sensor also measures agitation and sends wave parameters each 20 min. There is a GPS station Leica Geosystems GRX1200 GG Pro and antenna 1202. Bathymetric campaigns inside the harbour have been made. At Ibiza site new measurements and levelling between the GPS reference station and a Radar MIROS, both from Puertos del Estado, has been made recently. A calibration campaign for Jason-1 was made in June 2003 in the Ibiza area, main calibration site. The presentation is directed to the description of the actual situation of the geodetic infrastructure of Barcelona, l'Estartit sites for sea level determination and complementing Ibiza site for a new altimeter calibration campaign of Jason-2 and Saral/AltiKa satellites to be made in 2013. Specifications of the new marine calibration campaign will be presented.

Modis, SeaWIFS, and Pathfinder funded activities

NASA Technical Reports Server (NTRS)

Evans, Robert H.

1995-01-01

MODIS (Moderate Resolution Imaging Spectrometer), SeaWIFS (Sea-viewing Wide Field Sensor), Pathfinder, and DSP (Digital Signal Processor) objectives are summarized. An overview of current progress is given for the automatic processing database, client/server status, matchup database, and DSP support.

Cryosphere Sensor Webs With The Autonomous Sciencecraft Experiment

NASA Astrophysics Data System (ADS)

Scharenbroich, L.; Doggett, T.; Kratz, T.; Castano, R.; Chien, S.; Davies, A. G.; Tran, D.; Mazzoni, D.

2006-12-01

Autonomous sensor-webs are being deployed as part of the Autonomous Sciencecraft Experiment [1], whereby observations using the Hyperion instrument [2] on-board Earth Observing-1 (EO-1 are triggered by either ground sensors or by near-real-time analysis of data from other space-based sensors. In the realm of cryosphere monitoring, one sensor-web has been set up pairing EO-1 with a sensor buoy [3] deployed in Sparkling Lake, one of several lakes in northern Wisconsin monitored by University of Wisconsin's Trout Lake Station. A Support Vector Machine (SVM) classifier was trained on historical thermistor chain data with manually recorded ice-in and ice-out times and used to trigger Hyperion observations of the Trout Lake area during spring thaw and winter freeze in 2005. A second sensor-web is being developed using near-real time sea ice data products, based on Department of Defense meteorological satellites, available from the National Snow and Ice Data Center (NSIDC) [4]. Once operational, this sensor web will trigger Hyperion observations of pre-defined targets in the Arctic and Antarctic where regional resolution data shows sea ice formation or break up. [1] Chien et al. (2005), An autonomous earth-observing sensor-web, IEEE Intelligent Systems, [2] Pearlman et al. (2003), Hyperion, a space-based imaging spectrometer, IEEE Trans. Geosci. Rem. Sens., 41(6), [3] Kratz, T. et al. (in press) Toward a Global Lake Ecological Observatory Network, Proceedings of the Karelian Institute, [4] Cavalieri et al. (1999) Near real-time DMSP SSM/I daily polar gridded sea ice concentrations, National Snow and Ice Data Center. Digital Media.

A Passive Wireless Multi-Sensor SAW Technology Device and System Perspectives

PubMed Central

Malocha, Donald C.; Gallagher, Mark; Fisher, Brian; Humphries, James; Gallagher, Daniel; Kozlovski, Nikolai

2013-01-01

This paper will discuss a SAW passive, wireless multi-sensor system under development by our group for the past several years. The device focus is on orthogonal frequency coded (OFC) SAW sensors, which use both frequency diversity and pulse position reflectors to encode the device ID and will be briefly contrasted to other embodiments. A synchronous correlator transceiver is used for the hardware and post processing and correlation techniques of the received signal to extract the sensor information will be presented. Critical device and system parameters addressed include encoding, operational range, SAW device parameters, post-processing, and antenna-SAW device integration. A fully developed 915 MHz OFC SAW multi-sensor system is used to show experimental results. The system is based on a software radio approach that provides great flexibility for future enhancements and diverse sensor applications. Several different sensor types using the OFC SAW platform are shown. PMID:23666124

An underwater optical wireless communication network

NASA Astrophysics Data System (ADS)

Arnon, Shlomi

2009-08-01

The growing need for underwater observation and sub-sea monitoring systems has stimulated considerable interest in advancing the enabling technologies of underwater wireless communication and underwater sensor networks. This communication technology is expected to play an important role in investigating climate change, in monitoring biological, bio-geochemical, evolutionary and ecological changes in the sea, ocean and lake environments and in helping to control and maintain oil production facilities and harbors using unmanned underwater vehicles (UUVs), submarines, ships, buoys, and divers. However, the present technology of underwater acoustic communication cannot provide the high data rate required to investigate and monitor these environments and facilities. Optical wireless communication has been proposed as the best alternative to meet this challenge. We present models of three kinds of optical wireless communication links a) a line-of-sight link, b) a modulating retro-reflector link and c) a reflective link, all of which can provide the required data rate. We analyze the link performance based on these models. From the analysis, it is clear that as the water absorption increases, the communication performance decreases dramatically for the three link types. However, by using the scattered lighted it was possible to mitigate this decrease in some cases. We conclude from the analysis that a high data rate underwater optical wireless network is a feasible solution for emerging applications such as UUV to UUV links and networks of sensors, and extended ranges in these applications could be achieved by applying a multi-hop concept.

Lensless transport-of-intensity phase microscopy and tomography with a color LED matrix

NASA Astrophysics Data System (ADS)

Zuo, Chao; Sun, Jiasong; Zhang, Jialin; Hu, Yan; Chen, Qian

2015-07-01

We demonstrate lens-less quantitative phase microscopy and diffraction tomography based on a compact on-chip platform, using only a CMOS image sensor and a programmable color LED array. Based on multi-wavelength transport-of- intensity phase retrieval and multi-angle illumination diffraction tomography, this platform offers high quality, depth resolved images with a lateral resolution of ˜3.7μm and an axial resolution of ˜5μm, over wide large imaging FOV of 24mm2. The resolution and FOV can be further improved by using a larger image sensors with small pixels straightforwardly. This compact, low-cost, robust, portable platform with a decent imaging performance may offer a cost-effective tool for telemedicine needs, or for reducing health care costs for point-of-care diagnostics in resource-limited environments.

Multi-Spectral Image Analysis for Improved Space Object Characterization

NASA Astrophysics Data System (ADS)

Duggin, M.; Riker, J.; Glass, W.; Bush, K.; Briscoe, D.; Klein, M.; Pugh, M.; Engberg, B.

The Air Force Research Laboratory (AFRL) is studying the application and utility of various ground based and space-based optical sensors for improving surveillance of space objects in both Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO). At present, ground-based optical and radar sensors provide the bulk of remotely sensed information on satellites and space debris, and will continue to do so into the foreseeable future. However, in recent years, the Space Based Visible (SBV) sensor was used to demonstrate that a synthesis of space-based visible data with ground-based sensor data could provide enhancements to information obtained from any one source in isolation. The incentives for space-based sensing include improved spatial resolution due to the absence of atmospheric effects and cloud cover and increased flexibility for observations. Though ground-based optical sensors can use adaptive optics to somewhat compensate for atmospheric turbulence, cloud cover and absorption are unavoidable. With recent advances in technology, we are in a far better position to consider what might constitute an ideal system to monitor our surroundings in space. This work has begun at the AFRL using detailed optical sensor simulations and analysis techniques to explore the trade space involved in acquiring and processing data from a variety of hypothetical space-based and ground-based sensor systems. In this paper, we briefly review the phenomenology and trade space aspects of what might be required in order to use multiple band-passes, sensor characteristics, and observation and illumination geometries to increase our awareness of objects in space.

Optical Sensors for Planetary Radiant Energy (OSPREy): Calibration and Validation of Current and Next-Generation NASA Missions

NASA Technical Reports Server (NTRS)

Hooker, Stanford B.; Bernhard, Germar; Morrow, John H.; Booth, Charles R.; Comer, Thomas; Lind, Randall N.; Quang, Vi

2012-01-01

A principal objective of the Optical Sensors for Planetary Radiance Energy (OSPREy) activity is to establish an above-water radiometer system as a lower-cost alternative to existing in-water systems for the collection of ground-truth observations. The goal is to be able to make high-quality measurements satisfying the accuracy requirements for the vicarious calibration and algorithm validation of next-generation satellites that make ocean color and atmospheric measurements. This means the measurements will have a documented uncertainty satisfying the established performance metrics for producing climate-quality data records. The OSPREy approach is based on enhancing commercial-off-the-shelf fixed-wavelength and hyperspectral sensors to create hybridspectral instruments with an improved accuracy and spectral resolution, as well as a dynamic range permitting sea, Sun, sky, and Moon observations. Greater spectral diversity in the ultraviolet (UV) will be exploited to separate the living and nonliving components of marine ecosystems; UV bands will also be used to flag and improve atmospheric correction algorithms in the presence of absorbing aerosols. The short-wave infrared (SWIR) is expected to improve atmospheric correction, because the ocean is radiometrically blacker at these wavelengths. This report describes the development of the sensors, including unique capabilities like three-axis polarimetry; the documented uncertainty will be presented in a subsequent report.

Improved Satellite Estimation of Near-Surface Humidity Using Vertical Water Vapor Profile Information

NASA Astrophysics Data System (ADS)

Tomita, H.; Hihara, T.; Kubota, M.

2018-01-01

Near-surface air-specific humidity is a key variable in the estimation of air-sea latent heat flux and evaporation from the ocean surface. An accurate estimation over the global ocean is required for studies on global climate, air-sea interactions, and water cycles. Current remote sensing techniques are problematic and a major source of errors for flux and evaporation. Here we propose a new method to estimate surface humidity using satellite microwave radiometer instruments, based on a new finding about the relationship between multichannel brightness temperatures measured by satellite sensors, surface humidity, and vertical moisture structure. Satellite estimations using the new method were compared with in situ observations to evaluate this method, confirming that it could significantly improve satellite estimations with high impact on satellite estimation of latent heat flux. We recommend the adoption of this method for any satellite microwave radiometer observations.

Multispectral simulation environment for modeling low-light-level sensor systems

NASA Astrophysics Data System (ADS)

Ientilucci, Emmett J.; Brown, Scott D.; Schott, John R.; Raqueno, Rolando V.

1998-11-01

Image intensifying cameras have been found to be extremely useful in low-light-level (LLL) scenarios including military night vision and civilian rescue operations. These sensors utilize the available visible region photons and an amplification process to produce high contrast imagery. It has been demonstrated that processing techniques can further enhance the quality of this imagery. For example, fusion with matching thermal IR imagery can improve image content when very little visible region contrast is available. To aid in the improvement of current algorithms and the development of new ones, a high fidelity simulation environment capable of producing radiometrically correct multi-band imagery for low- light-level conditions is desired. This paper describes a modeling environment attempting to meet these criteria by addressing the task as two individual components: (1) prediction of a low-light-level radiance field from an arbitrary scene, and (2) simulation of the output from a low- light-level sensor for a given radiance field. The radiance prediction engine utilized in this environment is the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model which is a first principles based multi-spectral synthetic image generation model capable of producing an arbitrary number of bands in the 0.28 to 20 micrometer region. The DIRSIG model is utilized to produce high spatial and spectral resolution radiance field images. These images are then processed by a user configurable multi-stage low-light-level sensor model that applies the appropriate noise and modulation transfer function (MTF) at each stage in the image processing chain. This includes the ability to reproduce common intensifying sensor artifacts such as saturation and 'blooming.' Additionally, co-registered imagery in other spectral bands may be simultaneously generated for testing fusion and exploitation algorithms. This paper discusses specific aspects of the DIRSIG radiance prediction for low- light-level conditions including the incorporation of natural and man-made sources which emphasizes the importance of accurate BRDF. A description of the implementation of each stage in the image processing and capture chain for the LLL model is also presented. Finally, simulated images are presented and qualitatively compared to lab acquired imagery from a commercial system.

Network Coding on Heterogeneous Multi-Core Processors for Wireless Sensor Networks

PubMed Central

Kim, Deokho; Park, Karam; Ro, Won W.

2011-01-01

While network coding is well known for its efficiency and usefulness in wireless sensor networks, the excessive costs associated with decoding computation and complexity still hinder its adoption into practical use. On the other hand, high-performance microprocessors with heterogeneous multi-cores would be used as processing nodes of the wireless sensor networks in the near future. To this end, this paper introduces an efficient network coding algorithm developed for the heterogenous multi-core processors. The proposed idea is fully tested on one of the currently available heterogeneous multi-core processors referred to as the Cell Broadband Engine. PMID:22164053

Seasonal-to-decadal predictability in the Nordic Seas and Arctic with the Norwegian Climate Prediction Model

NASA Astrophysics Data System (ADS)

Counillon, Francois; Kimmritz, Madlen; Keenlyside, Noel; Wang, Yiguo; Bethke, Ingo

2017-04-01

The Norwegian Climate Prediction Model combines the Norwegian Earth System Model and the Ensemble Kalman Filter data assimilation method. The prediction skills of different versions of the system (with 30 members) are tested in the Nordic Seas and the Arctic region. Comparing the hindcasts branched from a SST-only assimilation run with a free ensemble run of 30 members, we are able to dissociate the predictability rooted in the external forcing from the predictability harvest from SST derived initial conditions. The latter adds predictability in the North Atlantic subpolar gyre and the Nordic Seas regions and overall there is very little degradation or forecast drift. Combined assimilation of SST and T-S profiles further improves the prediction skill in the Nordic Seas and into the Arctic. These lead to multi-year predictability in the high-latitudes. Ongoing developments of strongly coupled assimilation (ocean and sea ice) of ice concentration in idealized twin experiment will be shown, as way to further enhance prediction skill in the Arctic.

Using Direct Policy Search to Identify Robust Strategies in Adapting to Uncertain Sea Level Rise and Storm Surge

NASA Astrophysics Data System (ADS)

Garner, G. G.; Keller, K.

2017-12-01

Sea-level rise poses considerable risks to coastal communities, ecosystems, and infrastructure. Decision makers are faced with deeply uncertain sea-level projections when designing a strategy for coastal adaptation. The traditional methods have provided tremendous insight into this decision problem, but are often silent on tradeoffs as well as the effects of tail-area events and of potential future learning. Here we reformulate a simple sea-level rise adaptation model to address these concerns. We show that Direct Policy Search yields improved solution quality, with respect to Pareto-dominance in the objectives, over the traditional approach under uncertain sea-level rise projections and storm surge. Additionally, the new formulation produces high quality solutions with less computational demands than the traditional approach. Our results illustrate the utility of multi-objective adaptive formulations for the example of coastal adaptation, the value of information provided by observations, and point to wider-ranging application in climate change adaptation decision problems.

STARR: shortwave-targeted agile Raman robot for the detection and identification of emplaced explosives

NASA Astrophysics Data System (ADS)

Gomer, Nathaniel R.; Gardner, Charles W.

2014-05-01

In order to combat the threat of emplaced explosives (land mines, etc.), ChemImage Sensor Systems (CISS) has developed a multi-sensor, robot mounted sensor capable of identification and confirmation of potential threats. The system, known as STARR (Shortwave-infrared Targeted Agile Raman Robot), utilizes shortwave infrared spectroscopy for the identification of potential threats, combined with a visible short-range standoff Raman hyperspectral imaging (HSI) system for material confirmation. The entire system is mounted onto a Talon UGV (Unmanned Ground Vehicle), giving the sensor an increased area search rate and reducing the risk of injury to the operator. The Raman HSI system utilizes a fiber array spectral translator (FAST) for the acquisition of high quality Raman chemical images, allowing for increased sensitivity and improved specificity. An overview of the design and operation of the system will be presented, along with initial detection results of the fusion sensor.

ABS-FishCount: An Agent-Based Simulator of Underwater Sensors for Measuring the Amount of Fish

PubMed Central

2017-01-01

Underwater sensors provide one of the possibilities to explore oceans, seas, rivers, fish farms and dams, which all together cover most of our planet’s area. Simulators can be helpful to test and discover some possible strategies before implementing these in real underwater sensors. This speeds up the development of research theories so that these can be implemented later. In this context, the current work presents an agent-based simulator for defining and testing strategies for measuring the amount of fish by means of underwater sensors. The current approach is illustrated with the definition and assessment of two strategies for measuring fish. One of these two corresponds to a simple control mechanism, while the other is an experimental strategy and includes an implicit coordination mechanism. The experimental strategy showed a statistically significant improvement over the control one in the reduction of errors with a large Cohen’s d effect size of 2.55. PMID:29137165

Multi-decadal trend and space-time variability of sea level over the Indian Ocean since the 1950s: impact of decadal climate modes

NASA Astrophysics Data System (ADS)

Han, W.; Stammer, D.; Meehl, G. A.; Hu, A.; Sienz, F.

2016-12-01

Sea level varies on decadal and multi-decadal timescales over the Indian Ocean. The variations are not spatially uniform, and can deviate considerably from the global mean sea level rise (SLR) due to various geophysical processes. One of these processes is the change of ocean circulation, which can be partly attributed to natural internal modes of climate variability. Over the Indian Ocean, the most influential climate modes on decadal and multi-decadal timescales are the Interdecadal Pacific Oscillation (IPO) and decadal variability of the Indian Ocean dipole (IOD). Here, we first analyze observational datasets to investigate the impacts of IPO and IOD on spatial patterns of decadal and interdecadal (hereafter decal) sea level variability & multi-decadal trend over the Indian Ocean since the 1950s, using a new statistical approach of Bayesian Dynamical Linear regression Model (DLM). The Bayesian DLM overcomes the limitation of "time-constant (static)" regression coefficients in conventional multiple linear regression model, by allowing the coefficients to vary with time and therefore measuring "time-evolving (dynamical)" relationship between climate modes and sea level. For the multi-decadal sea level trend since the 1950s, our results show that climate modes and non-climate modes (the part that cannot be explained by climate modes) have comparable contributions in magnitudes but with different spatial patterns, with each dominating different regions of the Indian Ocean. For decadal variability, climate modes are the major contributors for sea level variations over most region of the tropical Indian Ocean. The relative importance of IPO and decadal variability of IOD, however, varies spatially. For example, while IOD decadal variability dominates IPO in the eastern equatorial basin (85E-100E, 5S-5N), IPO dominates IOD in causing sea level variations in the tropical southwest Indian Ocean (45E-65E, 12S-2S). To help decipher the possible contribution of external forcing to the multi-decadal sea level trend and decadal variability, we also analyze the model outputs from NCAR's Community Earth System Model (CESM) Large Ensemble Experiments, and compare the results with our observational analyses.

Application of Sensor Fusion to Improve Uav Image Classification

NASA Astrophysics Data System (ADS)

Jabari, S.; Fathollahi, F.; Zhang, Y.

2017-08-01

Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

Quantitative multi-modal NDT data analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heideklang, René; Shokouhi, Parisa

2014-02-18

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundantmore » information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity.« less

Improving a prediction system for oil spills in the Yellow Sea: effect of tides on subtidal flow.

PubMed

Kim, Chang-Sin; Cho, Yang-Ki; Choi, Byoung-Ju; Jung, Kyung Tae; You, Sung Hyup

2013-03-15

A multi-nested prediction system for the Yellow Sea using drifter trajectory simulations was developed to predict the movements of an oil spill after the MV Hebei Spirit accident. The speeds of the oil spill trajectories predicted by the model without tidal forcing were substantially faster than the observations; however, predictions taking into account the tides, including both tidal cycle and subtidal periods, were satisfactorily improved. Subtidal flow in the simulation without tides was stronger than in that with tides because of reduced frictional effects. Friction induced by tidal stress decelerated the southward subtidal flows driven by northwesterly winter winds along the Korean coast of the Yellow Sea. These results strongly suggest that in order to produce accurate predictions of oil spill trajectories, simulations must include tidal effects, such as variations within a tidal cycle and advections over longer time scales in tide-dominated areas. Copyright © 2012 Elsevier Ltd. All rights reserved.

DUACS: Toward High Resolution Sea Level Products

NASA Astrophysics Data System (ADS)

Faugere, Y.; Gerald, D.; Ubelmann, C.; Claire, D.; Pujol, M. I.; Antoine, D.; Desjonqueres, J. D.; Picot, N.

2016-12-01

The DUACS system produces, as part of the CNES/SALP project, and the Copernicus Marine Environment and Monitoring Service, high quality multimission altimetry Sea Level products for oceanographic applications, climate forecasting centers, geophysic and biology communities... These products consist in directly usable and easy to manipulate Level 3 (along-track cross-calibrated SLA) and Level 4 products (multiple sensors merged as maps or time series) and are available in global and regional version (Mediterranean Sea, Arctic, European Shelves …).The quality of the products is today limited by the altimeter technology "Low Resolution Mode" (LRM), and the lack of available observations. The launch of 2 new satellites in 2016, Jason-3 and Sentinel-3A, opens new perspectives. Using the global Synthetic Aperture Radar mode (SARM) coverage of S3A and optimizing the LRM altimeter processing (retracking, editing, ...) will allow us to fully exploit the fine-scale content of the altimetric missions. Thanks to this increase of real time altimetry observations we will also be able to improve Level-4 products by combining these new Level-3 products and new mapping methodology, such as dynamic interpolation. Finally these improvements will benefit to downstream products : geostrophic currents, Lagrangian products, eddy atlas… Overcoming all these challenges will provide major upgrades of Sea Level products to better fulfill user needs.

A Powerful Method of Measuring Sea Wave Spectra and their Direction

NASA Astrophysics Data System (ADS)

Blasi, Christoph; Mai, Stephan; Wilhelmi, Jens; Zenz, Theodor; Barjenbruch, Ulrich

2014-05-01

Besides the need of precise measurements of water levels of the sea, there is an increasing demand for assessing waves in height and direction for different purposes like sea-wave modelling and coastal engineering. The design of coastal structures such as piles, breakwaters, and offshore structures like wind farms must take account of the direction of the impacting waves. To date, records of wave directions are scarce. The reason for this might be the high costs of purchasing and operating such measuring devices. These are usually buoys, which require regular maintenance. Against this background, the German Federal Institute of Hydrology (BfG) developed a low-cost directional sea-wave monitoring system that is based on commercially available liquid-level radar sensors. These sensors have the advantage that they have no contact to the fluid, i.e. the corrosive sea water. The newly developed device was tested on two sites. One is the tide gauge 'Borkum Südstrand' that is located in the southern North Sea off the island of Borkum. The other one is the 'Research Platform FINO1' approximately 45 km north of the island of Borkum. The main focus of these tests is the comparison of the data measured by the radar-based system with those of a conventional Directional Wave Rider Buoy. The general conditions at the testing sites are good for the tests. At the tide gauge 'Borkum Südstrand' waves propagate in different directions, strongly influenced by the morphological conditions like shallow waters of the Wadden Seas and the coast of the island of Borkum. Whereas on the open sea, at the site FINO1, the full physical conditions of the sea state, like heavy storms etc. play an important role. To determine and measure the direction of waves, the device has to be able to assess the wave movements in two dimensions. Therefore, an array of several radar sensors is required. Radar sensors are widely used and well established in measuring water levels, e.g. in tanks and basins. They operate by emitting a chain of electromagnetic pulses at a frequency of 26 GHz twice per second and, in turn, detect the backscatter information from the water surface. As the travelling time of each pulse is proportional to the distance between water surface and sensor, the height of the water surface can be easily calculated. To obtain the directional information of the sea state, all four radar sensors in the array have to collect simultaneously the wave profiles at fixed points. The Wave Rider Buoy works in a completely different way. Here, the wave height is calculated by the double integration of the measured vertical acceleration. By correlating the three-dimensional motion data, which are gained from gravity-stabilized vertical and horizontal accelerometers, the directional wave spectrum can be derived. Data of both devices were collected and analysed. During the hurricane Xaver, extreme water levels and heavy sea hit the North Sea coast on 5 and 6 December 2013. The radar array at the testing site FINO1 measured wave heights in the order of 15.5 meters. Furthermore, it was possible to detect significant wave heights, the mean wave direction, and the spread of the sea state. For the first time the accuracy of the wave height distribution could be determined as well.

Application of zonal model on indoor air sensor network design

NASA Astrophysics Data System (ADS)

Chen, Y. Lisa; Wen, Jin

2007-04-01

Growing concerns over the safety of the indoor environment have made the use of sensors ubiquitous. Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is more informed by intuition and experience rather by systematic design. To develop a sensor system design methodology, a proper indoor airflow modeling approach is needed. Various indoor airflow modeling techniques, from complicated computational fluid dynamics approaches to simplified multi-zone approaches, exist in the literature. In this study, the effects of two airflow modeling techniques, multi-zone modeling technique and zonal modeling technique, on indoor air protection sensor system design are discussed. Common building attack scenarios, using a typical CBW agent, are simulated. Both multi-zone and zonal models are used to predict airflows and contaminant dispersion. Genetic Algorithm is then applied to optimize the sensor location and quantity. Differences in the sensor system design resulting from the two airflow models are discussed for a typical office environment and a large hall environment.

A novel cooperative localization algorithm using enhanced particle filter technique in maritime search and rescue wireless sensor network.

PubMed

Wu, Huafeng; Mei, Xiaojun; Chen, Xinqiang; Li, Junjun; Wang, Jun; Mohapatra, Prasant

2018-07-01

Maritime search and rescue (MSR) play a significant role in Safety of Life at Sea (SOLAS). However, it suffers from scenarios that the measurement information is inaccurate due to wave shadow effect when utilizing wireless Sensor Network (WSN) technology in MSR. In this paper, we develop a Novel Cooperative Localization Algorithm (NCLA) in MSR by using an enhanced particle filter method to reduce measurement errors on observation model caused by wave shadow effect. First, we take into account the mobility of nodes at sea to develop a motion model-Lagrangian model. Furthermore, we introduce both state model and observation model to constitute a system model for particle filter (PF). To address the impact of the wave shadow effect on the observation model, we develop an optimal parameter derived by Kullback-Leibler divergence (KLD) to mitigate the error. After the optimal parameter is acquired, an improved likelihood function is presented. Finally, the estimated position is acquired. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Pathways of Atlantic Waters in the Nordic seas: locally eddy-permitting ocean simulation in a global setup

NASA Astrophysics Data System (ADS)

Wekerle, C.; Wang, Q.; Danilov, S.; Jung, T.; Schourup-Kristensen, V.

2016-02-01

Atlantic Water (AW) passes through the Nordic Seas and enters the Arctic Ocean through the shallow Barents Sea and the deep Fram Strait. Since the 1990's, observations indicate a series of anomalously warm pulses of Atlantic Water that entered the Arctic Ocean. In fact, poleward oceanic heat transport may even increase in the future, which might have implications for the heat uptake in the Arctic Ocean as well as for the sea ice cover. The ability of models to faithfully simulate the pathway of the AW and accompanying dynamics is thus of high climate relevance. In this study, we explore the potential of a global multi-resolution sea ice-ocean model with a locally eddy-permitting resolution (around 4.5 km) in the Nordic seas region and Arctic Ocean in improving the representation of Atlantic Water inflow, and more broadly, the dynamics of the circulation in the Northern North Atlantic and Arctic. The simulation covers the time period 1969-2009. We find that locally increased resolution improves the localization and thickness of the Atlantic Water layer in the Nordic seas, compared with a 20 km resolution reference simulation. In particular, the inflow of Atlantic Waters through the Greenland Scotland Ridge and the narrow branches of the Norwegian Atlantic Current can be realistically represented. Lateral spreading due to simulated eddies essentially reduces the bias in the surface temperature. In addition, a qualitatively good agreement of the simulated eddy kinetic energy field with observations can be achieved. This study indicates that a substantial improvement in representing local ocean dynamics can be reached through the local refinement, which requires a rather moderate computational effort. The successful model assessment allows us to further investigate the variability and mechanisms behind Atlantic Water transport into the Arctic Ocean.

Integrating technologies for oil spill response in the SW Iberian coast

NASA Astrophysics Data System (ADS)

Janeiro, J.; Neves, A.; Martins, F.; Relvas, P.

2017-09-01

An operational oil spill modelling system developed for the SW Iberia Coast is used to investigate the relative importance of the different components and technologies integrating an oil spill monitoring and response structure. A backtrack of a CleanSeaNet oil detection in the region is used to demonstrate the concept. Taking advantage of regional operational products available, the system provides the necessary resolution to go from regional to coastal scales using a downscalling approach, while a multi-grid methodology allows the based oil spill model to span across model domains taking full advantage of the increasing resolution between the model grids. An extensive validation procedure using a multiplicity of sensors, with good spatial and temporal coverage, strengthens the operational system ability to accurately solve coastal scale processes. The model is validated using available trajectories from satellite-tracked drifters. Finally, a methodology is proposed to identifying potential origins for the CleanSeaNet oil detection, by combining model backtrack results with ship trajectories supplied by AIS was developed, including the error estimations found in the backtrack validation.

Coastal and mesoscale dynamics characterization combining glider and altimetry: case study over the Western Mediterranean Sea

NASA Astrophysics Data System (ADS)

Jerome, Bouffard; Pascual, Ananda; Ruiz, Simon; Isabelle Pujol, Marie; Faugere, Yannice; Larnicol, Gilles; Tintore, Joaquin

Satellite altimetry allows a direct computation of geostrophic velocity anomalies. However, conventional altimetry measurements remain largely spurious in coastal zone, due to several factors such as inaccurate geophysical corrections (e.g. atmospheric and tidal signals) as well as environmental issues (land contamination in the altimetric and radiometric footprints). At the present time and in the attempt of future relevant technologies (cf. SWOT satellite), experimen-tal coastal altimeter products are under development (XTRACK, PISTACH, COASTALT. . . ). The main efforts consist in the application of coastal-oriented corrections and the review of the data recovery strategies near the coast. The new coastal altimetric products need to be assessed with independent data before to be used in synergy with other measurements and fully exploited for scientific applications. This is the frame of this study as part of an intensive observational program conducted in the Western Mediterranean Sea. We present here the main outcomes resulting from the combination of coastal altimetry and gliders. Gliders -autonomous underwater vehicles -allow to provide precise and high resolution data complementary to altimetry (temperature, salinity, pressure, velocity. . . ) both at surface and over the whole water column. Since July 2007, several glider missions have been performed along Jason-1, Jason-2 and ENVISAT altimeters. The altimetric sea level anomalies have been processed from both standard and coastal-oriented strategies. Furthermore, new methodologies have also been developed in order to combine surface glider geostrophic velocities (derived from CTD measurements) with integrated currents estimated by the glider (derived from GPS locations every 6 hours). These approaches prove to be very efficient to improve the budget errors and homogenize the physical contents of altimetry and glider data. Further, the combined analysis of the two datasets provides interesting insights of the oceanic circulation characteristics at the regional scales. In summary, these studies highlight the relevance of multi-sensor approaches and the need of oceanic topography measurements at several spatial/temporal sampling requirements in view of the coastal and mesoscale dynamics characterizations.

Dynamic Range and Sensitivity Requirements of Satellite Ocean Color Sensors: Learning from the Past

NASA Technical Reports Server (NTRS)

Hu, Chuanmin; Feng, Lian; Lee, Zhongping; Davis, Curtiss O.; Mannino, Antonio; McClain, Charles R.; Franz, Bryan A.

2012-01-01

Sensor design and mission planning for satellite ocean color measurements requires careful consideration of the signal dynamic range and sensitivity (specifically here signal-to-noise ratio or SNR) so that small changes of ocean properties (e.g., surface chlorophyll-a concentrations or Chl) can be quantified while most measurements are not saturated. Past and current sensors used different signal levels, formats, and conventions to specify these critical parameters, making it difficult to make cross-sensor comparisons or to establish standards for future sensor design. The goal of this study is to quantify these parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers. Using measurements from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite (MODISA) under various solar zenith angles (SZAs), typical (L(sub typical)) and maximum (L(sub max)) at-sensor radiances from the visible to the shortwave IR were determined. The Ltypical values at an SZA of 45 deg were used as constraints to calculate SNRs of 10 multiband sensors at the same L(sub typical) radiance input and 2 hyperspectral sensors at a similar radiance input. The calculations were based on clear-water scenes with an objective method of selecting pixels with minimal cross-pixel variations to assure target homogeneity. Among the widely used ocean color sensors that have routine global coverage, MODISA ocean bands (1 km) showed 2-4 times higher SNRs than the Sea-viewing Wide Field-of-view Sensor (Sea-WiFS) (1 km) and comparable SNRs to the Medium Resolution Imaging Spectrometer (MERIS)-RR (reduced resolution, 1.2 km), leading to different levels of precision in the retrieved Chl data product. MERIS-FR (full resolution, 300 m) showed SNRs lower than MODISA and MERIS-RR with the gain in spatial resolution. SNRs of all MODISA ocean bands and SeaWiFS bands (except the SeaWiFS near-IR bands) exceeded those from prelaunch sensor specifications after adjusting the input radiance to L(sub typical). The tabulated L(sub typical), L(sub max), and SNRs of the various multiband and hyperspectral sensors under the same or similar radiance input provide references to compare sensor performance in product precision and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission currently being planned by the U.S. National Aeronautics and Space Administration (NASA).

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

PubMed Central

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464

Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

PubMed

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

Assessment of Closed-Loop Control Using Multi-Mode Sensor Fusion For a High Reynolds Number Transonic Jet

NASA Astrophysics Data System (ADS)

Low, Kerwin; Elhadidi, Basman; Glauser, Mark

2009-11-01

Understanding the different noise production mechanisms caused by the free shear flows in a turbulent jet flow provides insight to improve ``intelligent'' feedback mechanisms to control the noise. Towards this effort, a control scheme is based on feedback of azimuthal pressure measurements in the near field of the jet at two streamwise locations. Previous studies suggested that noise reduction can be achieved by azimuthal actuators perturbing the shear layer at the jet lip. The closed-loop actuation will be based on a low-dimensional Fourier representation of the hydrodynamic pressure measurements. Preliminary results show that control authority and reduction in the overall sound pressure level was possible. These results provide motivation to move forward with the overall vision of developing innovative multi-mode sensing methods to improve state estimation and derive dynamical systems. It is envisioned that estimating velocity-field and dynamic pressure information from various locations both local and in the far-field regions, sensor fusion techniques can be utilized to ascertain greater overall control authority.

Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic

NASA Astrophysics Data System (ADS)

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.-A.

2010-10-01

The retrieval of sea ice motion with the Maximum Cross-Correlation (MCC) method from low-resolution (10-15 km) spaceborne imaging sensors is challenged by a dominating quantization noise as the time span of displacement vectors is shortened. To allow investigating shorter displacements from these instruments, we introduce an alternative sea ice motion tracking algorithm that builds on the MCC method but relies on a continuous optimization step for computing the motion vector. The prime effect of this method is to effectively dampen the quantization noise, an artifact of the MCC. It allows for retrieving spatially smooth 48 h sea ice motion vector fields in the Arctic. Strategies to detect and correct erroneous vectors as well as to optimally merge several polarization channels of a given instrument are also described. A test processing chain is implemented and run with several active and passive microwave imagers (Advanced Microwave Scanning Radiometer-EOS (AMSR-E), Special Sensor Microwave Imager, and Advanced Scatterometer) during three Arctic autumn, winter, and spring seasons. Ice motion vectors are collocated to and compared with GPS positions of in situ drifters. Error statistics are shown to be ranging from 2.5 to 4.5 km (standard deviation for components of the vectors) depending on the sensor, without significant bias. We discuss the relative contribution of measurement and representativeness errors by analyzing monthly validation statistics. The 37 GHz channels of the AMSR-E instrument allow for the best validation statistics. The operational low-resolution sea ice drift product of the EUMETSAT OSI SAF (European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility) is based on the algorithms presented in this paper.

Development of a decision support system for monitoring, reporting and forecasting ecological conditions of the Appalachian Trail

USGS Publications Warehouse

Wang, Yeqiao; Nemani, Ramakrishna; Dieffenbach, Fred; Stolte, Kenneth; Holcomb, Glenn B.; Robinson, Matt; Reese, Casey C.; McNiff, Marcia; Duhaime, Roland; Tierney, Geri; Mitchell, Brian; August, Peter; Paton, Peter; LaBash, Charles

2010-01-01

This paper introduces a collaborative multi-agency effort to develop an Appalachian Trail (A.T.) MEGA-Transect Decision Support System (DSS) for monitoring, reporting and forecasting ecological conditions of the A.T. and the surrounding lands. The project is to improve decisionmaking on management of the A.T. by providing a coherent framework for data integration, status reporting and trend analysis. The A.T. MEGA-Transect DSS is to integrate NASA multi-platform sensor data and modeling through the Terrestrial Observation and Prediction System (TOPS) and in situ measurements from A.T. MEGA-Transect partners to address identified natural resource priorities and improve resource management decisions.

Hybrid organic–inorganic porous semiconductor transducer for multi-parameters sensing

PubMed Central

Caliò, Alessandro; Cassinese, Antonio; Casalino, Maurizio; Rea, Ilaria; Barra, Mario; Chiarella, Fabio; De Stefano, Luca

2015-01-01

Porous silicon (PSi) non-symmetric multi-layers are modified by organic molecular beam deposition of an organic semiconductor, namely the N,N′-1H,1H-perfluorobutyldicyanoperylene-carboxydi-imide (PDIF-CN2). Joule evaporation of PDIF-CN2 into the PSi sponge-like matrix not only improves but also adds transducing skills, making this solid-state device a dual signal sensor for chemical monitoring. PDIF-CN2 modified PSi optical microcavities show an increase of about five orders of magnitude in electric current with respect to the same bare device. This feature can be used to sense volatile substances. PDIF-CN2 also improves chemical resistance of PSi against alkaline and acid corrosion. PMID:26063814

Stretchable Dual-Capacitor Multi-Sensor for Touch-Curvature-Pressure-Strain Sensing.

PubMed

Jin, Hanbyul; Jung, Sungchul; Kim, Junhyung; Heo, Sanghyun; Lim, Jaeik; Park, Wonsang; Chu, Hye Yong; Bien, Franklin; Park, Kibog

2017-09-07

We introduce a new type of multi-functional capacitive sensor that can sense several different external stimuli. It is fabricated only with polydimethylsiloxane (PDMS) films and silver nanowire electrodes by using selective oxygen plasma treatment method without photolithography and etching processes. Differently from the conventional single-capacitor multi-functional sensors, our new multi-functional sensor is composed of two vertically-stacked capacitors (dual-capacitor). The unique dual-capacitor structure can detect the type and strength of external stimuli including curvature, pressure, strain, and touch with clear distinction, and it can also detect the surface-normal directionality of curvature, pressure, and touch. Meanwhile, the conventional single-capacitor sensor has ambiguity in distinguishing curvature and pressure and it can detect only the strength of external stimulus. The type, directionality, and strength of external stimulus can be determined based on the relative capacitance changes of the two stacked capacitors. Additionally, the logical flow reflected on a tree structure with its branches reaching the direction and strength of the corresponding external stimulus unambiguously is devised. This logical flow can be readily implemented in the sensor driving circuit if the dual-capacitor sensor is commercialized actually in the future.

Development of Advanced Signal Processing and Source Imaging Methods for Superparamagnetic Relaxometry

PubMed Central

Huang, Ming-Xiong; Anderson, Bill; Huang, Charles W.; Kunde, Gerd J.; Vreeland, Erika C.; Huang, Jeffrey W.; Matlashov, Andrei N.; Karaulanov, Todor; Nettles, Christopher P.; Gomez, Andrew; Minser, Kayla; Weldon, Caroline; Paciotti, Giulio; Harsh, Michael; Lee, Roland R.; Flynn, Edward R.

2017-01-01

Superparamagnetic Relaxometry (SPMR) is a highly sensitive technique for the in vivo detection of tumor cells and may improve early stage detection of cancers. SPMR employs superparamagnetic iron oxide nanoparticles (SPION). After a brief magnetizing pulse is used to align the SPION, SPMR measures the time decay of SPION using Super-conducting Quantum Interference Device (SQUID) sensors. Substantial research has been carried out in developing the SQUID hardware and in improving the properties of the SPION. However, little research has been done in the pre-processing of sensor signals and post-processing source modeling in SPMR. In the present study, we illustrate new pre-processing tools that were developed to: 1) remove trials contaminated with artifacts, 2) evaluate and ensure that a single decay process associated with bounded SPION exists in the data, 3) automatically detect and correct flux jumps, and 4) accurately fit the sensor signals with different decay models. Furthermore, we developed an automated approach based on multi-start dipole imaging technique to obtain the locations and magnitudes of multiple magnetic sources, without initial guesses from the users. A regularization process was implemented to solve the ambiguity issue related to the SPMR source variables. A procedure based on reduced chi-square cost-function was introduced to objectively obtain the adequate number of dipoles that describe the data. The new pre-processing tools and multi-start source imaging approach have been successfully evaluated using phantom data. In conclusion, these tools and multi-start source modeling approach substantially enhance the accuracy and sensitivity in detecting and localizing sources from the SPMR signals. Furthermore, multi-start approach with regularization provided robust and accurate solutions for a poor SNR condition similar to the SPMR detection sensitivity in the order of 1000 cells. We believe such algorithms will help establishing the industrial standards for SPMR when applying the technique in pre-clinical and clinical settings. PMID:28072579

Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS)

NASA Technical Reports Server (NTRS)

Rhothermel, Jeffry; Jones, W. D.; Dunkin, J. A.; Mccaul, E. W., Jr.

1993-01-01

This effort involves development of a calibrated, pulsed coherent CO2 Doppler lidar, followed by a carefully-planned and -executed program of multi-dimensional wind velocity and aerosol backscatter measurements from the NASA DC-8 research aircraft. The lidar, designated as the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS), will be applicable to two research areas. First, MACAWS will enable specialized measurements of atmospheric dynamical processes in the planetary boundary layer and free troposphere in geographic locations and over scales of motion not routinely or easily accessible to conventional sensors. The proposed observations will contribute fundamentally to a greater understanding of the role of the mesoscale, helping to improve predictive capabilities for mesoscale phenomena and to provide insights into improving model parameterizations of sub-grid scale processes within large-scale circulation models. As such, it has the potential to contribute uniquely to major, multi-institutional field programs planned for the mid 1990's. Second, MACAWS measurements can be used to reduce the degree of uncertainty in performance assessments and algorithm development for NASA's prospective Laser Atmospheric Wind Sounder (LAWS), which has no space-based instrument heritage. Ground-based lidar measurements alone are insufficient to address all of the key issues. To minimize costs, MACAWS is being developed cooperatively by the lidar remote sensing groups of the Jet Propulsion Laboratory, NOAA Wave Propagation Laboratory, and MSFC using existing lidar hardware and manpower resources. Several lidar components have already been exercised in previous airborne lidar programs (for example, MSFC Airborne Doppler Lidar System (ADLS) used in 1981,4 Severe Storms Wind Measurement Program; JPL Airborne Backscatter Lidar Experiment (ABLE) used in 1989,90 Global Backscatter Experiment Survey Missions). MSFC has been given responsibility for directing the overall program of instrument development and scientific measurement. The focus of current research and plans for next year are presented.

An SOI CMOS-Based Multi-Sensor MEMS Chip for Fluidic Applications.

PubMed

Mansoor, Mohtashim; Haneef, Ibraheem; Akhtar, Suhail; Rafiq, Muhammad Aftab; De Luca, Andrea; Ali, Syed Zeeshan; Udrea, Florin

2016-11-04

An SOI CMOS multi-sensor MEMS chip, which can simultaneously measure temperature, pressure and flow rate, has been reported. The multi-sensor chip has been designed keeping in view the requirements of researchers interested in experimental fluid dynamics. The chip contains ten thermodiodes (temperature sensors), a piezoresistive-type pressure sensor and nine hot film-based flow rate sensors fabricated within the oxide layer of the SOI wafers. The silicon dioxide layers with embedded sensors are relieved from the substrate as membranes with the help of a single DRIE step after chip fabrication from a commercial CMOS foundry. Very dense sensor packing per unit area of the chip has been enabled by using technologies/processes like SOI, CMOS and DRIE. Independent apparatuses were used for the characterization of each sensor. With a drive current of 10 µA-0.1 µA, the thermodiodes exhibited sensitivities of 1.41 mV/°C-1.79 mV/°C in the range 20-300 °C. The sensitivity of the pressure sensor was 0.0686 mV/(V excit kPa) with a non-linearity of 0.25% between 0 and 69 kPa above ambient pressure. Packaged in a micro-channel, the flow rate sensor has a linearized sensitivity of 17.3 mV/(L/min) -0.1 in the tested range of 0-4.7 L/min. The multi-sensor chip can be used for simultaneous measurement of fluid pressure, temperature and flow rate in fluidic experiments and aerospace/automotive/biomedical/process industries.

An SOI CMOS-Based Multi-Sensor MEMS Chip for Fluidic Applications †

PubMed Central

Mansoor, Mohtashim; Haneef, Ibraheem; Akhtar, Suhail; Rafiq, Muhammad Aftab; De Luca, Andrea; Ali, Syed Zeeshan; Udrea, Florin

2016-01-01

An SOI CMOS multi-sensor MEMS chip, which can simultaneously measure temperature, pressure and flow rate, has been reported. The multi-sensor chip has been designed keeping in view the requirements of researchers interested in experimental fluid dynamics. The chip contains ten thermodiodes (temperature sensors), a piezoresistive-type pressure sensor and nine hot film-based flow rate sensors fabricated within the oxide layer of the SOI wafers. The silicon dioxide layers with embedded sensors are relieved from the substrate as membranes with the help of a single DRIE step after chip fabrication from a commercial CMOS foundry. Very dense sensor packing per unit area of the chip has been enabled by using technologies/processes like SOI, CMOS and DRIE. Independent apparatuses were used for the characterization of each sensor. With a drive current of 10 µA–0.1 µA, the thermodiodes exhibited sensitivities of 1.41 mV/°C–1.79 mV/°C in the range 20–300 °C. The sensitivity of the pressure sensor was 0.0686 mV/(Vexcit kPa) with a non-linearity of 0.25% between 0 and 69 kPa above ambient pressure. Packaged in a micro-channel, the flow rate sensor has a linearized sensitivity of 17.3 mV/(L/min)−0.1 in the tested range of 0–4.7 L/min. The multi-sensor chip can be used for simultaneous measurement of fluid pressure, temperature and flow rate in fluidic experiments and aerospace/automotive/biomedical/process industries. PMID:27827904

Demonstration of SST value as EBVs descriptor in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Valentini, E.; Filipponi, F.; Nguyen Xuan, A.; Taramelli, A.

2017-12-01

Sea Surface Temperature is an Essential Climate and Ocean Variable (ECV - EOV) able to capture critical scales in the seascape warming patterns and to highlight the exceeding of thresholds. This presentation addresses the changes of the SST in the last three decades over the Mediterranean Sea, a "Large Marine Ecosystem (LME)", in order to speculate the value of such powerful variable, as proxy for the assessment of ecosystem state in terms of ecosystem structures, functions and composition key descriptor. Time series of daily SST for the period 1982-2016, estimated from multi-sensor satellite data and provided by Copernicus Marine Environment Monitoring Service (CMEMS-EU) are used to perform different statistical analysis on common fish species. Results highlight the critical conditions, the general trends as well as the spatial and temporal patterns, in terms of thermal growth, vitality and stress influence on selected fish species. Results confirm a constant increasing trend in SST with an average rise of 1.4° C in the past thirty years. The variance associated to the average trend is not constant across the entire Mediterranean Sea opening the way to multiple scenarios for fish growth and vitality in the diverse sub-basins. A major effort is oriented in addressing the cross-scale ecological interactions to assess the feasibility of using SST as descriptor for Essential Biodiversity Variables, able to prioritize areas and to feed operational tools for planning and management in the Mediterranean LME.

Subtropical Gyre Variability as Seen from Satellites

NASA Technical Reports Server (NTRS)

Signorini, Sergio R.; McClain, Charles R.

2011-01-01

A satellite multi-sensor approach is used to analyse the biological response of open ocean regions of the subtropical gyres to changes in physical forcing. Thirteen years (1998-2010) of SeaWiFS chlorophyll a (Chl-a), combined with concurrent satellite records of sea-surface temperature (SST) and sea level height, were analysed to investigate the seasonal and interannual variability of Chl-a concentration within these immense so-called ocean deserts. The seasonal variability of Chl-a within the gyres is driven mostly by the warming/cooling of surface waters. Summer warming promotes shallower mixed layers and lower Chl-a due to a reduction of vertical mixing and consequently a decrease in nutrient supply. The opposite happens during the winter cooling period. Therefore, long-term trends in SST have the potential to cause an impact on the interannual variability of Chl-a. Our analyses show that, during the 13 whole years of SeaWiFS data record, the North Pacific, Indian Ocean, and North Atlantic gyres experienced a decrease in Chl-a of 9%, 12%, and 11%, respectively, with corresponding SST increases of 0.27 C, 0.42 C, and 0.32 C. The South Pacific and South Atlantic gyres also showed warming trends but with weak positive trends in Chl-a that are not statistically significant. We hypothesize that the warming of surface waters in these two gyres are counterbalanced by other interacting physical and biological driving mechanisms, as indicated in previous studies.

A new Arctic 25-year Altimetric Sea-level Record (1992-2016) and Initial look at Arctic Sea Level Budget Closure

NASA Astrophysics Data System (ADS)

Andersen, O. B.; Passaro, M.; Benveniste, J.; Piccioni, G.

2016-12-01

A new initiative within the ESA Sea Level Climate Change initiative (SL-cci) framework to improve the Arctic sea level record has been initiated as a combined effort to reprocess and retrack past altimetry to create a 25-year combined sea level record for sea level research studies. One of the objectives is to retracked ERS-2 dataset for the high latitudes based on the ALES retracking algorithm through adapting the ALES retracker for retracking of specular surfaces (leads). Secondly a reprocessing using tailored editing to Arctic Conditions will be carried out also focusing on the merging of the multi-mission data. Finally an effort is to combine physical and empirical retracked sea surface height information to derive an experimental spatio-temporal enhanced sea level product for high latitude. The first results in analysing Arctic Sea level variations on annual inter-annual scales for the 1992-2015 from a preliminar version of this dataset is presented. By including the GRACE water storage estimates and NOAA halo- and thermo-steric sea level variatios since 2002 a preliminary attempt to close the Arctic Sea level budget is presented here. Closing the Arctic sea level budget is by no mean trivial as both steric data and satellite altimetry is both sparse temporally and limited geographically.

Enhanced chemical weapon warning via sensor fusion

NASA Astrophysics Data System (ADS)

Flaherty, Michael; Pritchett, Daniel; Cothren, Brian; Schwaiger, James

2011-05-01

Torch Technologies Inc., is actively involved in chemical sensor networking and data fusion via multi-year efforts with Dugway Proving Ground (DPG) and the Defense Threat Reduction Agency (DTRA). The objective of these efforts is to develop innovative concepts and advanced algorithms that enhance our national Chemical Warfare (CW) test and warning capabilities via the fusion of traditional and non-traditional CW sensor data. Under Phase I, II, and III Small Business Innovative Research (SBIR) contracts with DPG, Torch developed the Advanced Chemical Release Evaluation System (ACRES) software to support non real-time CW sensor data fusion. Under Phase I and II SBIRs with DTRA in conjunction with the Edgewood Chemical Biological Center (ECBC), Torch is using the DPG ACRES CW sensor data fuser as a framework from which to develop the Cloud state Estimation in a Networked Sensor Environment (CENSE) data fusion system. Torch is currently developing CENSE to implement and test innovative real-time sensor network based data fusion concepts using CW and non-CW ancillary sensor data to improve CW warning and detection in tactical scenarios.

Cutting Edge Technologies Presentation: An Overview of Developing Sensor Technology Directions and Possible Barriers to New Technology Implementation

NASA Technical Reports Server (NTRS)

Hunter, Gary W.

2007-01-01

The aerospace industry requires the development of a range of chemical sensor technologies for such applications as leak detection, emission monitoring, fuel leak detection, environmental monitoring, and fire detection. A range of chemical sensors are being developed based on micromachining and microfabrication technology to fabricate microsensors with minimal size, weight, and power consumption; and the use of nanomaterials and structures to develop sensors with improved stability combined with higher sensitivity, However, individual sensors are limited in the amount of information that they can provide in environments that contain multiple chemical species. Thus, sensor arrays are being developed to address detection needs in such multi-species environments. These technologies and technical approaches have direct relevance to breath monitoring for clinical applications. This presentation gives an overview of developing cutting-edge sensor technology and possible barriers to new technology implementation. This includes lessons learned from previous microsensor development, recent work in development of a breath monitoring system, and future directions in the implementation of cutting edge sensor technology.

Multi-sensor analysis of urban ecosystems

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei

2004-01-01

This study examines the synthesis of multiple space-based sensors to characterize the urban environment Single scene data (e.g., ASTER visible and near-IR surface reflectance, and land surface temperature data), multi-temporal data (e.g., one year of 16-day MODIS and AVHRR vegetation index data), and DMSP-OLS nighttime light data acquired in the early 1990s and 2000 were evaluated for urban ecosystem analysis. The advantages of a multi-sensor approach for the analysis of urban ecosystem processes are discussed.

Canadian snow and sea ice: assessment of snow, sea ice, and related climate processes in Canada's Earth system model and climate-prediction system

NASA Astrophysics Data System (ADS)

Kushner, Paul J.; Mudryk, Lawrence R.; Merryfield, William; Ambadan, Jaison T.; Berg, Aaron; Bichet, Adéline; Brown, Ross; Derksen, Chris; Déry, Stephen J.; Dirkson, Arlan; Flato, Greg; Fletcher, Christopher G.; Fyfe, John C.; Gillett, Nathan; Haas, Christian; Howell, Stephen; Laliberté, Frédéric; McCusker, Kelly; Sigmond, Michael; Sospedra-Alfonso, Reinel; Tandon, Neil F.; Thackeray, Chad; Tremblay, Bruno; Zwiers, Francis W.

2018-04-01

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.

Linear FBG Temperature Sensor Interrogation with Fabry-Perot ITU Multi-wavelength Reference

PubMed Central

Park, Hyoung-Jun; Song, Minho

2008-01-01

The equidistantly spaced multi-passbands of a Fabry-Perot ITU filter are used as an efficient multi-wavelength reference for fiber Bragg grating sensor demodulation. To compensate for the nonlinear wavelength tuning effect in the FBG sensor demodulator, a polynomial fitting algorithm was applied to the temporal peaks of the wavelength-scanned ITU filter. The fitted wavelength values are assigned to the peak locations of the FBG sensor reflections, obtaining constant accuracy, regardless of the wavelength scan range and frequency. A linearity error of about 0.18% against a reference thermocouple thermometer was obtained with the suggested method. PMID:27873898

Fiber Loop Ringdown — a Time-Domain Sensing Technique for Multi-Function Fiber Optic Sensor Platforms: Current Status and Design Perspectives

PubMed Central

Wang, Chuji

2009-01-01

Fiber loop ringdown (FLRD) utilizes an inexpensive telecommunications light source, a photodiode, and a section of single-mode fiber to form a uniform fiber optic sensor platform for sensing various quantities, such as pressure, temperature, strain, refractive index, chemical species, biological cells, and small volume of fluids. In FLRD, optical losses of a light pulse in a fiber loop induced by changes in a quantity are measured by the light decay time constants. FLRD measures time to detect a quantity; thus, FLRD is referred to as a time-domain sensing technique. FLRD sensors have near real-time response, multi-pass enhanced high-sensitivity, and relatively low cost (i.e., without using an optical spectral analyzer). During the last eight years since the introduction of the original form of fiber ringdown spectroscopy, there has been increasing interest in the FLRD technique in fiber optic sensor developments, and new application potential is being explored. This paper first discusses the challenging issues in development of multi-function, fiber optic sensors or sensor networks using current fiber optic sensor sensing schemes, and then gives a review on current fiber optic sensor development using FLRD technique. Finally, design perspectives on new generation, multi-function, fiber optic sensor platforms using FLRD technique are particularly presented. PMID:22408471