Application Possibility of Smartphone as Payload for Photogrammetric Uav System

NASA Astrophysics Data System (ADS)

Yun, M. H.; Kim, J.; Seo, D.; Lee, J.; Choi, C.

2012-07-01

Smartphone can not only be operated under 3G network environment anytime and anyplace but also cost less than the existing photogrammetric UAV since it provides high-resolution image, 3D location and attitude data on a real-time basis from a variety of built-in sensors. This study is aimed to assess the possibility of smartphone as a payload for photogrammetric UAV system. Prior to such assessment, a smartphone-based photogrammetric UAV system application was developed, through which real-time image, location and attitude data was obtained using smartphone under both static and dynamic conditions. Subsequently the accuracy assessment on the location and attitude data obtained and sent by this system was conducted. The smartphone images were converted into ortho-images through image triangulation. The image triangulation was conducted in accordance with presence or absence of consideration of the interior orientation (IO) parameters determined by camera calibration. In case IO parameters were taken into account in the static experiment, the results from triangulation for any smartphone type were within 1.5 pixel (RMSE), which was improved at least by 35% compared to when IO parameters were not taken into account. On the contrary, the improvement effect of considering IO parameters on accuracy in triangulation for smartphone images in dynamic experiment was not significant compared to the static experiment. It was due to the significant impact of vibration and sudden attitude change of UAV on the actuator for automatic focus control within the camera built in smartphone under the dynamic condition. This cause appears to have a negative impact on the image-based DEM generation. Considering these study findings, it is suggested that smartphone is very feasible as a payload for UAV system. It is also expected that smartphone may be loaded onto existing UAV playing direct or indirect roles significantly.

UAV Annual Report, FY 1996.

DTIC Science & Technology

1996-11-06

Tracor; Vector; Cl Fiberite; Hexcel; Honeywell Cannon; Tamam; IntegriNautics; Lockheed Martin; Carlyle Gp; Northrop Grumman (SAR); Hbroux; Hughes...Aerospace; Group; Teftec Inc. Northrop Grumman ; Williams Internations Developmental estimates Developmental estimates 09 31 UAV ANNUAL REPORT UAV Tier 11...Rosemount Aerospace; Northrop Grumman ; Williams International Developmental estimates 31 UAVANNUAL REPORT A U.S. Customs Service P-3 AEW and Predator

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation

PubMed Central

Nitti, Davide O.; Bovenga, Fabio; Chiaradia, Maria T.; Greco, Mario; Pinelli, Gianpaolo

2015-01-01

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimate UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system. PMID:26225977

Feasibility of Using Synthetic Aperture Radar to Aid UAV Navigation.

PubMed

Nitti, Davide O; Bovenga, Fabio; Chiaradia, Maria T; Greco, Mario; Pinelli, Gianpaolo

2015-07-28

This study explores the potential of Synthetic Aperture Radar (SAR) to aid Unmanned Aerial Vehicle (UAV) navigation when Inertial Navigation System (INS) measurements are not accurate enough to eliminate drifts from a planned trajectory. This problem can affect medium-altitude long-endurance (MALE) UAV class, which permits heavy and wide payloads (as required by SAR) and flights for thousands of kilometres accumulating large drifts. The basic idea is to infer position and attitude of an aerial platform by inspecting both amplitude and phase of SAR images acquired onboard. For the amplitude-based approach, the system navigation corrections are obtained by matching the actual coordinates of ground landmarks with those automatically extracted from the SAR image. When the use of SAR amplitude is unfeasible, the phase content can be exploited through SAR interferometry by using a reference Digital Terrain Model (DTM). A feasibility analysis was carried out to derive system requirements by exploring both radiometric and geometric parameters of the acquisition setting. We showed that MALE UAV, specific commercial navigation sensors and SAR systems, typical landmark position accuracy and classes, and available DTMs lead to estimated UAV coordinates with errors bounded within ±12 m, thus making feasible the proposed SAR-based backup system.

Estimating plant distance in maize using Unmanned Aerial Vehicle (UAV).

PubMed

Zhang, Jinshui; Basso, Bruno; Price, Richard F; Putman, Gregory; Shuai, Guanyuan

2018-01-01

Distance between rows and plants are essential parameters that affect the final grain yield in row crops. This paper presents the results of research intended to develop a novel method to quantify the distance between maize plants at field scale using an Unmanned Aerial Vehicle (UAV). Using this method, we can recognize maize plants as objects and calculate the distance between plants. We initially developed our method by training an algorithm in an indoor facility with plastic corn plants. Then, the method was scaled up and tested in a farmer's field with maize plant spacing that exhibited natural variation. The results of this study demonstrate that it is possible to precisely quantify the distance between maize plants. We found that accuracy of the measurement of the distance between maize plants depended on the height above ground level at which UAV imagery was taken. This study provides an innovative approach to quantify plant-to-plant variability and, thereby final crop yield estimates.

Intification and modelling of flight characteristics for self-build shock flyer type UAV

NASA Astrophysics Data System (ADS)

Rashid., Z. A.; Dardin, A. S. F. Syed.; Azid, A. A.; Ahmad, K. A.

2018-02-01

The development of an autonomous Unmanned Aerial Vehicle (UAV) requires a fundamentals studies of the UAV's flight characteristic. The aim of this study is to identify and model the flight characteristic of a conventional fixed-wing type UAV. Subsequence to this, the mode of flight of the UAV can be investigated. One technique to identify the characteristic of a UAV is a flight test where it required specific maneuvering to be executed while measuring the attitude sensor. In this study, a simple shock flyer type UAV was used as the aircraft. The result shows that the modeled flight characteristic has a significant relation with actual values but the fitting value is rather small. It is suggested that the future study is conducted with an improvement of the physical UAV, data filtering and better system identification methods.

Multiple UAV Cooperation for Wildfire Monitoring

NASA Astrophysics Data System (ADS)

Lin, Zhongjie

Wildfires have been a major factor in the development and management of the world's forest. An accurate assessment of wildfire status is imperative for fire management. This thesis is dedicated to the topic of utilizing multiple unmanned aerial vehicles (UAVs) to cooperatively monitor a large-scale wildfire. This is achieved through wildfire spreading situation estimation based on on-line measurements and wise cooperation strategy to ensure efficiency. First, based on the understanding of the physical characteristics of the wildfire propagation behavior, a wildfire model and a Kalman filter-based method are proposed to estimate the wildfire rate of spread and the fire front contour profile. With the enormous on-line measurements from on-board sensors of UAVs, the proposed method allows a wildfire monitoring mission to benefit from on-line information updating, increased flexibility, and accurate estimation. An independent wildfire simulator is utilized to verify the effectiveness of the proposed method. Second, based on the filter analysis, wildfire spreading situation and vehicle dynamics, the influence of different cooperation strategies of UAVs to the overall mission performance is studied. The multi-UAV cooperation problem is formulated in a distributed network. A consensus-based method is proposed to help address the problem. The optimal cooperation strategy of UAVs is obtained through mathematical analysis. The derived optimal cooperation strategy is then verified in an independent fire simulation environment to verify its effectiveness.

Textured digital elevation model formation from low-cost UAV LADAR/digital image data

NASA Astrophysics Data System (ADS)

Bybee, Taylor C.; Budge, Scott E.

2015-05-01

Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, scientific-quality models are expensive to obtain using conventional aircraft-based methods. The cost of creating an accurate textured terrain model can be reduced by using a low-cost (<$20k) UAV system fitted with ladar and electro-optical (EO) sensors. A texel camera fuses calibrated ladar and EO data upon simultaneous capture, creating a texel image. This eliminates the problem of fusing the data in a post-processing step and enables both 2D- and 3D-image registration techniques to be used. This paper describes formation of TDEMs using simulated data from a small UAV gathering swaths of texel images of the terrain below. Being a low-cost UAV, only a coarse knowledge of position and attitude is known, and thus both 2D- and 3D-image registration techniques must be used to register adjacent swaths of texel imagery to create a TDEM. The process of creating an aggregate texel image (a TDEM) from many smaller texel image swaths is described. The algorithm is seeded with the rough estimate of position and attitude of each capture. Details such as the required amount of texel image overlap, registration models, simulated flight patterns (level and turbulent), and texture image formation are presented. In addition, examples of such TDEMs are shown and analyzed for accuracy.

Assessing UAVs in Monitoring Crop Evapotranspiration within a Heterogeneous Soil

NASA Astrophysics Data System (ADS)

Rouze, G.; Neely, H.; Morgan, C.; Kustas, W. P.; McKee, L.; Prueger, J. H.; Cope, D.; Yang, C.; Thomasson, A.; Jung, J.

2017-12-01

Airborne and satellite remote sensing methods have been developed to provide ET estimates across entire management fields. However, airborne-based ET is not particularly cost-effective and satellite-based ET provides insufficient spatial/temporal information. ET estimations through remote sensing are also problematic where soils are highly variable within a given management field. Unlike airborne/satellite-based ET, Unmanned Aerial Vehicle (UAV)-based ET has the potential to increase the spatial and temporal detail of these measurements, particularly within a heterogeneous soil landscape. However, it is unclear to what extent UAVs can model ET. The overall goal of this project was to assess the capability of UAVs in modeling ET across a heterogeneous landscape. Within a 20-ha irrigated cotton field in Central Texas, low-altitude UAV surveys were conducted throughout the growing season over two soil types. UAVs were equipped with thermal and multispectral cameras to obtain canopy temperature and NDVI, respectively. UAV data were supplemented simultaneously with ground-truth measurements such as Leaf Area Index (LAI) and plant height. Both remote sensing and ground-truth parameters were used to model ET using a Two-Source Energy Balance (TSEB) model. UAV-based estimations of ET and other energy balance components were validated against energy balance measurements obtained from nearby eddy covariance towers that were installed within each soil type. UAV-based ET fluxes were also compared with airborne and satellite (Landsat 8)-based ET fluxes collected near the time of the UAV survey.

a Micro-Uav with the Capability of Direct Georeferencing

NASA Astrophysics Data System (ADS)

Rehak, M.; Mabillard, R.; Skaloud, J.

2013-08-01

This paper presents the development of a low cost UAV (Unmanned Aerial Vehicle) with the capability of direct georeferencing. The advantage of such system lies in its high maneuverability, operation flexibility as well as capability to acquire image data without the need of establishing ground control points (GCPs). Moreover, the precise georeferencing offers an improvement in the final mapping accuracy when employing integrated sensor orientation. Such mode of operation limits the number and distribution of GCPs, which in turns save time in their signalization and surveying. Although the UAV systems feature high flexibility and capability of flying into areas that are inhospitable or inaccessible to humans, the lack of precision in positioning and attitude estimation on-board decrease the gained value of the captured imagery and limits their mode of operation to specific configurations and need of groundreference. Within a scope of this study we show the potential of present technologies in the field of position and orientation determination on a small UAV. The hardware implementation and especially the non-trivial synchronization of all components is clarified. Thanks to the implementation of a multi-frequency, low power GNSS receiver and its coupling with redundant MEMSIMU, we can attain the characteristic of a much larger systems flown on large carries while keeping the sensor size and weight suitable for MAV operations.

Feasibility of employing a smartphone as the payload in a photogrammetric UAV system

NASA Astrophysics Data System (ADS)

Kim, Jinsoo; Lee, Seongkyu; Ahn, Hoyong; Seo, Dongju; Park, Soyoung; Choi, Chuluong

2013-05-01

Smartphones can be operated in a 3G network environment at any time or location, and they also cost less than existing photogrammetric UAV systems, providing high-resolution images and 3D location and attitude data from a variety of built-in sensors. This study aims to assess the feasibility of using a smartphone as the payload for a photogrammetric UAV system. To carry out the assessment, a smartphone-based photogrammetric UAV system was developed and utilized to obtain image, location, and attitude data under both static and dynamic conditions. The accuracy of the location and attitude data obtained and sent by this system was then evaluated. The smartphone images were converted into ortho-images via image triangulation, which was carried out both with and without consideration of the interior orientation (IO) parameters determined by camera calibration. In the static experiment, when the IO parameters were taken into account, the triangulation results were less than 1.28 pixels (RMSE) for all smartphone types, an improvement of at least 47% compared with the case when IO parameters were not taken into account. In the dynamic experiment, on the other hand, the accuracy of smartphone image triangulation was not significantly improved by considering IO parameters. This was because the electronic rolling shutter within the complementary metal-oxide semiconductor (CMOS) sensor built into the smartphone and the actuator for the voice coil motor (VCM)-type auto-focusing affected by the vibration and the speed of the UAV, which is likely to have a negative effect on image-based digital elevation model (DEM) generation. However, considering that these results were obtained using a single smartphone, this suggests that a smartphone is not only feasible as the payload for a photogrammetric UAV system but it may also play a useful role when installed in existing UAV systems.

Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.

PubMed

Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

2009-01-01

This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

Validation of Inertial and Optical Navigation Techniques for Space Applications with UAVS

NASA Astrophysics Data System (ADS)

Montaño, J.; Wis, M.; Pulido, J. A.; Latorre, A.; Molina, P.; Fernández, E.; Angelats, E.; Colomina, I.

2015-09-01

PERIGEO is an R&D project, funded by the INNPRONTA 2011-2014 programme from Spanish CDTI, which aims to investigate the use of UAV technologies and processes for the validation of space oriented technologies. For this purpose, among different space missions and technologies, a set of activities for absolute and relative navigation are being carried out to deal with the attitude and position estimation problem from a temporal image sequence from a camera on the visible spectrum and/or Light Detection and Ranging (LIDAR) sensor. The process is covered entirely: from sensor measurements and data acquisition (images, LiDAR ranges and angles), data pre-processing (calibration and co-registration of camera and LIDAR data), features and landmarks extraction from the images and image/LiDAR-based state estimation. In addition to image processing area, classical navigation system based on inertial sensors is also included in the research. The reason of combining both approaches is to enable the possibility to keep navigation capability in environments or missions where the radio beacon or reference signal as the GNSS satellite is not available (as for example an atmospheric flight in Titan). The rationale behind the combination of those systems is that they complement each other. The INS is capable of providing accurate position, velocity and full attitude estimations at high data rates. However, they need an absolute reference observation to compensate the time accumulative errors caused by inertial sensor inaccuracies. On the other hand, imaging observables can provide absolute and relative positioning and attitude estimations. However they need that the sensor head is pointing toward ground (something that may not be possible if the carrying platform is maneuvering) to provide accurate estimations and they are not capable of provide some hundreds of Hz that can deliver an INS. This mutual complementarity has been observed in PERIGEO and because of this they are combined

Magnetometer-only attitude and angular velocity filtering estimation for attitude changing spacecraft

NASA Astrophysics Data System (ADS)

Ma, Hongliang; Xu, Shijie

2014-09-01

This paper presents an improved real-time sequential filter (IRTSF) for magnetometer-only attitude and angular velocity estimation of spacecraft during its attitude changing (including fast and large angular attitude maneuver, rapidly spinning or uncontrolled tumble). In this new magnetometer-only attitude determination technique, both attitude dynamics equation and first time derivative of measured magnetic field vector are directly leaded into filtering equations based on the traditional single vector attitude determination method of gyroless and real-time sequential filter (RTSF) of magnetometer-only attitude estimation. The process noise model of IRTSF includes attitude kinematics and dynamics equations, and its measurement model consists of magnetic field vector and its first time derivative. The observability of IRTSF for small or large angular velocity changing spacecraft is evaluated by an improved Lie-Differentiation, and the degrees of observability of IRTSF for different initial estimation errors are analyzed by the condition number and a solved covariance matrix. Numerical simulation results indicate that: (1) the attitude and angular velocity of spacecraft can be estimated with sufficient accuracy using IRTSF from magnetometer-only data; (2) compared with that of RTSF, the estimation accuracies and observability degrees of attitude and angular velocity using IRTSF from magnetometer-only data are both improved; and (3) universality: the IRTSF of magnetometer-only attitude and angular velocity estimation is observable for any different initial state estimation error vector.

Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

NASA Astrophysics Data System (ADS)

Nelson, P.; Paradis, D. P.

2017-12-01

The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined

Robust Vision-Based Pose Estimation Algorithm for AN Uav with Known Gravity Vector

NASA Astrophysics Data System (ADS)

Kniaz, V. V.

2016-06-01

Accurate estimation of camera external orientation with respect to a known object is one of the central problems in photogrammetry and computer vision. In recent years this problem is gaining an increasing attention in the field of UAV autonomous flight. Such application requires a real-time performance and robustness of the external orientation estimation algorithm. The accuracy of the solution is strongly dependent on the number of reference points visible on the given image. The problem only has an analytical solution if 3 or more reference points are visible. However, in limited visibility conditions it is often needed to perform external orientation with only 2 visible reference points. In such case the solution could be found if the gravity vector direction in the camera coordinate system is known. A number of algorithms for external orientation estimation for the case of 2 known reference points and a gravity vector were developed to date. Most of these algorithms provide analytical solution in the form of polynomial equation that is subject to large errors in the case of complex reference points configurations. This paper is focused on the development of a new computationally effective and robust algorithm for external orientation based on positions of 2 known reference points and a gravity vector. The algorithm implementation for guidance of a Parrot AR.Drone 2.0 micro-UAV is discussed. The experimental evaluation of the algorithm proved its computational efficiency and robustness against errors in reference points positions and complex configurations.

Three-Axis Attitude Estimation Using Rate-Integrating Gyroscopes

NASA Technical Reports Server (NTRS)

Crassidis, John L.; Markley, F. Landis

2016-01-01

Traditionally, attitude estimation has been performed using a combination of external attitude sensors and internal three-axis gyroscopes. There are many studies of three-axis attitude estimation using gyros that read angular rates. Rate-integrating gyros measure integrated rates or angular displacements, but three-axis attitude estimation using these types of gyros has not been as fully investigated. This paper derives a Kalman filtering framework for attitude estimation using attitude sensors coupled with rate- integrating gyroscopes. In order to account for correlations introduced by using these gyros, the state vector must be augmented, compared with filters using traditional gyros that read angular rates. Two filters are derived in this paper. The first uses an augmented state-vector form that estimates attitude, gyro biases, and gyro angular displacements. The second ignores correlations, leading to a filter that estimates attitude and gyro biases only. Simulation comparisons are shown for both filters. The work presented in this paper focuses only on attitude estimation using rate-integrating gyros, but it can easily be extended to other applications such as inertial navigation, which estimates attitude and position.

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV.

PubMed

Li, Huanyu; Wu, Linfeng; Li, Yingjie; Li, Chunwen; Li, Hangyu

2016-12-02

Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy.

A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV

PubMed Central

Li, Huanyu; Wu, Linfeng; Li, Yingjie; Li, Chunwen; Li, Hangyu

2016-01-01

Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy. PMID:27918422

Development of a Novel, Two-Processor Architecture for a Small UAV Autopilot System,

DTIC Science & Technology

2006-07-26

is, and the control laws the user implements to control it. The flight control system board will contain the processor selected for this system...Unit (IMU). The IMU contains solid-state gyros and accelerometers and uses these to determine the attitude of the UAV within the three dimensions of...multiple-UAV swarming for combat support operations. The mission processor board will contain the processor selected to execute the mission

Uav Photogrammetry: Block Triangulation Comparisons

NASA Astrophysics Data System (ADS)

Gini, R.; Pagliari, D.; Passoni, D.; Pinto, L.; Sona, G.; Dosso, P.

2013-08-01

UAVs systems represent a flexible technology able to collect a big amount of high resolution information, both for metric and interpretation uses. In the frame of experimental tests carried out at Dept. ICA of Politecnico di Milano to validate vector-sensor systems and to assess metric accuracies of images acquired by UAVs, a block of photos taken by a fixed wing system is triangulated with several software. The test field is a rural area included in an Italian Park ("Parco Adda Nord"), useful to study flight and imagery performances on buildings, roads, cultivated and uncultivated vegetation. The UAV SenseFly, equipped with a camera Canon Ixus 220HS, flew autonomously over the area at a height of 130 m yielding a block of 49 images divided in 5 strips. Sixteen pre-signalized Ground Control Points, surveyed in the area through GPS (NRTK survey), allowed the referencing of the block and accuracy analyses. Approximate values for exterior orientation parameters (positions and attitudes) were recorded by the flight control system. The block was processed with several software: Erdas-LPS, EyeDEA (Univ. of Parma), Agisoft Photoscan, Pix4UAV, in assisted or automatic way. Results comparisons are given in terms of differences among digital surface models, differences in orientation parameters and accuracies, when available. Moreover, image and ground point coordinates obtained by the various software were independently used as initial values in a comparative adjustment made by scientific in-house software, which can apply constraints to evaluate the effectiveness of different methods of point extraction and accuracies on ground check points.

Multimodal UAV detection: study of various intrusion scenarios

NASA Astrophysics Data System (ADS)

Hengy, Sebastien; Laurenzis, Martin; Schertzer, Stéphane; Hommes, Alexander; Kloeppel, Franck; Shoykhetbrod, Alex; Geibig, Thomas; Johannes, Winfried; Rassy, Oussama; Christnacher, Frank

2017-10-01

Small unmanned aerial vehicles (UAVs) are becoming increasingly popular and affordable the last years for professional and private consumer market, with varied capacities and performances. Recent events showed that illicit or hostile uses constitute an emergent, quickly evolutionary threat. Recent developments in UAV technologies tend to bring autonomous, highly agile and capable unmanned aerial vehicles to the market. These UAVs can be used for spying operations as well as for transporting illicit or hazardous material (smuggling, flying improvised explosive devices). The scenario of interest concerns the protection of sensitive zones against the potential threat constituted by small drones. In the recent past, field trials were carried out to investigate the detection and tracking of multiple UAV flying at low altitude. Here, we present results which were achieved using a heterogeneous sensor network consisting of acoustic antennas, small FMCW RADAR systems and optical sensors. While acoustics and RADAR was applied to monitor a wide azimuthal area (360°), optical sensors were used for sequentially identification. The localization results have been compared to the ground truth data to estimate the efficiency of each detection system. Seven-microphone acoustic arrays allow single source localization. The mean azimuth and elevation estimation error has been measured equal to 1.5 and -2.5 degrees respectively. The FMCW radar allows tracking of multiple UAVs by estimating their range, azimuth and motion speed. Both technologies can be linked to the electro-optical system for final identification of the detected object.

Autonomous Control of a Quadrotor UAV Using Fuzzy Logic

NASA Astrophysics Data System (ADS)

Sureshkumar, Vijaykumar

UAVs are being increasingly used today than ever before in both military and civil applications. They are heavily preferred in "dull, dirty or dangerous" mission scenarios. Increasingly, UAVs of all kinds are being used in policing, fire-fighting, inspection of structures, pipelines etc. Recently, the FAA gave its permission for UAVs to be used on film sets for motion capture and high definition video recording. The rapid development in MEMS and actuator technology has made possible a plethora of UAVs that are suited for commercial applications in an increasingly cost effective manner. An emerging popular rotary wing UAV platform is the Quadrotor A Quadrotor is a helicopter with four rotors, that make it more stable; but more complex to model and control. Characteristics that provide a clear advantage over other fixed wing UAVs are VTOL and hovering capabilities as well as a greater maneuverability. It is also simple in construction and design compared to a scaled single rotorcraft. Flying such UAVs using a traditional radio Transmitter-Receiver setup can be a daunting task especially in high stress situations. In order to make such platforms widely applicable, a certain level of autonomy is imperative to the future of such UAVs. This thesis paper presents a methodology for the autonomous control of a Quadrotor UAV using Fuzzy Logic. Fuzzy logic control has been chosen over conventional control methods as it can deal effectively with highly nonlinear systems, allows for imprecise data and is extremely modular. Modularity and adaptability are the key cornerstones of FLC. The objective of this thesis is to present the steps of designing, building and simulating an intelligent flight control module for a Quadrotor UAV. In the course of this research effort, a Quadrotor UAV is indigenously developed utilizing the resources of an online open source project called Aeroquad. System design is comprehensively dealt with. A math model for the Quadrotor is developed and a

Attitude Estimation in Fractionated Spacecraft Cluster Systems

NASA Technical Reports Server (NTRS)

Hadaegh, Fred Y.; Blackmore, James C.

2011-01-01

An attitude estimation was examined in fractioned free-flying spacecraft. Instead of a single, monolithic spacecraft, a fractionated free-flying spacecraft uses multiple spacecraft modules. These modules are connected only through wireless communication links and, potentially, wireless power links. The key advantage of this concept is the ability to respond to uncertainty. For example, if a single spacecraft module in the cluster fails, a new one can be launched at a lower cost and risk than would be incurred with onorbit servicing or replacement of the monolithic spacecraft. In order to create such a system, however, it is essential to know what the navigation capabilities of the fractionated system are as a function of the capabilities of the individual modules, and to have an algorithm that can perform estimation of the attitudes and relative positions of the modules with fractionated sensing capabilities. Looking specifically at fractionated attitude estimation with startrackers and optical relative attitude sensors, a set of mathematical tools has been developed that specify the set of sensors necessary to ensure that the attitude of the entire cluster ( cluster attitude ) can be observed. Also developed was a navigation filter that can estimate the cluster attitude if these conditions are satisfied. Each module in the cluster may have either a startracker, a relative attitude sensor, or both. An extended Kalman filter can be used to estimate the attitude of all modules. A range of estimation performances can be achieved depending on the sensors used and the topology of the sensing network.

Performance comparison of attitude determination, attitude estimation, and nonlinear observers algorithms

NASA Astrophysics Data System (ADS)

MOHAMMED, M. A. SI; BOUSSADIA, H.; BELLAR, A.; ADNANE, A.

2017-01-01

This paper presents a brief synthesis and useful performance analysis of different attitude filtering algorithms (attitude determination algorithms, attitude estimation algorithms, and nonlinear observers) applied to Low Earth Orbit Satellite in terms of accuracy, convergence time, amount of memory, and computation time. This latter is calculated in two ways, using a personal computer and also using On-board computer 750 (OBC 750) that is being used in many SSTL Earth observation missions. The use of this comparative study could be an aided design tool to the designer to choose from an attitude determination or attitude estimation or attitude observer algorithms. The simulation results clearly indicate that the nonlinear Observer is the more logical choice.

Attitude determination and parameter estimation using vector observations - Theory

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1989-01-01

Procedures for attitude determination based on Wahba's loss function are generalized to include the estimation of parameters other than the attitude, such as sensor biases. Optimization with respect to the attitude is carried out using the q-method, which does not require an a priori estimate of the attitude. Optimization with respect to the other parameters employs an iterative approach, which does require an a priori estimate of these parameters. Conventional state estimation methods require a priori estimates of both the parameters and the attitude, while the algorithm presented in this paper always computes the exact optimal attitude for given values of the parameters. Expressions for the covariance of the attitude and parameter estimates are derived.

Estimating spatially distributed turbulent heat fluxes from high-resolution thermal imagery acquired with a UAV system

PubMed Central

Brenner, Claire; Thiem, Christina Elisabeth; Wizemann, Hans-Dieter; Bernhardt, Matthias; Schulz, Karsten

2017-01-01

ABSTRACT In this study, high-resolution thermal imagery acquired with a small unmanned aerial vehicle (UAV) is used to map evapotranspiration (ET) at a grassland site in Luxembourg. The land surface temperature (LST) information from the thermal imagery is the key input to a one-source and two-source energy balance model. While the one-source model treats the surface as a single uniform layer, the two-source model partitions the surface temperature and fluxes into soil and vegetation components. It thus explicitly accounts for the different contributions of both components to surface temperature as well as turbulent flux exchange with the atmosphere. Contrary to the two-source model, the one-source model requires an empirical adjustment parameter in order to account for the effect of the two components. Turbulent heat flux estimates of both modelling approaches are compared to eddy covariance (EC) measurements using the high-resolution input imagery UAVs provide. In this comparison, the effect of different methods for energy balance closure of the EC data on the agreement between modelled and measured fluxes is also analysed. Additionally, the sensitivity of the one-source model to the derivation of the empirical adjustment parameter is tested. Due to the very dry and hot conditions during the experiment, pronounced thermal patterns developed over the grassland site. These patterns result in spatially variable turbulent heat fluxes. The model comparison indicates that both models are able to derive ET estimates that compare well with EC measurements under these conditions. However, the two-source model, with a more complex treatment of the energy and surface temperature partitioning between the soil and vegetation, outperformed the simpler one-source model in estimating sensible and latent heat fluxes. This is consistent with findings from prior studies. For the one-source model, a time-variant expression of the adjustment parameter (to account for the difference

Estimating spatially distributed turbulent heat fluxes from high-resolution thermal imagery acquired with a UAV system.

PubMed

Brenner, Claire; Thiem, Christina Elisabeth; Wizemann, Hans-Dieter; Bernhardt, Matthias; Schulz, Karsten

2017-05-19

In this study, high-resolution thermal imagery acquired with a small unmanned aerial vehicle (UAV) is used to map evapotranspiration (ET) at a grassland site in Luxembourg. The land surface temperature (LST) information from the thermal imagery is the key input to a one-source and two-source energy balance model. While the one-source model treats the surface as a single uniform layer, the two-source model partitions the surface temperature and fluxes into soil and vegetation components. It thus explicitly accounts for the different contributions of both components to surface temperature as well as turbulent flux exchange with the atmosphere. Contrary to the two-source model, the one-source model requires an empirical adjustment parameter in order to account for the effect of the two components. Turbulent heat flux estimates of both modelling approaches are compared to eddy covariance (EC) measurements using the high-resolution input imagery UAVs provide. In this comparison, the effect of different methods for energy balance closure of the EC data on the agreement between modelled and measured fluxes is also analysed. Additionally, the sensitivity of the one-source model to the derivation of the empirical adjustment parameter is tested. Due to the very dry and hot conditions during the experiment, pronounced thermal patterns developed over the grassland site. These patterns result in spatially variable turbulent heat fluxes. The model comparison indicates that both models are able to derive ET estimates that compare well with EC measurements under these conditions. However, the two-source model, with a more complex treatment of the energy and surface temperature partitioning between the soil and vegetation, outperformed the simpler one-source model in estimating sensible and latent heat fluxes. This is consistent with findings from prior studies. For the one-source model, a time-variant expression of the adjustment parameter (to account for the difference between

Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems.

PubMed

Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio

2016-12-17

Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical Systems (MEMS)-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS) receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase) exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision) to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information.

Fast Quaternion Attitude Estimation from Two Vector Measurements

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Bauer, Frank H. (Technical Monitor)

2001-01-01

Many spacecraft attitude determination methods use exactly two vector measurements. The two vectors are typically the unit vector to the Sun and the Earth's magnetic field vector for coarse "sun-mag" attitude determination or unit vectors to two stars tracked by two star trackers for fine attitude determination. Existing closed-form attitude estimates based on Wahba's optimality criterion for two arbitrarily weighted observations are somewhat slow to evaluate. This paper presents two new fast quaternion attitude estimation algorithms using two vector observations, one optimal and one suboptimal. The suboptimal method gives the same estimate as the TRIAD algorithm, at reduced computational cost. Simulations show that the TRIAD estimate is almost as accurate as the optimal estimate in representative test scenarios.

UAV remote sensing atmospheric degradation image restoration based on multiple scattering APSF estimation

NASA Astrophysics Data System (ADS)

Qiu, Xiang; Dai, Ming; Yin, Chuan-li

2017-09-01

Unmanned aerial vehicle (UAV) remote imaging is affected by the bad weather, and the obtained images have the disadvantages of low contrast, complex texture and blurring. In this paper, we propose a blind deconvolution model based on multiple scattering atmosphere point spread function (APSF) estimation to recovery the remote sensing image. According to Narasimhan analytical theory, a new multiple scattering restoration model is established based on the improved dichromatic model. Then using the L0 norm sparse priors of gradient and dark channel to estimate APSF blur kernel, the fast Fourier transform is used to recover the original clear image by Wiener filtering. By comparing with other state-of-the-art methods, the proposed method can correctly estimate blur kernel, effectively remove the atmospheric degradation phenomena, preserve image detail information and increase the quality evaluation indexes.

An automated method of tuning an attitude estimator

NASA Technical Reports Server (NTRS)

Mason, Paul A. C.; Mook, D. Joseph

1995-01-01

Attitude determination is a major element of the operation and maintenance of a spacecraft. There are several existing methods of determining the attitude of a spacecraft. One of the most commonly used methods utilizes the Kalman filter to estimate the attitude of the spacecraft. Given an accurate model of a system and adequate observations, a Kalman filter can produce accurate estimates of the attitude. If the system model, filter parameters, or observations are inaccurate, the attitude estimates may be degraded. Therefore, it is advantageous to develop a method of automatically tuning the Kalman filter to produce the accurate estimates. In this paper, a three-axis attitude determination Kalman filter, which uses only magnetometer measurements, is developed and tested using real data. The appropriate filter parameters are found via the Process Noise Covariance Estimator (PNCE). The PNCE provides an optimal criterion for determining the best filter parameters.

UAV magnetometry in mineral exploration and infrastructure detection

NASA Astrophysics Data System (ADS)

Braun, A.; Parvar, K.; Burns, M.

2015-12-01

Magnetic surveys are critical tools in mineral exploration and UAVs have the potential to carry magnetometers. UAV surveys can offer higher spatial resolution than traditional airborne surveys, and higher coverage than terrestrial surveys. However, the main advantage is their ability to sense the magnetic field in 3-D, while most airborne or terrestrial surveys are restricted to 2-D acquisition. This study compares UAV magnetic data from two different UAVs (JIB drone, DJI Phantom 2) and three different magnetometers (GEM GSPM35, Honeywell HMR2300, GEM GST-19). The first UAV survey was conducted using a JIB UAV with a GSPM35 flying at 10-15 m above ground. The survey's goal was to detect intrusive Rhyolite bodies for primary mineral exploration. The survey resulted in a better understanding of the validity/resolution of UAV data and led to improved knowledge about the geological structures in the area. The results further drove the design of a following terrestrial survey. Comparing the UAV data with an available airborne survey (upward continued to 250 m) reveals that the UAV data has superior spatial resolution, but exhibits a higher noise level. The magnetic anomalies related to the Rhyolite intrusions is about 109 nT and translates into an estimated depth of approximately 110 meters. The second survey was conducted using an in-house developed UAV magnetometer system equipped with a DJI Phantom 2 and a Honeywell HMR2300 fluxgate magnetometer. By flying the sensor in different altitudes, the vertical and horizontal gradients can be derived leading to full 3-D magnetic data volumes which can provide improved constraints for source depth/geometry characterization. We demonstrate that a buried steam pipeline was detectable with the UAV magnetometer system and compare the resulting data with a terrestrial survey using a GEM GST-19 Proton Precession Magnetometer.

Optimal trajectory planning for a UAV glider using atmospheric thermals

NASA Astrophysics Data System (ADS)

Kagabo, Wilson B.

An Unmanned Aerial Vehicle Glider (UAV glider) uses atmospheric energy in its different forms to remain aloft for extended flight durations. This UAV glider's aim is to extract atmospheric thermal energy and use it to supplement its battery energy usage and increase the mission period. Given an infrared camera identified atmospheric thermal of known strength and location; current wind speed and direction; current battery level; altitude and location of the UAV glider; and estimating the expected altitude gain from the thermal, is it possible to make an energy-efficient based motivation to fly to an atmospheric thermal so as to achieve UAV glider extended flight time? For this work, an infrared thermal camera aboard the UAV glider takes continuous forward-looking ground images of "hot spots". Through image processing a candidate atmospheric thermal strength and location is estimated. An Intelligent Decision Model incorporates this information with the current UAV glider status and weather conditions to provide an energy-based recommendation to modify the flight path of the UAV glider. Research, development, and simulation of the Intelligent Decision Model is the primary focus of this work. Three models are developed: (1) Battery Usage Model, (2) Intelligent Decision Model, and (3) Altitude Gain Model. The Battery Usage Model comes from the candidate flight trajectory, wind speed & direction and aircraft dynamic model. Intelligent Decision Model uses a fuzzy logic based approach. The Altitude Gain Model requires the strength and size of the thermal and is found a priori.

Demonstration of UAV deployment and control of mobile wireless sensing networks for modal analysis of structures

NASA Astrophysics Data System (ADS)

Zhou, Hao; Hirose, Mitsuhito; Greenwood, William; Xiao, Yong; Lynch, Jerome; Zekkos, Dimitrios; Kamat, Vineet

2016-04-01

Unmanned aerial vehicles (UAVs) can serve as a powerful mobile sensing platform for assessing the health of civil infrastructure systems. To date, the majority of their uses have been dedicated to vision and laser-based spatial imaging using on-board cameras and LiDAR units, respectively. Comparatively less work has focused on integration of other sensing modalities relevant to structural monitoring applications. The overarching goal of this study is to explore the ability for UAVs to deploy a network of wireless sensors on structures for controlled vibration testing. The study develops a UAV platform with an integrated robotic gripper that can be used to install wireless sensors in structures, drop a heavy weight for the introduction of impact loads, and to uninstall wireless sensors for reinstallation elsewhere. A pose estimation algorithm is embedded in the UAV to estimate the location of the UAV during sensor placement and impact load introduction. The Martlet wireless sensor network architecture is integrated with the UAV to provide the UAV a mobile sensing capability. The UAV is programmed to command field deployed Martlets, aggregate and temporarily store data from the wireless sensor network, and to communicate data to a fixed base station on site. This study demonstrates the integrated UAV system using a simply supported beam in the lab with Martlet wireless sensors placed by the UAV and impact load testing performed. The study verifies the feasibility of the integrated UAV-wireless monitoring system architecture with accurate modal characteristics of the beam estimated by modal analysis.

Research on performance requirements of turbofan engine used on carrier-based UAV

NASA Astrophysics Data System (ADS)

Zhao, Shufan; Li, Benwei; Zhang, Wenlong; Wu, Heng; Feng, Tang

2017-05-01

According to the mission requirements of the carrier-based unmanned aerial vehicle (UAV), a mode level flight was established to calculate the thrust requirements from altitude 9 km to 13 km. Then, the estimation method of flight profile was used to calculate the weight of UAV in each stage to get the specific fuel consumption requirements of the UAV in standby stage. The turbofan engine of carrier-based UAV should meet the thrust and specific fuel consumption requirements. Finally, the GSP software was used to verify the simulation of a small high-bypass turbofan engine. The conclusion is useful for the turbofan engine selection of carrier-based UAV.

Differential GNSS and Vision-Based Tracking to Improve Navigation Performance in Cooperative Multi-UAV Systems

PubMed Central

Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico; Moccia, Antonio

2016-01-01

Autonomous navigation of micro-UAVs is typically based on the integration of low cost Global Navigation Satellite System (GNSS) receivers and Micro-Electro-Mechanical Systems (MEMS)-based inertial and magnetic sensors to stabilize and control the flight. The resulting navigation performance in terms of position and attitude accuracy may not suffice for other mission needs, such as the ones relevant to fine sensor pointing. In this framework, this paper presents a cooperative UAV navigation algorithm that allows a chief vehicle, equipped with inertial and magnetic sensors, a Global Positioning System (GPS) receiver, and a vision system, to improve its navigation performance (in real time or in the post processing phase) exploiting formation flying deputy vehicles equipped with GPS receivers. The focus is set on outdoor environments and the key concept is to exploit differential GPS among vehicles and vision-based tracking (DGPS/Vision) to build a virtual additional navigation sensor whose information is then integrated in a sensor fusion algorithm based on an Extended Kalman Filter. The developed concept and processing architecture are described, with a focus on DGPS/Vision attitude determination algorithm. Performance assessment is carried out on the basis of both numerical simulations and flight tests. In the latter ones, navigation estimates derived from the DGPS/Vision approach are compared with those provided by the onboard autopilot system of a customized quadrotor. The analysis shows the potential of the developed approach, mainly deriving from the possibility to exploit magnetic- and inertial-independent accurate attitude information. PMID:27999318

Baseline and Multimodal UAV GCS Interface Design

DTIC Science & Technology

2011-12-01

information queries). 2 Calhoun et al. (2004) Different musical chords and intervals. Priority level of a late-arriving UAV. 4 Graham and...tactors (the lower levels ones especially) would be on for much longer durations as the UAV’s attitude upset increases. 2.2.2.7.2 Uni- centred Circles...in uni- centred circles. Figure 2.12: Tactor formation for the uni- centred circles of tactors. In this type of display, the tactors which are

Magnetic profiling of the San Andreas Fault using a dual magnetometer UAV aerial survey system.

NASA Astrophysics Data System (ADS)

Abbate, J. A.; Angelopoulos, V.; Masongsong, E. V.; Yang, J.; Medina, H. R.; Moon, S.; Davis, P. M.

2017-12-01

Aeromagnetic survey methods using planes are more time-effective than hand-held methods, but can be far more expensive per unit area unless large areas are covered. The availability of low cost UAVs and low cost, lightweight fluxgate magnetometers (FGMs) allows, with proper offset determination and stray fields correction, for low-cost magnetic surveys. Towards that end, we have developed a custom multicopter UAV for magnetic mapping using a dual 3-axis fluxgate magnetometer system: the GEOphysical Drone Enhanced Survey Instrument (GEODESI). A high precision sensor measures the UAV's position and attitude (roll, pitch, and yaw) and is recorded using a custom Arduino data processing system. The two FGMs (in-board and out-board) are placed on two ends of a vertical 1m boom attached to the base of the UAV. The in-board FGM is most sensitive to stray fields from the UAV and its signal is used, after scaling, to clean the signal of the out-board FGM from the vehicle noise. The FGMs record three orthogonal components of the magnetic field in the UAV body coordinates which are then transformed into a north-east-down coordinate system using a rotation matrix determined from the roll-pitch-yaw attitude data. This ensures knowledge of the direction of all three field components enabling us to perform inverse modeling of magnetic anomalies with greater accuracy than total or vertical field measurements used in the past. Field tests were performed at Dragon's Back Pressure Ridge in the Carrizo Plain of California, where there is a known crossing of the San Andreas Fault. Our data and models were compared to previously acquired LiDAR and hand-held magnetometer measurements. Further tests will be carried out to solidify our results and streamline our processing for educational use in the classroom and student field training.

Attitude and Trajectory Estimation Using Earth Magnetic Field Data

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack Y.

1996-01-01

The magnetometer has long been a reliable, inexpensive sensor used in spacecraft momentum management and attitude estimation. Recent studies show an increased accuracy potential for magnetometer-only attitude estimation systems. Since the Earth's magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computer and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft orbit, are a function of both the spacecraft trajectory and attitude errors. Therefore, these errors can be used to estimate both trajectory and attitude. Traditionally, satellite attitude and trajectory have been estimated with completely separate system, using different measurement data. Recently, trajectory estimation for low earth orbit satellites was successfully demonstrated in ground software using only magnetometer data. This work proposes a single augmented extended Kalman Filter to simultaneously and autonomously estimate both spacecraft trajectory and attitude with data from a magnetometer and either dynamically determined rates or gyro-measured body rates.

A UAV and S2A data-based estimation of the initial biomass of green algae in the South Yellow Sea.

PubMed

Xu, Fuxiang; Gao, Zhiqiang; Jiang, Xiaopeng; Shang, Weitao; Ning, Jicai; Song, Debin; Ai, Jinquan

2018-03-01

Previous studies have shown that the initial biomass of green tide was the green algae attaching to Pyropia aquaculture rafts in the Southern Yellow Sea. In this study, the green algae was identified with unmanned aerial vehicle (UAV), an biomass estimation model was proposed for green algae biomass in the radial sand ridge area based on Sentinel-2A image (S2A) and UAV images. The result showed that the green algae was detected highly accurately with the normalized green-red difference index (NGRDI); approximately 1340 tons and 700 tons of green algae were attached to rafts and raft ropes respectively, and the lower biomass might be the main cause for the smaller scale of green tide in 2017. In addition, UAV play an important role in raft-attaching green algae monitoring and long-term research of its biomass would provide a scientific basis for the control and forecast of green tide in the Yellow Sea. Copyright © 2018 Elsevier Ltd. All rights reserved.

Landslide Mapping Using Imagery Acquired by a Fixed-Wing Uav

NASA Astrophysics Data System (ADS)

Rau, J. Y.; Jhan, J. P.; Lo, C. F.; Lin, Y. S.

2011-09-01

In Taiwan, the average annual rainfall is about 2,500 mm, about three times the world average. Hill slopes where are mostly under meta-stable conditions due to fragmented surface materials can easily be disturbed by heavy typhoon rainfall and/or earthquakes, resulting in landslides and debris flows. Thus, an efficient data acquisition and disaster surveying method is critical for decision making. Comparing with satellite and airplane, the unmanned aerial vehicle (UAV) is a portable and dynamic platform for data acquisition. In particularly when a small target area is required. In this study, a fixed-wing UAV that equipped with a consumer grade digital camera, i.e. Canon EOS 450D, a flight control computer, a Garmin GPS receiver and an attitude heading reference system (AHRS) are proposed. The adopted UAV has about two hours flight duration time with a flight control range of 20 km and has a payload of 3 kg, which is suitable for a medium scale mapping and surveying mission. In the paper, a test area with 21.3 km2 in size containing hundreds of landslides induced by Typhoon Morakot is used for landslides mapping. The flight height is around 1,400 meters and the ground sampling distance of the acquired imagery is about 17 cm. The aerial triangulation, ortho-image generation and mosaicking are applied to the acquired images in advance. An automatic landslides detection algorithm is proposed based on the object-based image analysis (OBIA) technique. The color ortho-image and a digital elevation model (DEM) are used. The ortho-images before and after typhoon are utilized to estimate new landslide regions. Experimental results show that the developed algorithm can achieve a producer's accuracy up to 91%, user's accuracy 84%, and a Kappa index of 0.87. It demonstrates the feasibility of the landslide detection algorithm and the applicability of a fixed-wing UAV for landslide mapping.

Nearshore Measurements From a Small UAV.

NASA Astrophysics Data System (ADS)

Holman, R. A.; Brodie, K. L.; Spore, N.

2016-02-01

Traditional measurements of nearshore hydrodynamics and evolving bathymetry are expensive and dangerous and must be frequently repeated to track the rapid changes of typical ocean beaches. However, extensive research into remote sensing methods using cameras or radars mounted on fixed towers has resulted in increasingly mature algorithms for estimating bathymetry, currents and wave characteristics. This naturally raises questions about how easily and effectively these algorithms can be applied to optical data from low-cost, easily-available UAV platforms. This paper will address the characteristics and quality of data taken from a small, low-cost UAV, the DJI Phantom. In particular, we will study the stability of imagery from a vehicle `parked' at 300 feet altitude, methods to stabilize remaining wander, and the quality of nearshore bathymetry estimates from the resulting image time series, computed using the cBathy algorithm. Estimates will be compared to ground truth surveys collected at the Field Research Facility at Duck, NC.

Comparison of 3D point clouds obtained by photogrammetric UAVs and TLS to determine the attitude of dolerite outcrops discontinuities.

NASA Astrophysics Data System (ADS)

Duarte, João; Gonçalves, Gil; Duarte, Diogo; Figueiredo, Fernando; Mira, Maria

2015-04-01

Photogrammetric Unmanned Aerial Vehicles (UAVs) and Terrestrial Laser Scanners (TLS) are two emerging technologies that allows the production of dense 3D point clouds of the sensed topographic surfaces. Although image-based stereo-photogrammetric point clouds could not, in general, compete on geometric quality over TLS point clouds, fully automated mapping solutions based on ultra-light UAVs (or drones) have recently become commercially available at very reasonable accuracy and cost for engineering and geological applications. The purpose of this paper is to compare the two point clouds generated by these two technologies, in order to automatize the manual process tasks commonly used to detect and represent the attitude of discontinuities (Stereographic projection: Schmidt net - Equal area). To avoid the difficulties of access and guarantee the data survey security conditions, this fundamental step in all geological/geotechnical studies, applied to the extractive industry and engineering works, has to be replaced by a more expeditious and reliable methodology. This methodology will allow, in a more actuated clear way, give answers to the needs of evaluation of rock masses, by mapping the structures present, which will reduce considerably the associated risks (investment, structures dimensioning, security, etc.). A case study of a dolerite outcrop locate in the center of Portugal (the dolerite outcrop is situated in the volcanic complex of Serra de Todo-o-Mundo, Casais Gaiola, intruded in Jurassic sandstones) will be used to assess this methodology. The results obtained show that the 3D point cloud produced by the Photogrammetric UAV platform has the appropriate geometric quality for extracting the parameters that define the discontinuities of the dolerite outcrops. Although, they are comparable to the manual extracted parameters, their quality is inferior to parameters extracted from the TLS point cloud.

Comparison of UAV and WorldView-2 imagery for mapping leaf area index of mangrove forest

NASA Astrophysics Data System (ADS)

Tian, Jinyan; Wang, Le; Li, Xiaojuan; Gong, Huili; Shi, Chen; Zhong, Ruofei; Liu, Xiaomeng

2017-09-01

Unmanned Aerial Vehicle (UAV) remote sensing has opened the door to new sources of data to effectively characterize vegetation metrics at very high spatial resolution and at flexible revisit frequencies. Successful estimation of the leaf area index (LAI) in precision agriculture with a UAV image has been reported in several studies. However, in most forests, the challenges associated with the interference from a complex background and a variety of vegetation species have hindered research using UAV images. To the best of our knowledge, very few studies have mapped the forest LAI with a UAV image. In addition, the drawbacks and advantages of estimating the forest LAI with UAV and satellite images at high spatial resolution remain a knowledge gap in existing literature. Therefore, this paper aims to map LAI in a mangrove forest with a complex background and a variety of vegetation species using a UAV image and compare it with a WorldView-2 image (WV2). In this study, three representative NDVIs, average NDVI (AvNDVI), vegetated specific NDVI (VsNDVI), and scaled NDVI (ScNDVI), were acquired with UAV and WV2 to predict the plot level (10 × 10 m) LAI. The results showed that AvNDVI achieved the highest accuracy for WV2 (R2 = 0.778, RMSE = 0.424), whereas ScNDVI obtained the optimal accuracy for UAV (R2 = 0.817, RMSE = 0.423). In addition, an overall comparison results of the WV2 and UAV derived LAIs indicated that UAV obtained a better accuracy than WV2 in the plots that were covered with homogeneous mangrove species or in the low LAI plots, which was because UAV can effectively eliminate the influence from the background and the vegetation species owing to its high spatial resolution. However, WV2 obtained a slightly higher accuracy than UAV in the plots covered with a variety of mangrove species, which was because the UAV sensor provides a negative spectral response function(SRF) than WV2 in terms of the mangrove LAI estimation.

Photogrammetric Measurements in Fixed Wing Uav Imagery

NASA Astrophysics Data System (ADS)

Gülch, E.

2012-07-01

Several flights have been undertaken with PAMS (Photogrammetric Aerial Mapping System) by Germap, Germany, which is briefly introduced. This system is based on the SmartPlane fixed-wing UAV and a CANON IXUS camera system. The plane is equipped with GPS and has an infrared sensor system to estimate attitude values. A software has been developed to link the PAMS output to a standard photogrammetric processing chain built on Trimble INPHO. The linking of the image files and image IDs and the handling of different cases with partly corrupted output have to be solved to generate an INPHO project file. Based on this project file the software packages MATCH-AT, MATCH-T DSM, OrthoMaster and OrthoVista for digital aerial triangulation, DTM/DSM generation and finally digital orthomosaik generation are applied. The focus has been on investigations on how to adapt the "usual" parameters for the digital aerial triangulation and other software to the UAV flight conditions, which are showing high overlaps, large kappa angles and a certain image blur in case of turbulences. It was found, that the selected parameter setup shows a quite stable behaviour and can be applied to other flights. A comparison is made to results from other open source multi-ray matching software to handle the issue of the described flight conditions. Flights over the same area at different times have been compared to each other. The major objective was here to see, on how far differences occur relative to each other, without having access to ground control data, which would have a potential for applications with low requirements on the absolute accuracy. The results show, that there are influences of weather and illumination visible. The "unusual" flight pattern, which shows big time differences for neighbouring strips has an influence on the AT and DTM/DSM generation. The results obtained so far do indicate problems in the stability of the camera calibration. This clearly requests a usage of GCPs for all

The Combination of Spherical Photogrammetry and UAV for 3D Modeling

NASA Astrophysics Data System (ADS)

Ihsanudin, T.; Affriani, A. R.

2017-12-01

The complete of 3D models required the object that was recorded from both side and top. If the object recorded from above, then the object from the side can not be covered, and if the objects recorded from the side, it can not be covered from the top. Recording of objects from the side using spherical photogrammetry method and from the top using UAV method. The merge of both models using a conform transformation, by bringing the spherical photogrammetry coordinates system to the UAV model. The object of this research is Ratu Boko temple, Sleman, Yogyakarta. The spherical photogrammetry recording was performed by rotating the camera in 360° angle on the entire area of the temple. The area consists of 12 stations. The UAV method uses a drone with flight attitude of 20 meters. The merge of the both models produced the completeness of the temple model from the top and side.

a Redundant Gnss-Ins Low-Cost Uav Navigation Solution for Professional Applications

NASA Astrophysics Data System (ADS)

Navarro, J.; Parés, M. E.; Colomina, I.; Bianchi, G.; Pluchino, S.; Baddour, R.; Consoli, A.; Ayadi, J.; Gameiro, A.; Sekkas, O.; Tsetsos, V.; Gatsos, T.; Navoni, R.

2015-08-01

This paper presents the current results for the FP7 GINSEC project. Its goal is to build a pre-commercial prototype of a low-cost, accurate and reliable system for the professional UAV market. Low-cost, in this context, stands for the use of sensors in the most affordable segment of the market, especially MEMS IMUs and GNSS receivers. Reliability applies to the ability of the autopilot to cope with situations where unfavourable GNSS reception conditions or strong electromagnetic fields make the computation of the position and / or attitude of the UAV difficult. Professional and accurate mean that, at least using post-processing techniques as PPP, it will be possible to reach cm-level precisions that open the door to a range of applications demanding high levels of quality in positioning, as precision agriculture or mapping. To achieve such goal, a rigorous sensor error modelling approach, the use of redundant IMUs and a dual-GNSS receiver setup, together with close-coupling techniques and an extended Kalman filter with self-analysis capabilities have been used. Although the project is not yet complete, the results obtained up to now prove the feasibility of the aforementioned goal, especially in those aspects related to position determination. Research work is still undergoing to estimate the heading using a dual-GNNS receiver setup; preliminary results prove the validity of this approach for relatively long baselines, although positive results are expected when these are shorter than 1 m - which is a necessary requisite for small-sized UAVs.

Multisensor Equipped Uav/ugv for Automated Exploration

NASA Astrophysics Data System (ADS)

Batzdorfer, S.; Bobbe, M.; Becker, M.; Harms, H.; Bestmann, U.

2017-08-01

The usage of unmanned systems for exploring disaster scenarios has become more and more important in recent times as a supporting system for action forces. These systems have to offer a well-balanced relationship between the quality of support and additional workload. Therefore within the joint research project ANKommEn - german acronym for Automated Navigation and Communication for Exploration - a system for exploration of disaster scenarios is build-up using multiple UAV und UGV controlled via a central ground station. The ground station serves as user interface for defining missions and tasks conducted by the unmanned systems, equipped with different environmental sensors like cameras - RGB as well as IR - or LiDAR. Depending on the exploration task results, in form of pictures, 2D stitched orthophoto or LiDAR point clouds will be transmitted via datalinks and displayed online at the ground station or will be processed in short-term after a mission, e.g. 3D photogrammetry. For mission planning and its execution, UAV/UGV monitoring and georeferencing of environmental sensor data, reliable positioning and attitude information is required. This is gathered using an integrated GNSS/IMU positioning system. In order to increase availability of positioning information in GNSS challenging scenarios, a GNSS-Multiconstellation based approach is used, amongst others. The present paper focuses on the overall system design including the ground station and sensor setups on the UAVs and UGVs, the underlying positioning techniques as well as 2D and 3D exploration based on a RGB camera mounted on board the UAV and its evaluation based on real world field tests.

Multi-UAV Collaborative Sensor Management for UAV Team Survivability

DTIC Science & Technology

2006-08-01

Multi-UAV Collaborative Sensor Management for UAV Team Survivability Craig Stoneking, Phil DiBona , and Adria Hughes Lockheed Martin Advanced...Command, Aviation Applied Technology Directorate. REFERENCES [1] DiBona , P., Belov, N., Pawlowski, A. (2006). “Plan-Driven Fusion: Shaping the

Estimation of attitude sensor timetag biases

NASA Technical Reports Server (NTRS)

Sedlak, J.

1995-01-01

This paper presents an extended Kalman filter for estimating attitude sensor timing errors. Spacecraft attitude is determined by finding the mean rotation from a set of reference vectors in inertial space to the corresponding observed vectors in the body frame. Any timing errors in the observations can lead to attitude errors if either the spacecraft is rotating or the reference vectors themselves vary with time. The state vector here consists of the attitude quaternion, timetag biases, and, optionally, gyro drift rate biases. The filter models the timetags as random walk processes: their expectation values propagate as constants and white noise contributes to their covariance. Thus, this filter is applicable to cases where the true timing errors are constant or slowly varying. The observability of the state vector is studied first through an examination of the algebraic observability condition and then through several examples with simulated star tracker timing errors. The examples use both simulated and actual flight data from the Extreme Ultraviolet Explorer (EUVE). The flight data come from times when EUVE had a constant rotation rate, while the simulated data feature large angle attitude maneuvers. The tests include cases with timetag errors on one or two sensors, both constant and time-varying, and with and without gyro bias errors. Due to EUVE's sensor geometry, the observability of the state vector is severely limited when the spacecraft rotation rate is constant. In the absence of attitude maneuvers, the state elements are highly correlated, and the state estimate is unreliable. The estimates are particularly sensitive to filter mistuning in this case. The EUVE geometry, though, is a degenerate case having coplanar sensors and rotation vector. Observability is much improved and the filter performs well when the rate is either varying or noncoplanar with the sensors, as during a slew. Even with bad geometry and constant rates, if gyro biases are

Entropy-based adaptive attitude estimation

NASA Astrophysics Data System (ADS)

Kiani, Maryam; Barzegar, Aylin; Pourtakdoust, Seid H.

2018-03-01

Gaussian approximation filters have increasingly been developed to enhance the accuracy of attitude estimation in space missions. The effective employment of these algorithms demands accurate knowledge of system dynamics and measurement models, as well as their noise characteristics, which are usually unavailable or unreliable. An innovation-based adaptive filtering approach has been adopted as a solution to this problem; however, it exhibits two major challenges, namely appropriate window size selection and guaranteed assurance of positive definiteness for the estimated noise covariance matrices. The current work presents two novel techniques based on relative entropy and confidence level concepts in order to address the abovementioned drawbacks. The proposed adaptation techniques are applied to two nonlinear state estimation algorithms of the extended Kalman filter and cubature Kalman filter for attitude estimation of a low earth orbit satellite equipped with three-axis magnetometers and Sun sensors. The effectiveness of the proposed adaptation scheme is demonstrated by means of comprehensive sensitivity analysis on the system and environmental parameters by using extensive independent Monte Carlo simulations.

Volumetric calculation using low cost unmanned aerial vehicle (UAV) approach

NASA Astrophysics Data System (ADS)

Rahman, A. A. Ab; Maulud, K. N. Abdul; Mohd, F. A.; Jaafar, O.; Tahar, K. N.

2017-12-01

Unmanned Aerial Vehicles (UAV) technology has evolved dramatically in the 21st century. It is used by both military and general public for recreational purposes and mapping work. Operating cost for UAV is much cheaper compared to that of normal aircraft and it does not require a large work space. The UAV systems have similar functions with the LIDAR and satellite images technologies. These systems require a huge cost, labour and time consumption to produce elevation and dimension data. Measurement of difficult objects such as water tank can also be done by using UAV. The purpose of this paper is to show the capability of UAV to compute the volume of water tank based on a different number of images and control points. The results were compared with the actual volume of the tank to validate the measurement. In this study, the image acquisition was done using Phantom 3 Professional, which is a low cost UAV. The analysis in this study is based on different volume computations using two and four control points with variety set of UAV images. The results show that more images will provide a better quality measurement. With 95 images and four GCP, the error percentage to the actual volume is about 5%. Four controls are enough to get good results but more images are needed, estimated about 115 until 220 images. All in all, it can be concluded that the low cost UAV has a potential to be used for volume of water and dimension measurement.

UAV Cooperation Architectures for Persistent Sensing

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

Roberts, R S; Kent, C A; Jones, E D

2003-03-20

With the number of small, inexpensive Unmanned Air Vehicles (UAVs) increasing, it is feasible to build multi-UAV sensing networks. In particular, by using UAVs in conjunction with unattended ground sensors, a degree of persistent sensing can be achieved. With proper UAV cooperation algorithms, sensing is maintained even though exceptional events, e.g., the loss of a UAV, have occurred. In this paper a cooperation technique that allows multiple UAVs to perform coordinated, persistent sensing with unattended ground sensors over a wide area is described. The technique automatically adapts the UAV paths so that on the average, the amount of time thatmore » any sensor has to wait for a UAV revisit is minimized. We also describe the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture. This architecture is designed to help simulate and operate distributed sensor networks where multiple UAVs are used to collect data.« less

UAV Control on the Basis of 3D Landmark Bearing-Only Observations.

PubMed

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-11-27

The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks' position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations.

UAV Control on the Basis of 3D Landmark Bearing-Only Observations

PubMed Central

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-01-01

The article presents an approach to the control of a UAV on the basis of 3D landmark observations. The novelty of the work is the usage of the 3D RANSAC algorithm developed on the basis of the landmarks’ position prediction with the aid of a modified Kalman-type filter. Modification of the filter based on the pseudo-measurements approach permits obtaining unbiased UAV position estimation with quadratic error characteristics. Modeling of UAV flight on the basis of the suggested algorithm shows good performance, even under significant external perturbations. PMID:26633394

The application of micro UAV in construction project

NASA Astrophysics Data System (ADS)

Kaamin, Masiri; Razali, Siti Nooraiin Mohd; Ahmad, Nor Farah Atiqah; Bukari, Saifullizan Mohd; Ngadiman, Norhayati; Kadir, Aslila Abd; Hamid, Nor Baizura

2017-10-01

In every outstanding construction project, there is definitely have an effective construction management. Construction management allows a construction project to be implemented according to plan. Every construction project must have a progress development works that is usually created by the site engineer. Documenting the progress of works is one of the requirements in construction management. In a progress report it is necessarily have a visual image as an evidence. The conventional method used for photographing on the construction site is by using common digital camera which is has few setback comparing to Micro Unmanned Aerial Vehicles (UAV). Besides, site engineer always have a current issues involving limitation of monitoring on high reach point and entire view of the construction site. The purpose of this paper is to provide a concise review of Micro UAV technology in monitoring the progress on construction site through visualization approach. The aims of this study are to replace the conventional method of photographing on construction site using Micro UAV which can portray the whole view of the building, especially on high reach point and allows to produce better images, videos and 3D model and also facilitating site engineer to monitor works in progress. The Micro UAV was flown around the building construction according to the Ground Control Points (GCPs) to capture images and record videos. The images taken from Micro UAV have been processed generate 3D model and were analysed to visualize the building construction as well as monitoring the construction progress work and provides immediate reliable data for project estimation. It has been proven that by using Micro UAV, a better images and videos can give a better overview of the construction site and monitor any defects on high reach point building structures. Not to be forgotten, with Micro UAV the construction site progress is more efficiently tracked and kept on the schedule.

GPS Remote Sensing Measurements Using Aerosonde UAV

NASA Technical Reports Server (NTRS)

Grant, Michael S.; Katzberg, Stephen J.; Lawrence, R. W.

2005-01-01

In February 2004, a NASA-Langley GPS Remote Sensor (GPSRS) unit was flown on an Aerosonde unmanned aerial vehicle (UAV) from the Wallops Flight Facility (WFF) in Virginia. Using direct and surface-reflected 1.575 GHz coarse acquisition (C/A) coded GPS signals, remote sensing measurements were obtained over land and portions of open water. The strength of the surface-reflected GPS signal is proportional to the amount of moisture in the surface, and is also influenced by surface roughness. Amplitude and other characteristics of the reflected signal allow an estimate of wind speed over open water. In this paper we provide a synopsis of the instrument accommodation requirements, installation procedures, and preliminary results from what is likely the first-ever flight of a GPS remote sensing instrument on a UAV. The correct operation of the GPSRS unit on this flight indicates that Aerosonde-like UAV's can serve as platforms for future GPS remote sensing science missions.

Unmanned air vehicle (UAV) ultra-persitence research

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

Dron, S. B.

2012-03-01

Sandia National Laboratories and Northrop Grumman Corporation Integrated Systems, Unmanned Systems (NGIS UMS) collaborated to further ultra-persistence technologies for unmanned air vehicles (UAVs). The greatest shortfalls in UAV capabilities have been repeatedly identified as (1) insufficient flight persistence or 'hang time,' (2) marginal electrical power for running higher power avionics and payload systems, and (3) inadequate communications bandwidth and reach. NGIS UMS requested support from Sandia to develop an ultra-persistent propulsion and power system (UP3S) for potential incorporation into next generation UAV systems. The team members tried to determine which energy storage and power generation concepts could most effectively pushmore » UAV propulsion and electrical power capabilities to increase UAV sortie duration from days to months while increasing available electrical power at least two-fold. Primary research and development areas that were pursued included these goals: perform general system engineering and integration analyses; develop initial thermal and electrical power estimates; provide mass, volume, dimensional, and balance estimates; conduct preliminary safety assessments; assess logistics support requirements; perform, preliminary assessments of any security and safeguards; evaluate options for removal, replacement, and disposition of materials; generally advance the potential of the UP3S concept. The effort contrasted and compared eight heat sources technologies, three power conversion, two dual cycle propulsion system configurations, and a single electrical power generation scheme. Overall performance, specific power parameters, technical complexities, security, safety, and other operational features were successfully investigated. Large and medium sized UAV systems were envisioned and operational flight profiles were developed for each concept. Heat source creation and support challenges for domestic and expeditionary operations were

A robust two-way switching control system for remote piloting and stabilization of low-cost quadrotor UAVs

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Vivani, Andrea

2015-04-01

The aim of this paper is to present two control logics and an attitude estimator for UAV stabilization and remote piloting, that are as robust as possible to physical parameters variation and to other external disturbances. Moreover, they need to be implemented on low-cost micro-controllers, in order to be attractive for commercial drones. As an example, possible applications of the two switching control logics could be area surveillance and facial recognition by means of a camera mounted on the drone: the high computational speed logic is used to reach the target, when the high-stability one is activated, in order to complete the recognition tasks.

Optimal design of UAV's pod shape

NASA Astrophysics Data System (ADS)

Wei, Qun; Jia, Hong-guang

2011-08-01

In the modern war, UAV(unmanned aircraft system) plays a more and more important role in the army. UAVs always carry electrical-optical reconnaissance systems. These systems are used to accomplish the missions of observing and reconnaissance the battlefield. For traditional UAV, the shape of the pod on UAV is sphericity. In addition, the pod of UAV not only has the job of observing and reconnaissance the battlefield, but its shape also has impact on the UAV's drag when it flies in the air. In this paper, two different kinds of pod models are set up, one is the traditional sphericity model, the other is a new model. Unstructured grid is used on the flow field. Using CFD(computational fluid dynamic) method, the results of the drags of the different kinds of pod are got. The drag's relationship between the pod and the UAV is obtained by comparing the results of simulations. After analyzing the results we can get: when UAV flies at low speed(0.3Ma{0.7Ma), the drag's difference between the two kinds of pod is little, the pod's drag takes a small part of the UAV's whole drag which is only about 14%. At transonic speed(0.8Ma{1.2Ma), the drag's difference between these two kinds of pod is getting bigger and bigger along with the speed goes higher. The traditional pod's drag is 1/3 of the UAV's whole drag value, but for the new pod, it is only 1/5. At supersonic speed(1.3Ma{2.0Ma), the traditional pod's drag goes up rapidly, but the new kind of pod's drag goes up slowly. This makes the difference between the two kinds of UAVs' total drag comes greater. For example, at 2Ma, the total drag of new UAV is only 2/3 of the traditional UAV. These results show: when the UAV flies at low speed, these two kinds of pod have little difference in drag. But if it flies at supersonic speed, the pod has great impact on the UAV's total drag, so the designer of UAV's pod should pay more attention on the out shape.

Attitude/attitude-rate estimation from GPS differential phase measurements using integrated-rate parameters

NASA Technical Reports Server (NTRS)

Oshman, Yaakov; Markley, Landis

1998-01-01

A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.

Attitude estimation of earth orbiting satellites by decomposed linear recursive filters

NASA Technical Reports Server (NTRS)

Kou, S. R.

1975-01-01

Attitude estimation of earth orbiting satellites (including Large Space Telescope) subjected to environmental disturbances and noises was investigated. Modern control and estimation theory is used as a tool to design an efficient estimator for attitude estimation. Decomposed linear recursive filters for both continuous-time systems and discrete-time systems are derived. By using this accurate estimation of the attitude of spacecrafts, state variable feedback controller may be designed to achieve (or satisfy) high requirements of system performance.

Prognostics Applied to Electric Propulsion UAV

NASA Technical Reports Server (NTRS)

Goebel, Kai; Saha, Bhaskar

2013-01-01

Health management plays an important role in operations of UAV. If there is equipment malfunction on critical components, safe operation of the UAV might possibly be compromised. A technology with particular promise in this arena is equipment prognostics. This technology provides a state assessment of the health of components of interest and, if a degraded state has been found, it estimates how long it will take before the equipment will reach a failure threshold, conditional on assumptions about future operating conditions and future environmental conditions. This chapter explores the technical underpinnings of how to perform prognostics and shows an implementation on the propulsion of an electric UAV. A particle filter is shown as the method of choice in performing state assessment and predicting future degradation. The method is then applied to the batteries that provide power to the propeller motors. An accurate run-time battery life prediction algorithm is of critical importance to ensure the safe operation of the vehicle if one wants to maximize in-air time. Current reliability based techniques turn out to be insufficient to manage the use of such batteries where loads vary frequently in uncertain environments.

Uav Cameras: Overview and Geometric Calibration Benchmark

NASA Astrophysics Data System (ADS)

Cramer, M.; Przybilla, H.-J.; Zurhorst, A.

2017-08-01

Different UAV platforms and sensors are used in mapping already, many of them equipped with (sometimes) modified cameras as known from the consumer market. Even though these systems normally fulfil their requested mapping accuracy, the question arises, which system performs best? This asks for a benchmark, to check selected UAV based camera systems in well-defined, reproducible environments. Such benchmark is tried within this work here. Nine different cameras used on UAV platforms, representing typical camera classes, are considered. The focus is laid on the geometry here, which is tightly linked to the process of geometrical calibration of the system. In most applications the calibration is performed in-situ, i.e. calibration parameters are obtained as part of the project data itself. This is often motivated because consumer cameras do not keep constant geometry, thus, cannot be seen as metric cameras. Still, some of the commercial systems are quite stable over time, as it was proven from repeated (terrestrial) calibrations runs. Already (pre-)calibrated systems may offer advantages, especially when the block geometry of the project does not allow for a stable and sufficient in-situ calibration. Especially for such scenario close to metric UAV cameras may have advantages. Empirical airborne test flights in a calibration field have shown how block geometry influences the estimated calibration parameters and how consistent the parameters from lab calibration can be reproduced.

Hurricane Harvey Building Damage Assessment Using UAV Data

NASA Astrophysics Data System (ADS)

Yeom, J.; Jung, J.; Chang, A.; Choi, I.

2017-12-01

Hurricane Harvey which was extremely destructive major hurricane struck southern Texas, U.S.A on August 25, causing catastrophic flooding and storm damages. We visited Rockport suffered severe building destruction and conducted UAV (Unmanned Aerial Vehicle) surveying for building damage assessment. UAV provides very high resolution images compared with traditional remote sensing data. In addition, prompt and cost-effective damage assessment can be performed regardless of several limitations in other remote sensing platforms such as revisit interval of satellite platforms, complicated flight plan in aerial surveying, and cloud amounts. In this study, UAV flight and GPS surveying were conducted two weeks after hurricane damage to generate an orthomosaic image and a DEM (Digital Elevation Model). 3D region growing scheme has been proposed to quantitatively estimate building damages considering building debris' elevation change and spectral difference. The result showed that the proposed method can be used for high definition building damage assessment in a time- and cost-effective way.

Guidance and Control of an Autonomous Soaring UAV

NASA Technical Reports Server (NTRS)

Allen, Michael J.; Lin, Victor

2007-01-01

Thermals caused by convection in the lower atmosphere are commonly used by birds and glider pilots to extend flight duration, increase cross-country speed, improve range, or simply to conserve energy. Uninhabited Aerial Vehicles (UAVs) can also increase performance and reduce energy consumption by exploiting atmospheric convection. An autonomous soaring research project was conducted at the NASA Dryden Flight Research Center to evaluate the concept through flight test of an electric-powered motorglider with a wingspan of 4.27 m (14 ft). The UAV's commercial autopilot software was modified to include outer-loop soaring guidance and control. The aircraft total energy state was used to detect and soar within thermals. Estimated thermal size and position were used to calculate guidance commands for soaring flight. Results from a total of 23 thermal encounters show good performance of the guidance and control algorithms to autonomously detect and exploit thermals. The UAV had an average climb of 172 m (567 ft) during these encounters.

Guidance and Control of an Autonomous Soaring UAV

NASA Technical Reports Server (NTRS)

Allen, Michael J.

2007-01-01

Thermals caused by convection in the lower atmosphere are commonly used by birds and glider pilots to extend flight duration, increase cross-country speed, improve range, or simply to conserve energy. Uninhabited Aerial Vehicles (UAVs) can also increase performance and reduce energy consumption by exploiting atmospheric convection. An autonomous soaring research project was conducted at the NASA Dryden Flight Research Center to evaluate the concept through flight test of an electric-powered motor-glider with a wingspan of 4.27 m (14 ft). The UAV's commercial autopilot software was modified to include outer-loop soaring guidance and control. The aircraft total energy state was used to detect and soar within thermals. Estimated thermal size and position were used to calculate guidance commands for soaring flight. Results from a total of 23 thermal encounters show good performance of the guidance and control algorithms to autonomously detect and exploit thermals. The UAV had an average climb of 172 m (567 ft) during these encounters.

Kalman Filter for Spinning Spacecraft Attitude Estimation

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Sedlak, Joseph E.

2008-01-01

This paper presents a Kalman filter using a seven-component attitude state vector comprising the angular momentum components in an inertial reference frame, the angular momentum components in the body frame, and a rotation angle. The relatively slow variation of these parameters makes this parameterization advantageous for spinning spacecraft attitude estimation. The filter accounts for the constraint that the magnitude of the angular momentum vector is the same in the inertial and body frames by employing a reduced six-component error state. Four variants of the filter, defined by different choices for the reduced error state, are tested against a quaternion-based filter using simulated data for the THEMIS mission. Three of these variants choose three of the components of the error state to be the infinitesimal attitude error angles, facilitating the computation of measurement sensitivity matrices and causing the usual 3x3 attitude covariance matrix to be a submatrix of the 6x6 covariance of the error state. These variants differ in their choice for the other three components of the error state. The variant employing the infinitesimal attitude error angles and the angular momentum components in an inertial reference frame as the error state shows the best combination of robustness and efficiency in the simulations. Attitude estimation results using THEMIS flight data are also presented.

Wilkinson Microwave Anisotropy Probe (WMAP) Attitude Estimation Filter Comparison

NASA Technical Reports Server (NTRS)

Harman, Richard R.

2005-01-01

The Wilkinson Microwave Anisotropy Probe (WMAP) spacecraft was launched in June of 2001. The sensor complement of WMAP consists of two Autonomous Star Trackers (ASTs), two Fine Sun Sensors (FSSs), and a gyro package which contains redundancy about one of the WMAP body axes. The onboard attitude estimation filter consists of an extended Kalman filter (EKF) solving for attitude and gyro bias errors which are then resolved into a spacecraft attitude quaternion and gyro bias. A pseudo-linear Kalman filter has been developed which directly estimates the spacecraft attitude quaternion, rate, and gyro bias. In this paper, the performance of the two filters is compared for the two major control modes of WMAP: inertial mode and observation mode.

Multiple scene attitude estimator performance for LANDSAT-1

NASA Technical Reports Server (NTRS)

Rifman, S. S.; Monuki, A. T.; Shortwell, C. P.

1979-01-01

Initial results are presented to demonstrate the performance of a linear sequential estimator (Kalman Filter) used to estimate a LANDSAT 1 spacecraft attitude time series defined for four scenes. With the revised estimator a GCP poor scene - a scene with no usable geodetic control points (GCPs) - can be rectified to higher accuracies than otherwise based on the use of GCPs in adjacent scenes. Attitude estimation errors was determined by the use of GCPs located in the GCP-poor test scene, but which are not used to update the Kalman filter. Initial results achieved indicate that errors of 500m (rms) can be attained for the GCP-poor scenes. Operational factors are related to various scenarios.

Spurious RF signals emitted by mini-UAVs

NASA Astrophysics Data System (ADS)

Schleijpen, Ric (H. M. A.); Voogt, Vincent; Zwamborn, Peter; van den Oever, Jaap

2016-10-01

This paper presents experimental work on the detection of spurious RF emissions of mini Unmanned Aerial Vehicles (mini-UAV). Many recent events have shown that mini-UAVs can be considered as a potential threat for civil security. For this reason the detection of mini-UAVs has become of interest to the sensor community. The detection, classification and identification chain can take advantage of different sensor technologies. Apart from the signatures used by radar and electro-optical sensor systems, the UAV also emits RF signals. These RF signatures can be split in intentional signals for communication with the operator and un-intentional RF signals emitted by the UAV. These unintentional or spurious RF emissions are very weak but could be used to discriminate potential UAV detections from false alarms. The goal of this research was to assess the potential of exploiting spurious emissions in the classification and identification chain of mini-UAVs. It was already known that spurious signals are very weak, but the focus was on the question whether the emission pattern could be correlated to the behaviour of the UAV. In this paper experimental examples of spurious RF emission for different types of mini-UAVs and their correlation with the electronic circuits in the UAVs will be shown

French MALE UAV Program

DTIC Science & Technology

2003-09-02

ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) MoD- France 8...1French Air Force MINISTÈRE DE LA DÉFENSE 1 SIDM CONOPS 2 FAF IMAGERY ARCHITECTURE 3 FUTURE FRENCH MALE UAV PROGRAM FRENCH MALE UAV PROGRAM Report...2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE French Male UAV Program 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

Autonomous unmanned air vehicles (UAV) techniques

NASA Astrophysics Data System (ADS)

Hsu, Ming-Kai; Lee, Ting N.

2007-04-01

The UAVs (Unmanned Air Vehicles) have great potentials in different civilian applications, such as oil pipeline surveillance, precision farming, forest fire fighting (yearly), search and rescue, boarder patrol, etc. The related industries of UAVs can create billions of dollars for each year. However, the road block of adopting UAVs is that it is against FAA (Federal Aviation Administration) and ATC (Air Traffic Control) regulations. In this paper, we have reviewed the latest technologies and researches on UAV navigation and obstacle avoidance. We have purposed a system design of Jittering Mosaic Image Processing (JMIP) with stereo vision and optical flow to fulfill the functionalities of autonomous UAVs.

Diverse Planning for UAV Control and Remote Sensing

PubMed Central

Tožička, Jan; Komenda, Antonín

2016-01-01

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs. PMID:28009831

Diverse Planning for UAV Control and Remote Sensing.

PubMed

Tožička, Jan; Komenda, Antonín

2016-12-21

Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs.

Accurate Attitude Estimation Using ARS under Conditions of Vehicle Movement Based on Disturbance Acceleration Adaptive Estimation and Correction

PubMed Central

Xing, Li; Hang, Yijun; Xiong, Zhi; Liu, Jianye; Wan, Zhong

2016-01-01

This paper describes a disturbance acceleration adaptive estimate and correction approach for an attitude reference system (ARS) so as to improve the attitude estimate precision under vehicle movement conditions. The proposed approach depends on a Kalman filter, where the attitude error, the gyroscope zero offset error and the disturbance acceleration error are estimated. By switching the filter decay coefficient of the disturbance acceleration model in different acceleration modes, the disturbance acceleration is adaptively estimated and corrected, and then the attitude estimate precision is improved. The filter was tested in three different disturbance acceleration modes (non-acceleration, vibration-acceleration and sustained-acceleration mode, respectively) by digital simulation. Moreover, the proposed approach was tested in a kinematic vehicle experiment as well. Using the designed simulations and kinematic vehicle experiments, it has been shown that the disturbance acceleration of each mode can be accurately estimated and corrected. Moreover, compared with the complementary filter, the experimental results have explicitly demonstrated the proposed approach further improves the attitude estimate precision under vehicle movement conditions. PMID:27754469

Accurate Attitude Estimation Using ARS under Conditions of Vehicle Movement Based on Disturbance Acceleration Adaptive Estimation and Correction.

PubMed

Xing, Li; Hang, Yijun; Xiong, Zhi; Liu, Jianye; Wan, Zhong

2016-10-16

This paper describes a disturbance acceleration adaptive estimate and correction approach for an attitude reference system (ARS) so as to improve the attitude estimate precision under vehicle movement conditions. The proposed approach depends on a Kalman filter, where the attitude error, the gyroscope zero offset error and the disturbance acceleration error are estimated. By switching the filter decay coefficient of the disturbance acceleration model in different acceleration modes, the disturbance acceleration is adaptively estimated and corrected, and then the attitude estimate precision is improved. The filter was tested in three different disturbance acceleration modes (non-acceleration, vibration-acceleration and sustained-acceleration mode, respectively) by digital simulation. Moreover, the proposed approach was tested in a kinematic vehicle experiment as well. Using the designed simulations and kinematic vehicle experiments, it has been shown that the disturbance acceleration of each mode can be accurately estimated and corrected. Moreover, compared with the complementary filter, the experimental results have explicitly demonstrated the proposed approach further improves the attitude estimate precision under vehicle movement conditions.

Commercial vs professional UAVs for mapping

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Koukouvelas, Ioannis

2017-09-01

The continuous advancements in the technology behind Unmanned Aerial Vehicles (UAVs), in accordance with the consecutive decrease to their cost and the availability of photogrammetric software, make the use of UAVs an excellent tool for large scale mapping. In addition with the use of UAVs, the problems of increased costs, time consumption and the possible terrain accessibility problems, are significantly reduced. However, despite the growing number of UAV applications there has been a little quantitative assessment of UAV performance and of the quality of the derived products (orthophotos and Digital Surface Models). Here, we present results from field experiments designed to evaluate the accuracy of photogrammetrically-derived digital surface models (DSM) developed from imagery acquired with onboard digital cameras. We also show the comparison of the high resolution vs moderate resolution imagery for largescale geomorphic mapping. The acquired data analyzed in this study comes from a small commercial and a professional UAV. The test area was mapped using the same photogrammetric grid by the two UAVs. 3D models, DSMs and orthophotos were created using special software. Those products were compared to in situ survey measurements and the results are presented in this paper.

Water level observations from Unmanned Aerial Vehicles (UAVs) for improving probabilistic estimations of interaction between rivers and groundwater

NASA Astrophysics Data System (ADS)

Bandini, Filippo; Butts, Michael; Vammen Jacobsen, Torsten; Bauer-Gottwein, Peter

2016-04-01

Integrated hydrological models are generally calibrated against observations of river discharge and piezometric head in groundwater aquifers. Integrated hydrological models are rarely calibrated against spatially distributed water level observations measured by either in-situ stations or spaceborne platforms. Indeed in-situ observations derived from ground-based stations are generally spaced too far apart to capture spatial patterns in the water surface. On the other hand spaceborne observations have limited spatial resolution. Additionally satellite observations have a temporal resolution which is not ideal for observing the temporal patterns of the hydrological variables during extreme events. UAVs (Unmanned Aerial Vehicles) offer several advantages: i) high spatial resolution; ii) tracking of the water body better than any satellite technology; iii) timing of the sampling merely depending on the operators. In this case study the Mølleåen river (Denmark) and its catchment have been simulated through an integrated hydrological model (MIKE 11-MIKE SHE). This model was initially calibrated against observations of river discharge retrieved by in-situ stations and against piezometric head of the aquifers. Subsequently the hydrological model has been calibrated against dense spatially distributed water level observations, which could potentially be retrieved by UAVs. Error characteristics of synthetic UAV water level observations were taken from a recent proof-of-concept study. Since the technology for ranging water level is under development, UAV synthetic water level observations were extracted from another model of the river with higher spatial resolution (cross sections located every 10 m). This model with high resolution is assumed to be absolute truth for the purpose of this work. The river model with the coarser resolution has been calibrated against the synthetic water level observations through Differential Evolution Adaptive Metropolis (DREAM) algorithm, an

Robust double gain unscented Kalman filter for small satellite attitude estimation

NASA Astrophysics Data System (ADS)

Cao, Lu; Yang, Weiwei; Li, Hengnian; Zhang, Zhidong; Shi, Jianjun

2017-08-01

Limited by the low precision of small satellite sensors, the estimation theories with high performance remains the most popular research topic for the attitude estimation. The Kalman filter (KF) and its extensions have been widely applied in the satellite attitude estimation and achieved plenty of achievements. However, most of the existing methods just take use of the current time-step's priori measurement residuals to complete the measurement update and state estimation, which always ignores the extraction and utilization of the previous time-step's posteriori measurement residuals. In addition, the uncertainty model errors always exist in the attitude dynamic system, which also put forward the higher performance requirements for the classical KF in attitude estimation problem. Therefore, the novel robust double gain unscented Kalman filter (RDG-UKF) is presented in this paper to satisfy the above requirements for the small satellite attitude estimation with the low precision sensors. It is assumed that the system state estimation errors can be exhibited in the measurement residual; therefore, the new method is to derive the second Kalman gain Kk2 for making full use of the previous time-step's measurement residual to improve the utilization efficiency of the measurement data. Moreover, the sequence orthogonal principle and unscented transform (UT) strategy are introduced to robust and enhance the performance of the novel Kalman Filter in order to reduce the influence of existing uncertainty model errors. Numerical simulations show that the proposed RDG-UKF is more effective and robustness in dealing with the model errors and low precision sensors for the attitude estimation of small satellite by comparing with the classical unscented Kalman Filter (UKF).

Application of Vehicle Dynamic Modeling in Uavs for Precise Determination of Exterior Orientation

NASA Astrophysics Data System (ADS)

Khaghani, M.; Skaloud, J.

2016-06-01

Advances in unmanned aerial vehicles (UAV) and especially micro aerial vehicle (MAV) technology together with increasing quality and decreasing price of imaging devices have resulted in growing use of MAVs in photogrammetry. The practicality of MAV mapping is seriously enhanced with the ability to determine parameters of exterior orientation (EO) with sufficient accuracy, in both absolute and relative senses (change of attitude between successive images). While differential carrier phase GNSS satisfies cm-level positioning accuracy, precise attitude determination is essential for both direct sensor orientation (DiSO) and integrated sensor orientation (ISO) in corridor mapping or in block configuration imaging over surfaces with low texture. Limited cost, size, and weight of MAVs represent limitations on quality of onboard navigation sensors and puts emphasis on exploiting full capacity of available resources. Typically short flying times (10-30 minutes) also limit the possibility of estimating and/or correcting factors such as sensor misalignment and poor attitude initialization of inertial navigation system (INS). This research aims at increasing the accuracy of attitude determination in both absolute and relative senses with no extra sensors onboard. In comparison to classical INS/GNSS setup, novel approach is presented here to integrated state estimation, in which vehicle dynamic model (VDM) is used as the main process model. Such system benefits from available information from autopilot and physical properties of the platform in enhancing performance of determination of trajectory and parameters of exterior orientation consequently. The navigation system employs a differential carrier phase GNSS receiver and a micro electro-mechanical system (MEMS) grade inertial measurement unit (IMU), together with MAV control input from autopilot. Monte-Carlo simulation has been performed on trajectories for typical corridor mapping and block imaging. Results reveal

Development of Cloud-Based UAV Monitoring and Management System

PubMed Central

Itkin, Mason; Kim, Mihui; Park, Younghee

2016-01-01

Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, we propose a cloud-based web application that provides real-time flight monitoring and management for UAVs. For each connected UAV, detailed UAV sensor readings from the accelerometer, GPS sensor, ultrasonic sensor and visual position cameras are provided along with status reports from the smaller internal components of UAVs (i.e., motor and battery). The dynamic map overlay visualizes active flight paths and current UAV locations, allowing the user to monitor all aircrafts easily. Our system detects and prevents potential collisions by automatically adjusting UAV flight paths and then alerting users to the change. We develop our proposed system and demonstrate its feasibility and performances through simulation. PMID:27854267

Development of Cloud-Based UAV Monitoring and Management System.

PubMed

Itkin, Mason; Kim, Mihui; Park, Younghee

2016-11-15

Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to revolutionize commercial industries and the public domain outside of the military. UAVs would be able to speed up rescue and recovery operations from natural disasters and can be used for autonomous delivery systems (e.g., Amazon Prime Air). An increase in the number of active UAV systems in dense urban areas is attributed to an influx of UAV hobbyists and commercial multi-UAV systems. As airspace for UAV flight becomes more limited, it is important to monitor and manage many UAV systems using modern collision avoidance techniques. In this paper, we propose a cloud-based web application that provides real-time flight monitoring and management for UAVs. For each connected UAV, detailed UAV sensor readings from the accelerometer, GPS sensor, ultrasonic sensor and visual position cameras are provided along with status reports from the smaller internal components of UAVs (i.e., motor and battery). The dynamic map overlay visualizes active flight paths and current UAV locations, allowing the user to monitor all aircrafts easily. Our system detects and prevents potential collisions by automatically adjusting UAV flight paths and then alerting users to the change. We develop our proposed system and demonstrate its feasibility and performances through simulation.

Visual navigation of the UAVs on the basis of 3D natural landmarks

NASA Astrophysics Data System (ADS)

Karpenko, Simon; Konovalenko, Ivan; Miller, Alexander; Miller, Boris; Nikolaev, Dmitry

2015-12-01

This work considers the tracking of the UAV (unmanned aviation vehicle) on the basis of onboard observations of natural landmarks including azimuth and elevation angles. It is assumed that UAV's cameras are able to capture the angular position of reference points and to measure the angles of the sight line. Such measurements involve the real position of UAV in implicit form, and therefore some of nonlinear filters such as Extended Kalman filter (EKF) or others must be used in order to implement these measurements for UAV control. Recently it was shown that modified pseudomeasurement method may be used to control UAV on the basis of the observation of reference points assigned along the UAV path in advance. However, the use of such set of points needs the cumbersome recognition procedure with the huge volume of on-board memory. The natural landmarks serving as such reference points which may be determined on-line can significantly reduce the on-board memory and the computational difficulties. The principal difference of this work is the usage of the 3D reference points coordinates which permits to determine the position of the UAV more precisely and thereby to guide along the path with higher accuracy which is extremely important for successful performance of the autonomous missions. The article suggests the new RANSAC for ISOMETRY algorithm and the use of recently developed estimation and control algorithms for tracking of given reference path under external perturbation and noised angular measurements.

Development and Validation of a UAV Based System for Air Pollution Measurements

PubMed Central

Villa, Tommaso Francesco; Salimi, Farhad; Morton, Kye; Morawska, Lidia; Gonzalez, Felipe

2016-01-01

Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO2, CO, NO2 and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection. PMID:28009820

Development and Validation of a UAV Based System for Air Pollution Measurements.

PubMed

Villa, Tommaso Francesco; Salimi, Farhad; Morton, Kye; Morawska, Lidia; Gonzalez, Felipe

2016-12-21

Air quality data collection near pollution sources is difficult, particularly when sites are complex, have physical barriers, or are themselves moving. Small Unmanned Aerial Vehicles (UAVs) offer new approaches to air pollution and atmospheric studies. However, there are a number of critical design decisions which need to be made to enable representative data collection, in particular the location of the air sampler or air sensor intake. The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions. The research included two different tests: (1) evaluate the air flow behavior of a hexacopter, its downwash and upwash effect, by measuring air speed along three axes to determine the location where the sensors should be mounted; (2) evaluate the use of gas sensors for CO₂, CO, NO₂ and NO, and the PNC monitor (DISCmini) to assess the efficiency and performance of the UAV based system by measuring emissions from a diesel engine. The air speed behavior map produced by test 1 shows the best mounting point for the sensors to be alongside the UAV. This position is less affected by the propeller downwash effect. Test 2 results demonstrated that the UAV propellers cause a dispersion effect shown by the decrease of gas and PN concentration measured in real time. A Linear Regression model was used to estimate how the sensor position, relative to the UAV center, affects pollutant concentration measurements when the propellers are turned on. This research establishes guidelines on how to develop a UAV system to measure point source emissions. Such research should be undertaken before any UAV system is developed for real world data collection.

Unmanned Aerial Vehicles unique cost estimating requirements

NASA Astrophysics Data System (ADS)

Malone, P.; Apgar, H.; Stukes, S.; Sterk, S.

Unmanned Aerial Vehicles (UAVs), also referred to as drones, are aerial platforms that fly without a human pilot onboard. UAVs are controlled autonomously by a computer in the vehicle or under the remote control of a pilot stationed at a fixed ground location. There are a wide variety of drone shapes, sizes, configurations, complexities, and characteristics. Use of these devices by the Department of Defense (DoD), NASA, civil and commercial organizations continues to grow. UAVs are commonly used for intelligence, surveillance, reconnaissance (ISR). They are also use for combat operations, and civil applications, such as firefighting, non-military security work, surveillance of infrastructure (e.g. pipelines, power lines and country borders). UAVs are often preferred for missions that require sustained persistence (over 4 hours in duration), or are “ too dangerous, dull or dirty” for manned aircraft. Moreover, they can offer significant acquisition and operations cost savings over traditional manned aircraft. Because of these unique characteristics and missions, UAV estimates require some unique estimating methods. This paper describes a framework for estimating UAV systems total ownership cost including hardware components, software design, and operations. The challenge of collecting data, testing the sensitivities of cost drivers, and creating cost estimating relationships (CERs) for each key work breakdown structure (WBS) element is discussed. The autonomous operation of UAVs is especially challenging from a software perspective.

Spacecraft Dynamics Should be Considered in Kalman Filter Attitude Estimation

NASA Technical Reports Server (NTRS)

Yang, Yaguang; Zhou, Zhiqiang

2016-01-01

Kalman filter based spacecraft attitude estimation has been used in some high-profile missions and has been widely discussed in literature. While some models in spacecraft attitude estimation include spacecraft dynamics, most do not. To our best knowledge, there is no comparison on which model is a better choice. In this paper, we discuss the reasons why spacecraft dynamics should be considered in the Kalman filter based spacecraft attitude estimation problem. We also propose a reduced quaternion spacecraft dynamics model which admits additive noise. Geometry of the reduced quaternion model and the additive noise are discussed. This treatment is more elegant in mathematics and easier in computation. We use some simulation example to verify our claims.

Multi-temporal UAV based data for mapping crop type and structure in smallholder dominated Tanzanian agricultural landscape

NASA Astrophysics Data System (ADS)

Nagol, J. R.; Chung, C.; Dempewolf, J.; Maurice, S.; Mbungu, W.; Tumbo, S.

2015-12-01

Timely mapping and monitoring of crops like Maize, an important food security crop in Tanzania, can facilitate timely response by government and non-government organizations to food shortage or surplus conditions. Small UAVs can play an important role in linking the spaceborne remote sensing data and ground based measurement to improve the calibration and validation of satellite based estimates of in-season crop metrics. In Tanzania most of the growing season is often obscured by clouds. UAV data, if collected within a stratified statistical sampling framework, can also be used to directly in lieu of spaceborne data to infer mid-season yield estimates at regional scales.Here we present an object based approach to estimate crop metrics like crop type, area, and height using multi-temporal UAV based imagery. The methods were tested at three 1km2 plots in Kilosa, Njombe, and Same districts in Tanzania. At these sites both ground based and UAV based data were collected on a monthly time-step during the year 2015 growing season. SenseFly eBee drone with RGB and NIR-R-G camera was used to collect data. Crop type classification accuracies of above 85% were easily achieved.

Cooperative UAV-Based Communications Backbone for Sensor Networks

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

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Velocity-Aided Attitude Estimation for Helicopter Aircraft Using Microelectromechanical System Inertial-Measurement Units.

PubMed

Lee, Sang Cheol; Hong, Sung Kyung

2016-12-11

This paper presents an algorithm for velocity-aided attitude estimation for helicopter aircraft using a microelectromechanical system inertial-measurement unit. In general, high- performance gyroscopes are used for estimating the attitude of a helicopter, but this type of sensor is very expensive. When designing a cost-effective attitude system, attitude can be estimated by fusing a low cost accelerometer and a gyro, but the disadvantage of this method is its relatively low accuracy. The accelerometer output includes a component that occurs primarily as the aircraft turns, as well as the gravitational acceleration. When estimating attitude, the accelerometer measurement terms other than gravitational ones can be considered as disturbances. Therefore, errors increase in accordance with the flight dynamics. The proposed algorithm is designed for using velocity as an aid for high accuracy at low cost. It effectively eliminates the disturbances of accelerometer measurements using the airspeed. The algorithm was verified using helicopter experimental data. The algorithm performance was confirmed through a comparison with an attitude estimate obtained from an attitude heading reference system based on a high accuracy optic gyro, which was employed as core attitude equipment in the helicopter.

Velocity-Aided Attitude Estimation for Helicopter Aircraft Using Microelectromechanical System Inertial-Measurement Units

PubMed Central

Lee, Sang Cheol; Hong, Sung Kyung

2016-01-01

This paper presents an algorithm for velocity-aided attitude estimation for helicopter aircraft using a microelectromechanical system inertial-measurement unit. In general, high- performance gyroscopes are used for estimating the attitude of a helicopter, but this type of sensor is very expensive. When designing a cost-effective attitude system, attitude can be estimated by fusing a low cost accelerometer and a gyro, but the disadvantage of this method is its relatively low accuracy. The accelerometer output includes a component that occurs primarily as the aircraft turns, as well as the gravitational acceleration. When estimating attitude, the accelerometer measurement terms other than gravitational ones can be considered as disturbances. Therefore, errors increase in accordance with the flight dynamics. The proposed algorithm is designed for using velocity as an aid for high accuracy at low cost. It effectively eliminates the disturbances of accelerometer measurements using the airspeed. The algorithm was verified using helicopter experimental data. The algorithm performance was confirmed through a comparison with an attitude estimate obtained from an attitude heading reference system based on a high accuracy optic gyro, which was employed as core attitude equipment in the helicopter. PMID:27973429

Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing

PubMed Central

Lee, Junhwa; Ahn, Eunjong; Cho, Soojin; Shin, Myoungsu

2017-01-01

Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%. PMID:28880254

Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing.

PubMed

Kim, Hyunjun; Lee, Junhwa; Ahn, Eunjong; Cho, Soojin; Shin, Myoungsu; Sim, Sung-Han

2017-09-07

Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.

Wind and Wake Sensing with UAV Formation Flight: System Development and Flight Testing

NASA Astrophysics Data System (ADS)

Larrabee, Trenton Jameson

Wind turbulence including atmospheric turbulence and wake turbulence have been widely investigated; however, only recently it become possible to use Unmanned Aerial Vehicles (UAVs) as a validation tool for research in this area. Wind can be a major contributing factor of adverse weather for aircraft. More importantly, it is an even greater risk towards UAVs because of their small size and weight. Being able to estimate wind fields and gusts can potentially provide substantial benefits for both unmanned and manned aviation. Possible applications include gust suppression for improving handling qualities, a better warning system for high wind encounters, and enhanced control for small UAVs during flight. On the other hand, the existence of wind can be advantageous since it can lead to fuel savings and longer duration flights through dynamic soaring or thermal soaring. Wakes are an effect of the lift distribution across an aircraft's wing or tail. Wakes can cause substantial disturbances when multiple aircraft are moving through the same airspace. In fact, the perils from an aircraft flying through the wake of another aircraft is a leading cause of the delay between takeoff times at airports. Similar to wind, though, wakes can be useful for energy harvesting and increasing an aircraft's endurance when flying in formation which can be a great advantage to UAVs because they are often limited in flight time due to small payload capacity. Formation flight can most often be seen in manned aircraft but can be adopted for use with unmanned systems. Autonomous flight is needed for flying in the "sweet spot" of the generated wakes for energy harvesting as well as for thermal soaring during long duration flights. For the research presented here formation flight was implemented for the study of wake sensing and gust alleviation. The major contributions of this research are in the areas of a novel technique to estimate wind using an Unscented Kalman filter and experimental wake

Fault tolerant attitude sensing and force feedback control for unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Jagadish, Chirag

Two aspects of an unmanned aerial vehicle are studied in this work. One is fault tolerant attitude determination and the other is to provide force feedback to the joy-stick of the UAV so as to prevent faulty inputs from the pilot. Determination of attitude plays an important role in control of aerial vehicles. One way of defining the attitude is through Euler angles. These angles can be determined based on the measurements of the projections of the gravity and earth magnetic fields on the three body axes of the vehicle. Attitude determination in unmanned aerial vehicles poses additional challenges due to limitations of space, payload, power and cost. Therefore it provides for almost no room for any bulky sensors or extra sensor hardware for backup and as such leaves no room for sensor fault issues either. In the face of these limitations, this study proposes a fault tolerant computing of Euler angles by utilizing multiple different computation methods, with each method utilizing a different subset of the available sensor measurement data. Twenty-five such methods have been presented in this document. The capability of computing the Euler angles in multiple ways provides a diversified redundancy required for fault tolerance. The proposed approach can identify certain sets of sensor failures and even separate the reference fields from the disturbances. A bank-to-turn maneuver of the NASA GTM UAV is used to demonstrate the fault tolerance provided by the proposed method as well as to demonstrate the method of determining the correct Euler angles despite interferences by inertial acceleration disturbances. Attitude computation is essential for stability. But as of today most UAVs are commanded remotely by human pilots. While basic stability control is entrusted to machine or the on-board automatic controller, overall guidance is usually with humans. It is therefore the pilot who sets the command/references through a joy-stick. While this is a good compromise between

Development of Open source-based automatic shooting and processing UAV imagery for Orthoimage Using Smart Camera UAV

NASA Astrophysics Data System (ADS)

Park, J. W.; Jeong, H. H.; Kim, J. S.; Choi, C. U.

2016-06-01

Recently, aerial photography with unmanned aerial vehicle (UAV) system uses UAV and remote controls through connections of ground control system using bandwidth of about 430 MHz radio Frequency (RF) modem. However, as mentioned earlier, existing method of using RF modem has limitations in long distance communication. The Smart Camera equipments's LTE (long-term evolution), Bluetooth, and Wi-Fi to implement UAV that uses developed UAV communication module system carried out the close aerial photogrammetry with the automatic shooting. Automatic shooting system is an image capturing device for the drones in the area's that needs image capturing and software for loading a smart camera and managing it. This system is composed of automatic shooting using the sensor of smart camera and shooting catalog management which manages filmed images and information. Processing UAV imagery module used Open Drone Map. This study examined the feasibility of using the Smart Camera as the payload for a photogrammetric UAV system. The open soure tools used for generating Android, OpenCV (Open Computer Vision), RTKLIB, Open Drone Map.

Real-time UAV trajectory generation using feature points matching between video image sequences

NASA Astrophysics Data System (ADS)

Byun, Younggi; Song, Jeongheon; Han, Dongyeob

2017-09-01

Unmanned aerial vehicles (UAVs), equipped with navigation systems and video capability, are currently being deployed for intelligence, reconnaissance and surveillance mission. In this paper, we present a systematic approach for the generation of UAV trajectory using a video image matching system based on SURF (Speeded up Robust Feature) and Preemptive RANSAC (Random Sample Consensus). Video image matching to find matching points is one of the most important steps for the accurate generation of UAV trajectory (sequence of poses in 3D space). We used the SURF algorithm to find the matching points between video image sequences, and removed mismatching by using the Preemptive RANSAC which divides all matching points to outliers and inliers. The inliers are only used to determine the epipolar geometry for estimating the relative pose (rotation and translation) between image sequences. Experimental results from simulated video image sequences showed that our approach has a good potential to be applied to the automatic geo-localization of the UAVs system

Sine Rotation Vector Method for Attitude Estimation of an Underwater Robot

PubMed Central

Ko, Nak Yong; Jeong, Seokki; Bae, Youngchul

2016-01-01

This paper describes a method for estimating the attitude of an underwater robot. The method employs a new concept of sine rotation vector and uses both an attitude heading and reference system (AHRS) and a Doppler velocity log (DVL) for the purpose of measurement. First, the acceleration and magnetic-field measurements are transformed into sine rotation vectors and combined. The combined sine rotation vector is then transformed into the differences between the Euler angles of the measured attitude and the predicted attitude; the differences are used to correct the predicted attitude. The method was evaluated according to field-test data and simulation data and compared to existing methods that calculate angular differences directly without a preceding sine rotation vector transformation. The comparison verifies that the proposed method improves the attitude estimation performance. PMID:27490549

Observing Crop-Height Dynamics Using a UAV

NASA Astrophysics Data System (ADS)

Ziliani, M. G.; Parkes, S. D.; McCabe, M.

2017-12-01

Retrieval of vegetation height during a growing season is a key indicator for monitoring crop status, offering insight to the forecast yield relative to previous planting cycles. Improvement in Unmanned Aerial Vehicle (UAV) technologies, supported by advances in computer vision and photogrammetry software, has enabled retrieval of crop heights with much higher spatial resolution and coverage. These methodologies retrieve a Digital Surface Map (DSM), which combine terrain and crop elements to obtain a Crop Surface Map (CSM). Here we describe an automated method for deriving high resolution CSMs from a DSM, using RGB imagery from a UAV platform. Importantly, the approach does not require the need for a digital terrain map (DTM). The method involves distinguishing between vegetation and bare-ground cover pixels, using vegetation index maps from the RGB orthomosaic derived from the same flight as the DSM. We show that the absolute crop height can be extracted to within several centimeters, exploiting the data captured from a single UAV flight. In addition, the method is applied across five surveys during a maize growing cycle and compared against a terrain map constructed from a baseline UAV survey undertaken prior to crop growth. Results show that the approach is able to reproduce the observed spatial variability of the crop height within the maize field throughout the duration of the growing season. This is particularly valuable since it may be employed to detect intra-field problems (i.e. fertilizer variability, inefficiency in the irrigation system, salinity etc.) at different stages of the season, from which remedial action can be initiated to mitigate against yield loss. The method also demonstrates that UAV imagery combined with commercial photogrammetry software can determine a CSM from a single flight without the requirement of a prior DTM. This, together with the dynamic crop height estimation, provide useful information with which to inform precision

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults.

PubMed

Sun, Rui; Cheng, Qi; Wang, Guanyu; Ochieng, Washington Yotto

2017-09-29

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

Aeromagnetic Compensation for UAVs

NASA Astrophysics Data System (ADS)

Naprstek, T.; Lee, M. D.

2017-12-01

Aeromagnetic data is one of the most widely collected types of data in exploration geophysics. With the continuing prevalence of unmanned air vehicles (UAVs) in everyday life there is a strong push for aeromagnetic data collection using UAVs. However, apart from the many political and legal barriers to overcome in the development of UAVs as aeromagnetic data collection platforms, there are also significant scientific hurdles, primary of which is magnetic compensation. This is a well-established process in manned aircraft achieved through a combination of platform magnetic de-noising and compensation routines. However, not all of this protocol can be directly applied to UAVs due to fundamental differences in the platforms, most notably the decrease in scale causing magnetometers to be significantly closer to the avionics. As such, the methodology must be suitably adjusted. The National Research Council of Canada has collaborated with Aeromagnetic Solutions Incorporated to develop a standardized approach to de-noising and compensating UAVs, which is accomplished through a series of static and dynamic experiments. On the ground, small static tests are conducted on individual components to determine their magnetization. If they are highly magnetic, they are removed, demagnetized, or characterized such that they can be accounted for in the compensation. Dynamic tests can include measuring specific components as they are powered on and off to assess their potential effect on airborne data. The UAV is then flown, and a modified compensation routine is applied. These modifications include utilizing onboard autopilot current sensors as additional terms in the compensation algorithm. This process has been applied with success to fixed-wing and rotary-wing platforms, with both a standard manned-aircraft magnetometer, as well as a new atomic magnetometer, much smaller in scale.

Looking Inward to the Use of Unmanned Aerial Vehicle (UAV) for Rice Production Assessment in Indonesia

NASA Astrophysics Data System (ADS)

Komaladara, A. A. S. P.; Ambarawati, I. G. A. A.; Wijaya, I. M. A. S.; Hongo, C.; Mirah Adi, A. A. A.

2015-12-01

Rice is the main source of carbohydrate for most Indonesians. Rice production has been very dynamic due to improved infrastructure, research and development, and better farm management. However, rice production is susceptible to loss caused by drought, pest and disease attack and climate change. With the growing concern on sustainable and self-reliance food production in the country, there is an urgency to encourage research and efforts to increase rice productivity. Attempts to provide spatial distribution of rice fields on high resolution optical remote sensing data have been employed to some extent, however this technology could be costly. The use of UAV has been introduced to estimate damage ratio in rice crop recently in Indonesia. This technology is one of the ways to estimate rice production quicker, cost-saving and before harvesting time. This study aims to analyze spatio temporal and damage ratio of rice crop using UAV in Indonesia. The study empirically presents the use of UAV (Phantom 2 Vision +) on rice fields to the soil condition and development of management zone map in Bali as an example. The study concludes that the use of UAV allows researchers to pin point characteristics of crop and land in a specific area of a farm. This will then allow researchers to assist farmers in implementing specific and appropriate solutions to production issues. Key words: UAV, rice production, damage ratio

Research for new UAV capabilities

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

Canavan, G.H.; Leadabrand, R.

1996-07-01

This paper discusses research for new Unmanned Aerial Vehicles (UAV) capabilities. Findings indicate that UAV performance could be greatly enhanced by modest research. Improved sensors and communications enhance near term cost effectiveness. Improved engines, platforms, and stealth improve long term effectiveness.

Video change detection for fixed wing UAVs

NASA Astrophysics Data System (ADS)

Bartelsen, Jan; Müller, Thomas; Ring, Jochen; Mück, Klaus; Brüstle, Stefan; Erdnüß, Bastian; Lutz, Bastian; Herbst, Theresa

2017-10-01

In this paper we proceed the work of Bartelsen et al.1 We present the draft of a process chain for an image based change detection which is designed for videos acquired by fixed wing unmanned aerial vehicles (UAVs). From our point of view, automatic video change detection for aerial images can be useful to recognize functional activities which are typically caused by the deployment of improvised explosive devices (IEDs), e.g. excavations, skid marks, footprints, left-behind tooling equipment, and marker stones. Furthermore, in case of natural disasters, like flooding, imminent danger can be recognized quickly. Due to the necessary flight range, we concentrate on fixed wing UAVs. Automatic change detection can be reduced to a comparatively simple photogrammetric problem when the perspective change between the "before" and "after" image sets is kept as small as possible. Therefore, the aerial image acquisition demands a mission planning with a clear purpose including flight path and sensor configuration. While the latter can be enabled simply by a fixed and meaningful adjustment of the camera, ensuring a small perspective change for "before" and "after" videos acquired by fixed wing UAVs is a challenging problem. Concerning this matter, we have performed tests with an advanced commercial off the shelf (COTS) system which comprises a differential GPS and autopilot system estimating the repetition accuracy of its trajectory. Although several similar approaches have been presented,23 as far as we are able to judge, the limits for this important issue are not estimated so far. Furthermore, we design a process chain to enable the practical utilization of video change detection. It consists of a front-end of a database to handle large amounts of video data, an image processing and change detection implementation, and the visualization of the results. We apply our process chain on the real video data acquired by the advanced COTS fixed wing UAV and synthetic data. For the

Optical and acoustical UAV detection

NASA Astrophysics Data System (ADS)

Christnacher, Frank; Hengy, Sébastien; Laurenzis, Martin; Matwyschuk, Alexis; Naz, Pierre; Schertzer, Stéphane; Schmitt, Gwenael

2016-10-01

Recent world events have highlighted that the proliferation of UAVs is bringing with it a new and rapidly increasing threat for national defense and security agencies. Whilst many of the reported UAV incidents seem to indicate that there was no terrorist intent behind them, it is not unreasonable to assume that it may not be long before UAV platforms are regularly employed by terrorists or other criminal organizations. The flight characteristics of many of these mini- and micro-platforms present challenges for current systems which have been optimized over time to defend against the traditional air-breathing airborne platforms. A lot of programs to identify cost-effective measures for the detection, classification, tracking and neutralization have begun in the recent past. In this paper, lSL shows how the performance of a UAV detection and tracking concept based on acousto-optical technology can be powerfully increased through active imaging.

Technology Challenges in Small UAV Development

NASA Technical Reports Server (NTRS)

Logan, Michael J.; Vranas, Thomas L.; Motter, Mark; Shams, Qamar; Pollock, Dion S.

2005-01-01

Development of highly capable small UAVs present unique challenges for technology protagonists. Size constraints, the desire for ultra low cost and/or disposable platforms, lack of capable design and analysis tools, and unique mission requirements all add to the level of difficulty in creating state-of-the-art small UAVs. This paper presents the results of several small UAV developments, the difficulties encountered, and proposes a list of technology shortfalls that need to be addressed.

Uav Photgrammetric Workflows: a best Practice Guideline

NASA Astrophysics Data System (ADS)

Federman, A.; Santana Quintero, M.; Kretz, S.; Gregg, J.; Lengies, M.; Ouimet, C.; Laliberte, J.

2017-08-01

The increasing commercialization of unmanned aerial vehicles (UAVs) has opened the possibility of performing low-cost aerial image acquisition for the documentation of cultural heritage sites through UAV photogrammetry. The flying of UAVs in Canada is regulated through Transport Canada and requires a Special Flight Operations Certificate (SFOC) in order to fly. Various image acquisition techniques have been explored in this review, as well as well software used to register the data. A general workflow procedure has been formulated based off of the literature reviewed. A case study example of using UAV photogrammetry at Prince of Wales Fort is discussed, specifically in relation to the data acquisition and processing. Some gaps in the literature reviewed highlight the need for streamlining the SFOC application process, and incorporating UAVs into cultural heritage documentation courses.

Improved TDEM formation using fused ladar/digital imagery from a low-cost small UAV

NASA Astrophysics Data System (ADS)

Khatiwada, Bikalpa; Budge, Scott E.

2017-05-01

Formation of a Textured Digital Elevation Model (TDEM) has been useful in many applications in the fields of agriculture, disaster response, terrain analysis and more. Use of a low-cost small UAV system with a texel camera (fused lidar/digital imagery) can significantly reduce the cost compared to conventional aircraft-based methods. This paper reports continued work on this problem reported in a previous paper by Bybee and Budge, and reports improvements in performance. A UAV fitted with a texel camera is flown at a fixed height above the terrain and swaths of texel image data of the terrain below is taken continuously. Each texel swath has one or more lines of lidar data surrounded by a narrow strip of EO data. Texel swaths are taken such that there is some overlap from one swath to its adjacent swath. The GPS/IMU fitted on the camera also give coarse knowledge of attitude and position. Using this coarse knowledge and the information from the texel image, the error in the camera position and attitude is reduced which helps in producing an accurate TDEM. This paper reports improvements in the original work by using multiple lines of lidar data per swath. The final results are shown and analyzed for numerical accuracy.

Orbit/attitude estimation with LANDSAT Landmark data

NASA Technical Reports Server (NTRS)

Hall, D. L.; Waligora, S.

1979-01-01

The use of LANDSAT landmark data for orbit/attitude and camera bias estimation was studied. The preliminary results of these investigations are presented. The Goddard Trajectory Determination System (GTDS) error analysis capability was used to perform error analysis studies. A number of questions were addressed including parameter observability and sensitivity, effects on the solve-for parameter errors of data span, density, and distribution an a priori covariance weighting. The use of the GTDS differential correction capability with acutal landmark data was examined. The rms line and element observation residuals were studied as a function of the solve-for parameter set, a priori covariance weighting, force model, attitude model and data characteristics. Sample results are presented. Finally, verfication and preliminary system evaluation of the LANDSAT NAVPAK system for sequential (extended Kalman Filter) estimation of orbit, and camera bias parameters is given.

Nonlinear Landing Control for Quadrotor UAVs

NASA Astrophysics Data System (ADS)

Voos, Holger

Quadrotor UAVs are one of the most preferred type of small unmanned aerial vehicles because of the very simple mechanical construction and propulsion principle. However, the nonlinear dynamic behavior requires a more advanced stabilizing control and guidance of these vehicles. In addition, the small payload reduces the amount of batteries that can be carried and thus also limits the operating range of the UAV. One possible solution for a range extension is the application of a mobile base station for recharging purpose even during operation. However, landing on a moving base station requires autonomous tracking and landing control of the UAV. In this paper, a nonlinear autopilot for quadrotor UAVs is extended with a tracking and landing controller to fulfill the required task.

UAV Trajectory Modeling Using Neural Networks

NASA Technical Reports Server (NTRS)

Xue, Min

2017-01-01

Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural

An UAV scheduling and planning method for post-disaster survey

NASA Astrophysics Data System (ADS)

Li, G. Q.; Zhou, X. G.; Yin, J.; Xiao, Q. Y.

2014-11-01

Annually, the extreme climate and special geological environments lead to frequent natural disasters, e.g., earthquakes, floods, etc. The disasters often bring serious casualties and enormous economic losses. Post-disaster surveying is very important for disaster relief and assessment. As the Unmanned Aerial Vehicle (UAV) remote sensing with the advantage of high efficiency, high precision, high flexibility, and low cost, it is widely used in emergency surveying in recent years. As the UAVs used in emergency surveying cannot stop and wait for the happening of the disaster, when the disaster happens the UAVs usually are working at everywhere. In order to improve the emergency surveying efficiency, it is needed to track the UAVs and assign the emergency surveying task for each selected UAV. Therefore, a UAV tracking and scheduling method for post-disaster survey is presented in this paper. In this method, Global Positioning System (GPS), and GSM network are used to track the UAVs; an emergency tracking UAV information database is built in advance by registration, the database at least includes the following information, e.g., the ID of the UAVs, the communication number of the UAVs; when catastrophe happens, the real time location of all UAVs in the database will be gotten using emergency tracking method at first, then the traffic cost time for all UAVs to the disaster region will be calculated based on the UAVs' the real time location and the road network using the nearest services analysis algorithm; the disaster region is subdivided to several emergency surveying regions based on DEM, area, and the population distribution map; the emergency surveying regions are assigned to the appropriated UAV according to shortest cost time rule. The UAVs tracking and scheduling prototype is implemented using SQLServer2008, ArcEnginge 10.1 SDK, Visual Studio 2010 C#, Android, SMS Modem, and Google Maps API.

Estimation of Attitude and External Acceleration Using Inertial Sensor Measurement During Various Dynamic Conditions

PubMed Central

Lee, Jung Keun; Park, Edward J.; Robinovitch, Stephen N.

2012-01-01

This paper proposes a Kalman filter-based attitude (i.e., roll and pitch) estimation algorithm using an inertial sensor composed of a triaxial accelerometer and a triaxial gyroscope. In particular, the proposed algorithm has been developed for accurate attitude estimation during dynamic conditions, in which external acceleration is present. Although external acceleration is the main source of the attitude estimation error and despite the need for its accurate estimation in many applications, this problem that can be critical for the attitude estimation has not been addressed explicitly in the literature. Accordingly, this paper addresses the combined estimation problem of the attitude and external acceleration. Experimental tests were conducted to verify the performance of the proposed algorithm in various dynamic condition settings and to provide further insight into the variations in the estimation accuracy. Furthermore, two different approaches for dealing with the estimation problem during dynamic conditions were compared, i.e., threshold-based switching approach versus acceleration model-based approach. Based on an external acceleration model, the proposed algorithm was capable of estimating accurate attitudes and external accelerations for short accelerated periods, showing its high effectiveness during short-term fast dynamic conditions. Contrariwise, when the testing condition involved prolonged high external accelerations, the proposed algorithm exhibited gradually increasing errors. However, as soon as the condition returned to static or quasi-static conditions, the algorithm was able to stabilize the estimation error, regaining its high estimation accuracy. PMID:22977288

Volcanic Plume Measurements with UAV (Invited)

NASA Astrophysics Data System (ADS)

Shinohara, H.; Kaneko, T.; Ohminato, T.

2013-12-01

volcano operated by ERI, Tokyo University. In all cases, we could estimated volcanic gas compositions, such as CO2/SO2 ratios, but also found out that it is necessary to improve the techniques to avoid the contamination of the exhaust gases and to approach more concentrated part of the plume. It was also revealed that the aerial measurements have an advantage of the stable background. The error of the volcanic gas composition estimates are largely due to the large fluctuation of the atmospheric H2O and CO2 concentrations near the ground. The stable atmospheric background obtained by the UAV measurements enables accurate estimate of the volcanic gas compositions. One of the most successful measurements was that on May 18, 2011 at Shinomoedake, Kirishima volcano during repeating Vulcanian eruption stage. The major component composition was obtained as H2O=97, CO2=1.5, SO2=0.2, H2S=0.24, H2=0.006 mol%; the high CO2 contents suggests relatively deep source of the magma degassing and the apparent equilibrium temperature obtained as 400°C indicates that the gas was cooled during ascent to the surface. The volcanic plume measurement with UAV will become an important tool for the volcano monitoring that provides important information to understand eruption processes.

Air Force UAVs: The Secret History

DTIC Science & Technology

2010-07-01

iA Mitchell Institute Study i Air Force UAVs The Secret History A Mitchell Institute Study July 2010 By Thomas P. Ehrhard Report Documentation Page...DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Air Force UAVs The Secret History 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c...opening phases of Operation Enduring Freedom in Afghanistan. By Thomas P. Ehrhard a miTchEll insTiTuTE sTudy July 2010 Air Force UAVs The Secret History

Uav-Based 3d Urban Environment Monitoring

NASA Astrophysics Data System (ADS)

Boonpook, Wuttichai; Tan, Yumin; Liu, Huaqing; Zhao, Binbin; He, Lingfeng

2018-04-01

Unmanned Aerial Vehicle (UAV) based remote sensing can be used to make three-dimensions (3D) mapping with great flexibility, besides the ability to provide high resolution images. In this paper we propose a quick-change detection method on UAV images by combining altitude from Digital Surface Model (DSM) and texture analysis from images. Cases of UAV images with and without georeferencing are both considered. Research results show that the accuracy of change detection can be enhanced with georeferencing procedure, and the accuracy and precision of change detection on UAV images which are collected both vertically and obliquely but without georeferencing also have a good performance.

Air Force UAV’s: The Secret History

DTIC Science & Technology

2010-07-01

iA Mitchell Institute Study i Air Force UAVs The Secret History A Mitchell Institute Study July 2010 By Thomas P. Ehrhard Report Documentation Page...DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Air Force UAVs The Secret History 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c... The Secret History 2 Air Force UAVs: The Secret History2 air Force uaVs: The secret history Has any airplane in the past decade captured the public

Efficient algorithms for single-axis attitude estimation

NASA Technical Reports Server (NTRS)

Shuster, M. D.

1981-01-01

The computationally efficient algorithms determine attitude from the measurement of art lengths and dihedral angles. The dependence of these algorithms on the solution of trigonometric equations was reduced. Both single time and batch estimators are presented along with the covariance analysis of each algorithm.

Robust drone detection for day/night counter-UAV with static VIS and SWIR cameras

NASA Astrophysics Data System (ADS)

Müller, Thomas

2017-05-01

Recent progress in the development of unmanned aerial vehicles (UAVs) has led to more and more situations in which drones like quadrocopters or octocopters pose a potential serious thread or could be used as a powerful tool for illegal activities. Therefore, counter-UAV systems are required in a lot of applications to detect approaching drones as early as possible. In this paper, an efficient and robust algorithm is presented for UAV detection using static VIS and SWIR cameras. Whereas VIS cameras with a high resolution enable to detect UAVs in the daytime in further distances, surveillance at night can be performed with a SWIR camera. First, a background estimation and structural adaptive change detection process detects movements and other changes in the observed scene. Afterwards, the local density of changes is computed used for background density learning and to build up the foreground model which are compared in order to finally get the UAV alarm result. The density model is used to filter out noise effects, on the one hand. On the other hand, moving scene parts like moving leaves in the wind or driving cars on a street can easily be learned in order to mask such areas out and suppress false alarms there. This scene learning is done automatically simply by processing without UAVs in order to capture the normal situation. The given results document the performance of the presented approach in VIS and SWIR in different situations.

Detection, Location and Grasping Objects Using a Stereo Sensor on UAV in Outdoor Environments.

PubMed

Ramon Soria, Pablo; Arrue, Begoña C; Ollero, Anibal

2017-01-07

The article presents a vision system for the autonomous grasping of objects with Unmanned Aerial Vehicles (UAVs) in real time. Giving UAVs the capability to manipulate objects vastly extends their applications, as they are capable of accessing places that are difficult to reach or even unreachable for human beings. This work is focused on the grasping of known objects based on feature models. The system runs in an on-board computer on a UAV equipped with a stereo camera and a robotic arm. The algorithm learns a feature-based model in an offline stage, then it is used online for detection of the targeted object and estimation of its position. This feature-based model was proved to be robust to both occlusions and the presence of outliers. The use of stereo cameras improves the learning stage, providing 3D information and helping to filter features in the online stage. An experimental system was derived using a rotary-wing UAV and a small manipulator for final proof of concept. The robotic arm is designed with three degrees of freedom and is lightweight due to payload limitations of the UAV. The system has been validated with different objects, both indoors and outdoors.

Detection, Location and Grasping Objects Using a Stereo Sensor on UAV in Outdoor Environments

PubMed Central

Ramon Soria, Pablo; Arrue, Begoña C.; Ollero, Anibal

2017-01-01

The article presents a vision system for the autonomous grasping of objects with Unmanned Aerial Vehicles (UAVs) in real time. Giving UAVs the capability to manipulate objects vastly extends their applications, as they are capable of accessing places that are difficult to reach or even unreachable for human beings. This work is focused on the grasping of known objects based on feature models. The system runs in an on-board computer on a UAV equipped with a stereo camera and a robotic arm. The algorithm learns a feature-based model in an offline stage, then it is used online for detection of the targeted object and estimation of its position. This feature-based model was proved to be robust to both occlusions and the presence of outliers. The use of stereo cameras improves the learning stage, providing 3D information and helping to filter features in the online stage. An experimental system was derived using a rotary-wing UAV and a small manipulator for final proof of concept. The robotic arm is designed with three degrees of freedom and is lightweight due to payload limitations of the UAV. The system has been validated with different objects, both indoors and outdoors. PMID:28067851

Uav Positioning and Collision Avoidance Based on RSS Measurements

NASA Astrophysics Data System (ADS)

Masiero, A.; Fissore, F.; Guarnieri, A.; Pirotti, F.; Vettore, A.

2015-08-01

In recent years, Unmanned Aerial Vehicles (UAVs) are attracting more and more attention in both the research and industrial communities: indeed, the possibility to use them in a wide range of remote sensing applications makes them a very flexible and attractive solution in both civil and commercial cases (e.g. precision agriculture, security and control, monitoring of sites, exploration of areas difficult to reach). Most of the existing UAV positioning systems rely on the use of the GPS signal. Despite this can be a satisfactory solution in open environments where the GPS signal is available, there are several operating conditions of interest where it is unavailable or unreliable (e.g. close to high buildings, or mountains, in indoor environments). Consequently, a different approach has to be adopted in these cases. This paper considers the use ofWiFi measurements in order to obtain position estimations of the device of interest. More specifically, to limit the costs for the devices involved in the positioning operations, an approach based on radio signal strengths (RSS) measurements is considered. Thanks to the use of a Kalman filter, the proposed approach takes advantage of the temporal dynamic of the device of interest in order to improve the positioning results initially provided by means of maximum likelihood estimations. The considered UAVs are assumed to be provided with communication devices, which can allow them to communicate with each other in order to improve their cooperation abilities. In particular, the collision avoidance problem is examined in this work.

Space Technology 5 Post-Launch Ground Attitude Estimation Experience

NASA Technical Reports Server (NTRS)

Harman, Richard R.

2007-01-01

The Space Technology (ST)-5 satellites were launched March 22, 2006 on a Pegasus XL launch vehicle into a Sun-synchronous orbit. The three micro-satellites which constituted the ST-5 mission were kept in a formation which allowed three successive measurements taken of the Earth s magnetic field in order to study short term fluctuations of the field. The attitude of each satellite was computed on the ground using data from the science grade magnetometer as well as the miniature spinning Sun sensor (MSSS) which was the primary attitude sensor. Attitude and orbit maneuvers were performed using a single axial cold gas thruster. This paper describes the ground attitude estimation process and performance as well as anomaly resolutions.

Designing and Testing a UAV Mapping System for Agricultural Field Surveying

PubMed Central

Skovsen, Søren

2017-01-01

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35–0.58 m are correlated to the applied nitrogen treatments of 0–300 kgNha. The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations. PMID:29168783

Designing and Testing a UAV Mapping System for Agricultural Field Surveying.

PubMed

Christiansen, Martin Peter; Laursen, Morten Stigaard; Jørgensen, Rasmus Nyholm; Skovsen, Søren; Gislum, René

2017-11-23

A Light Detection and Ranging (LiDAR) sensor mounted on an Unmanned Aerial Vehicle (UAV) can map the overflown environment in point clouds. Mapped canopy heights allow for the estimation of crop biomass in agriculture. The work presented in this paper contributes to sensory UAV setup design for mapping and textual analysis of agricultural fields. LiDAR data are combined with data from Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) sensors to conduct environment mapping for point clouds. The proposed method facilitates LiDAR recordings in an experimental winter wheat field. Crop height estimates ranging from 0.35-0.58 m are correlated to the applied nitrogen treatments of 0-300 kg N ha . The LiDAR point clouds are recorded, mapped, and analysed using the functionalities of the Robot Operating System (ROS) and the Point Cloud Library (PCL). Crop volume estimation is based on a voxel grid with a spatial resolution of 0.04 × 0.04 × 0.001 m. Two different flight patterns are evaluated at an altitude of 6 m to determine the impacts of the mapped LiDAR measurements on crop volume estimations.

Attitude Estimation for Large Field-of-View Sensors

NASA Technical Reports Server (NTRS)

Cheng, Yang; Crassidis, John L.; Markley, F. Landis

2005-01-01

The QUEST measurement noise model for unit vector observations has been widely used in spacecraft attitude estimation for more than twenty years. It was derived under the approximation that the noise lies in the tangent plane of the respective unit vector and is axially symmetrically distributed about the vector. For large field-of-view sensors, however, this approximation may be poor, especially when the measurement falls near the edge of the field of view. In this paper a new measurement noise model is derived based on a realistic noise distribution in the focal-plane of a large field-of-view sensor, which shows significant differences from the QUEST model for unit vector observations far away from the sensor boresight. An extended Kalman filter for attitude estimation is then designed with the new measurement noise model. Simulation results show that with the new measurement model the extended Kalman filter achieves better estimation performance using large field-of-view sensor observations.

Unmanned aerial vehicles (UAVs) in pest management: Progress in the development of a UAV-deployed mating disruption system for Wisconsin cranberries

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAVs) represent a powerful new tool for agriculture. Currently, UAVs are used almost exclusively as crop reconnaissance devices (“eyes in the sky”), not as pest control delivery systems. Research in Wisconsin cranberries is taking UAVs in a new direction. The Steffan and Lu...

Unmanned aerial vehicles (UAVs) in pest management: Progress in the development of a UAV-deployed mating disruption system for Wisconsin cranberries

USDA-ARS?s Scientific Manuscript database

Unmanned aerial vehicles (UAVs) hold significant promise for agriculture. Currently, UAVs are being employed for various reconnaissance purposes (“eyes in the sky”), but not as pest control delivery systems. Research in Wisconsin cranberries is taking UAVs in a new direction. The Steffan and Luck La...

Chosen Aspects of the Production of the Basic Map Using Uav Imagery

NASA Astrophysics Data System (ADS)

Kedzierski, M.; Fryskowska, A.; Wierzbicki, D.; Nerc, P.

2016-06-01

For several years there has been an increasing interest in the use of unmanned aerial vehicles in acquiring image data from a low altitude. Considering the cost-effectiveness of the flight time of UAVs vs. conventional airplanes, the use of the former is advantageous when generating large scale accurate ortophotos. Through the development of UAV imagery, we can update large-scale basic maps. These maps are cartographic products which are used for registration, economic, and strategic planning. On the basis of these maps other cartographic maps are produced, for example maps used building planning. The article presents an assessesment of the usefulness of orthophotos based on UAV imagery to upgrade the basic map. In the research a compact, non-metric camera, mounted on a fixed wing powered by an electric motor was used. The tested area covered flat, agricultural and woodland terrains. The processing and analysis of orthorectification were carried out with the INPHO UASMaster programme. Due to the effect of UAV instability on low-altitude imagery, the use of non-metric digital cameras and the low-accuracy GPS-INS sensors, the geometry of images is visibly lower were compared to conventional digital aerial photos (large values of phi and kappa angles). Therefore, typically, low-altitude images require large along- and across-track direction overlap - usually above 70 %. As a result of the research orthoimages were obtained with a resolution of 0.06 meters and a horizontal accuracy of 0.10m. Digitized basic maps were used as the reference data. The accuracy of orthoimages vs. basic maps was estimated based on the study and on the available reference sources. As a result, it was found that the geometric accuracy and interpretative advantages of the final orthoimages allow the updating of basic maps. It is estimated that such an update of basic maps based on UAV imagery reduces processing time by approx. 40%.

State-Of in Uav Remote Sensing Survey - First Insights Into Applications of Uav Sensing Systems

NASA Astrophysics Data System (ADS)

Aasen, H.

2017-08-01

UAVs are increasingly adapted as remote sensing platforms. Together with specialized sensors, they become powerful sensing systems for environmental monitoring and surveying. Spectral data has great capabilities to the gather information about biophysical and biochemical properties. Still, capturing meaningful spectral data in a reproducible way is not trivial. Since a couple of years small and lightweight spectral sensors, which can be carried on small flexible platforms, have become available. With their adaption in the community, the responsibility to ensure the quality of the data is increasingly shifted from specialized companies and agencies to individual researchers or research teams. Due to the complexity of the data acquisition of spectral data, this poses a challenge for the community and standardized protocols, metadata and best practice procedures are needed to make data intercomparable. In November 2016, the ESSEM COST action Innovative optical Tools for proximal sensing of ecophysiological processes (OPTIMISE; http://optimise.dcs.aber.ac.uk/) held a workshop on best practices for UAV spectral sampling. The objective of this meeting was to trace the way from particle to pixel and identify influences on the data quality / reliability, to figure out how well we are currently doing with spectral sampling from UAVs and how we can improve. Additionally, a survey was designed to be distributed within the community to get an overview over the current practices and raise awareness for the topic. This talk will introduce the approach of the OPTIMISE community towards best practises in UAV spectral sampling and present first results of the survey (uav-survey/"target="_blank">http://optimise.dcs.aber.ac.uk/uav-survey/). This contribution briefly introduces the survey and gives some insights into the first results given by the interviewees.

Exploratory use of a UAV platform for variety selection in peanut

NASA Astrophysics Data System (ADS)

Balota, Maria; Oakes, Joseph

2016-05-01

Variety choice is the most important production decision farmers make because high yielding varieties can increase profit with no additional production costs. Therefore, yield improvement has been the major objective for peanut (Arachis hypogaea L.) breeding programs worldwide, but the current breeding approach (selecting for yield under optimal production conditions) is slow and inconsistent with the needs derived from population demand and climate change. To improve the rate of genetic gain, breeders have used target physiological traits such as leaf chlorophyll content using SPAD chlorophyll meter, Normalized Difference Vegetation Index (NDVI) from canopy reflectance in visible and near infra-red (NIR) wavelength bands, and canopy temperature (CT) manually measured with infra-red (IR) thermometers at the canopy level; but its use for routine selection was hampered by the time required to walk hundreds of plots. Recent developments in remote sensing-based high throughput phenotyping platforms using unmanned aerial vehicles (UAV) have shown good potential for future breeding advancements. Recently, we initiated a study for the evaluation of suitability of digital imagery, NDVI, and CT taken from an UAV platform for peanut variety differentiation. Peanut is unique for setting its yield underground and resilience to drought and heat, for which yield is difficult to pre-harvest estimate; although the need for early yield estimation within the breeding programs exists. Twenty-six peanut cultivars and breeding lines were grown in replicated plots either optimally or deficiently irrigated under rain exclusion shelters at Suffolk, Virginia. At the beginning maturity growth stage, approximately a month before digging, NDVI and CT were taken with ground-based sensors at the same time with red, blue, green (RGB) images from a Sony camera mounted on an UAV platform. Disease ratings were also taken pre-harvest. Ground and UAV derived vegetation indices were analyzed for

Analysis of the Command and Control Segment (CCS) attitude estimation algorithm

NASA Technical Reports Server (NTRS)

Stockwell, Catherine

1993-01-01

This paper categorizes the qualitative behavior of the Command and Control Segment (CCS) differential correction algorithm as applied to attitude estimation using simultaneous spin axis sun angle and Earth cord length measurements. The categories of interest are the domains of convergence, divergence, and their boundaries. Three series of plots are discussed that show the dependence of the estimation algorithm on the vehicle radius, the sun/Earth angle, and the spacecraft attitude. Common qualitative dynamics to all three series are tabulated and discussed. Out-of-limits conditions for the estimation algorithm are identified and discussed.

A Novel System for Correction of Relative Angular Displacement between Airborne Platform and UAV in Target Localization

PubMed Central

Liu, Chenglong; Liu, Jinghong; Song, Yueming; Liang, Huaidan

2017-01-01

This paper provides a system and method for correction of relative angular displacements between an Unmanned Aerial Vehicle (UAV) and its onboard strap-down photoelectric platform to improve localization accuracy. Because the angular displacements have an influence on the final accuracy, by attaching a measuring system to the platform, the texture image of platform base bulkhead can be collected in a real-time manner. Through the image registration, the displacement vector of the platform relative to its bulkhead can be calculated to further determine angular displacements. After being decomposed and superposed on the three attitude angles of the UAV, the angular displacements can reduce the coordinate transformation errors and thus improve the localization accuracy. Even a simple kind of method can improve the localization accuracy by 14.3%. PMID:28273845

A Novel System for Correction of Relative Angular Displacement between Airborne Platform and UAV in Target Localization.

PubMed

Liu, Chenglong; Liu, Jinghong; Song, Yueming; Liang, Huaidan

2017-03-04

This paper provides a system and method for correction of relative angular displacements between an Unmanned Aerial Vehicle (UAV) and its onboard strap-down photoelectric platform to improve localization accuracy. Because the angular displacements have an influence on the final accuracy, by attaching a measuring system to the platform, the texture image of platform base bulkhead can be collected in a real-time manner. Through the image registration, the displacement vector of the platform relative to its bulkhead can be calculated to further determine angular displacements. After being decomposed and superposed on the three attitude angles of the UAV, the angular displacements can reduce the coordinate transformation errors and thus improve the localization accuracy. Even a simple kind of method can improve the localization accuracy by 14.3%.

Vector Observation-Aided/Attitude-Rate Estimation Using Global Positioning System Signals

NASA Technical Reports Server (NTRS)

Oshman, Yaakov; Markley, F. Landis

1997-01-01

A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.

Moving object detection using dynamic motion modelling from UAV aerial images.

PubMed

Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

2014-01-01

Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

Colored noise effects on batch attitude accuracy estimates

NASA Technical Reports Server (NTRS)

Bilanow, Stephen

1991-01-01

The effects of colored noise on the accuracy of batch least squares parameter estimates with applications to attitude determination cases are investigated. The standard approaches used for estimating the accuracy of a computed attitude commonly assume uncorrelated (white) measurement noise, while in actual flight experience measurement noise often contains significant time correlations and thus is colored. For example, horizon scanner measurements from low Earth orbit were observed to show correlations over many minutes in response to large scale atmospheric phenomena. A general approach to the analysis of the effects of colored noise is investigated, and interpretation of the resulting equations provides insight into the effects of any particular noise color and the worst case noise coloring for any particular parameter estimate. It is shown that for certain cases, the effects of relatively short term correlations can be accommodated by a simple correction factor. The errors in the predicted accuracy assuming white noise and the reduced accuracy due to the suboptimal nature of estimators that do not take into account the noise color characteristics are discussed. The appearance of a variety of sample noise color characteristics are demonstrated through simulation, and their effects are discussed for sample estimation cases. Based on the analysis, options for dealing with the effects of colored noise are discussed.

Commercial UAV operations in civil airspace

NASA Astrophysics Data System (ADS)

Newcome, Laurence R.

2000-11-01

The Federal Aviation Administration is often portrayed as the major impediment to unmanned aerial vehicle expansion into civil government and commercial markets. This paper describes one company's record for successfully negotiating the FAA regulations and obtaining authorizations for several types of UAVs to fly commercial reconnaissance missions in civil airspace. The process and criteria for obtaining such authorizations are described. The mishap records of the Pioneer, Predator and Hunter UAVs are examined in regard to their impact on FAA rule making. The paper concludes with a discussion of the true impediments to UAV penetration of commercial markets to date.

UAV-based remote sensing of the Heumoes landslide, Austria Vorarlberg

NASA Astrophysics Data System (ADS)

Niethammer, U.; Joswig, M.

2009-04-01

The Heumoes landslide, is located in the eastern Vorarlberg Alps, Austria, 10 km southeast of Dornbirn. The extension of the landslide is about 2000 m in west to east direction and about 500 m at its widest extent in north to south direction. It occurs between an elevation of 940 m in the east and 1360 m in the west, slope angles of more than 60 % can be observed as well as almost flat areas. Its total volume is estimated to be 9.400.000 cubic meters and its average velocities amount to some centimeter per year. Surface signatures or 'photolineations' of creeping landslides, e.g. fractures and rupture lines in sediments and street pavings, and vegetation contrasts by changes of water table in shallow vegetation in principle can be resolved by remote sensing. The necessary ground cell resolution of few centimeters, however, generally can't be achieved by routine areal or satellite imagery. The fast technological progress of unmanned areal vehicles (UAV) and the reduced payload by miniaturized optical cameras now allow for UAV remote sensing applications that are below the high financial limits of military intelligence. Even with 'low-cost' equipment, the necessary centimeter-scale ground cell resolution can be achieved by adapting the flight altitude to some ten to one hundred meters. Operated by scientists experienced in remote-control flight models, UAV remote sensing can now be performed routinely, and campaign-wise after any significant event of, e.g., heavy rainfall, or partial mudflow. We have investigated a concept of UAV-borne remote sensing based on motorized gliders, and four-propeller helicopters or 'quad-rotors'. Several missions were flown over the Heumoes landslide. Between 2006 and 2008 three series UAV-borne photographs of the Heumoes landslide were taken and could be combined to orto-mosaics of the slope area within few centimeters ground cell resolution. We will present the concept of our low cost quad-rotor UAV system and first results of the

Earth Observations and the Role of UAVs: A Capabilities Assessment. Version 1.1

NASA Technical Reports Server (NTRS)

Cox, Timothy H.; Somers, Ivan; Fratello, David J.

2006-01-01

This document provides an assessment of the civil UAV missions and technologies and is intended to parallel the Office of the Secretary of Defense UAV Roadmap. The intent of this document is four-fold: 1. Determine and document desired future missions of Earth observation UAVs based on user-defined needs 2. Determine and document the technologies necessary to support those missions 3. Discuss the present state of the platform capabilities and required technologies, identifying those in progress, those planned, and those for which no current plans exist 4. Provide the foundations for development of a comprehensive civil UAV roadmap to complement the Department of Defense (DoD) effort (http://www.acq.osd.mil/uas/). Two aspects of the President's Management Agenda (refer to the document located at: www.whitehouse.gov/omb/budget/fy2002/mgmt.pdf ) are supported by this undertaking. First, it is one that will engage multiple Agencies in the effort as stakeholders and benefactors of the systems. In that sense, the market will be driven by the user requirements and applications. The second aspect is one of supporting economic development in the commercial sector. Market forecasts for the civil use of UAVs have indicated an infant market stage at present with a sustained forecasted growth. There is some difficulty in quantifying the value of the market since the typical estimate excludes system components other than the aerial platforms. Section 2.4 addresses the civil UAV market forecast and lists several independent forecasts. One conclusion that can be drawn from these forecasts is that all show a sustained growth for the duration of each long-term forecast.

Pricise Target Geolocation and Tracking Based on Uav Video Imagery

NASA Astrophysics Data System (ADS)

Hosseinpoor, H. R.; Samadzadegan, F.; Dadrasjavan, F.

2016-06-01

There is an increasingly large number of applications for Unmanned Aerial Vehicles (UAVs) from monitoring, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using an extended Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors, Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process. The results of this study compared with code-based ordinary GPS, indicate that RTK observation with proposed method shows more than 10 times improvement of accuracy in target geolocation.

Leaf Area Index Estimation in Vineyards from Uav Hyperspectral Data, 2d Image Mosaics and 3d Canopy Surface Models

NASA Astrophysics Data System (ADS)

Kalisperakis, I.; Stentoumis, Ch.; Grammatikopoulos, L.; Karantzalos, K.

2015-08-01

The indirect estimation of leaf area index (LAI) in large spatial scales is crucial for several environmental and agricultural applications. To this end, in this paper, we compare and evaluate LAI estimation in vineyards from different UAV imaging datasets. In particular, canopy levels were estimated from i.e., (i) hyperspectral data, (ii) 2D RGB orthophotomosaics and (iii) 3D crop surface models. The computed canopy levels have been used to establish relationships with the measured LAI (ground truth) from several vines in Nemea, Greece. The overall evaluation indicated that the estimated canopy levels were correlated (r2 > 73%) with the in-situ, ground truth LAI measurements. As expected the lowest correlations were derived from the calculated greenness levels from the 2D RGB orthomosaics. The highest correlation rates were established with the hyperspectral canopy greenness and the 3D canopy surface models. For the later the accurate detection of canopy, soil and other materials in between the vine rows is required. All approaches tend to overestimate LAI in cases with sparse, weak, unhealthy plants and canopy.

A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations.

PubMed

Qin, Fangjun; Chang, Lubin; Jiang, Sai; Zha, Feng

2018-05-03

In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms.

A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations

PubMed Central

Qin, Fangjun; Jiang, Sai; Zha, Feng

2018-01-01

In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms. PMID:29751538

Pressurized Structure Technology for UAVS

DTIC Science & Technology

2008-12-01

deficiencies of the UAVs just listed is to employ lighter-than-air or pressurized structure-based ( PSB ) technology. Basically, the UAV will be built such...that a considerable percentage of its weight is supported by or constructed from inflatable structures containing air or helium. PSB technology...neutral buoyancy will allow much slower flight speeds and increased maneuverability while expending little power. PSB airframes used in conjunction

Lidar on small UAV for 3D mapping

NASA Astrophysics Data System (ADS)

Tulldahl, H. Michael; Larsson, Hâkan

2014-10-01

Small UAV:s (Unmanned Aerial Vehicles) are currently in an explosive technical development phase. The performance of UAV-system components such as inertial navigation sensors, propulsion, control processors and algorithms are gradually improving. Simultaneously, lidar technologies are continuously developing in terms of reliability, accuracy, as well as speed of data collection, storage and processing. The lidar development towards miniature systems with high data rates has, together with recent UAV development, a great potential for new three dimensional (3D) mapping capabilities. Compared to lidar mapping from manned full-size aircraft a small unmanned aircraft can be cost efficient over small areas and more flexible for deployment. An advantage with high resolution lidar compared to 3D mapping from passive (multi angle) photogrammetry is the ability to penetrate through vegetation and detect partially obscured targets. Another advantage is the ability to obtain 3D data over the whole survey area, without the limited performance of passive photogrammetry in low contrast areas. The purpose of our work is to demonstrate 3D lidar mapping capability from a small multirotor UAV. We present the first experimental results and the mechanical and electrical integration of the Velodyne HDL-32E lidar on a six-rotor aircraft with a total weight of 7 kg. The rotating lidar is mounted at an angle of 20 degrees from the horizontal plane giving a vertical field-of-view of 10-50 degrees below the horizon in the aircraft forward directions. For absolute positioning of the 3D data, accurate positioning and orientation of the lidar sensor is of high importance. We evaluate the lidar data position accuracy both based on inertial navigation system (INS) data, and on INS data combined with lidar data. The INS sensors consist of accelerometers, gyroscopes, GPS, magnetometers, and a pressure sensor for altimetry. The lidar range resolution and accuracy is documented as well as the

Using crowd sourcing to combat potentially illegal or dangerous UAV operations

NASA Astrophysics Data System (ADS)

Tapsall, Brooke T.

2016-10-01

The UAV (Unmanned Aerial Vehicles) industry is growing exponentially at a pace that policy makers, individual countries and law enforcement agencies are finding difficult to keep up. The UAV market is large, as such the amount of UAVs being operated in potentially dangerous situations is prevalent and rapidly increasing. Media is continually reporting `near-miss' incidents between UAVs and commercial aircraft, UAV breaching security in sensitive areas or invading public privacy. One major challenge for law enforcement agencies is gaining tangible evidence against potentially dangerous or illegal UAV operators due to the rapidity with which UAV operators are able to enter, fly and exit a scene before authorities can arrive or before they can be located. DroneALERT, an application available via the Airport-UAV.com website, allows users to capture potentially dangerous or illegal UAV activity using their mobile device as it the incident is occurring. A short online DroneALERT Incident Report (DIR) is produced, emailed to the user and the Airport-UAV.com custodians. The DIR can be used to aid authorities in their investigations. The DIR contains details such as images and videos, location, time, date of the incident, drone model, its distance and height. By analysing information from the DIR, photos or video, there is a high potential for law enforcement authorities to use this evidence to identify the type of UAV used, triangulate the location of the potential dangerous UAV and operator, create a timeline of events, potential areas of operator exit and to determine the legalities breached. All provides crucial evidence for identifying and prosecuting a UAV operator.

UAV based hydromorphological mapping of a river reach to improve hydrodynamic numerical models

NASA Astrophysics Data System (ADS)

Lükő, Gabriella; Baranya, Sándor; Rüther, Nils

2017-04-01

Unmanned Aerial Vehicles (UAVs) are increasingly used in the field of engineering surveys. In river engineering, or in general, water resources engineering, UAV based measurements have a huge potential. For instance, indirect measurements of the flow discharge using e.g. large-scale particle image velocimetry (LSPIV), particle tracking velocimetry (PTV), space-time image velocimetry (STIV) or radars became a real alternative for direct flow measurements. Besides flow detection, topographic surveys are also essential for river flow studies as the channel and floodplain geometry is the primary steering feature of the flow. UAVs can play an important role in this field, too. The widely used laser based topographic survey method (LIDAR) can be deployed on UAVs, moreover, the application of the Structure from Motion (SfM) method, which is based on images taken by UAVs, might be an even more cost-efficient alternative to reveal the geometry of distinct objects in the river or on the floodplain. The goal of this study is to demonstrate the utilization of photogrammetry and videogrammetry from airborne footage to provide geometry and flow data for a hydrodynamic numerical simulation of a 2 km long river reach in Albania. First, the geometry of the river is revealed from photogrammetry using the SfM method. Second, a more detailed view of the channel bed at low water level is taken. Using the fine resolution images, a Matlab based code, BASEGrain, developed by the ETH in Zürich, will be applied to determine the grain size characteristics of the river bed. This information will be essential to define the hydraulic roughness in the numerical model. Third, flow mapping is performed using UAV measurements and LSPIV method to quantitatively asses the flow field at the free surface and to estimate the discharge in the river. All data collection and analysis will be carried out using a simple, low-cost UAV, moreover, for all the data processing, open source, freely available

UAVs Being Used for Environmental Surveying

ScienceCinema

Chung, Sandra

2017-12-09

UAVs, are much more sophisticated than your typical remote-controlled plane. INL robotics and remote sensing experts have added state-of-the-art imaging and wireless technology to the UAVs to create intelligent remote surveillance craft that can rapidly survey a wide area for damage and track down security threats.

A Programmable SDN+NFV Architecture for UAV Telemetry Monitoring

NASA Technical Reports Server (NTRS)

White, Kyle J. S.; Pezaros, Dimitrios P.; Denney, Ewen; Knudson, Matt D.

2017-01-01

With the explosive growth in UAV numbers forecast worldwide, a core concern is how to manage the ad-hoc network configuration required for mobility management. As UAVs migrate among ground control stations, associated network services, routing and operational control must also rapidly migrate to ensure a seamless transition. In this paper, we present a novel, lightweight and modular architecture which supports high mobility, resilience and flexibility through the application of SDN and NFV principles on top of the UAV infrastructure. By combining SDN programmability and Network Function Virtualization we can achieve resilient infrastructure migration of network services, such as network monitoring and anomaly detection, coupled with migrating UAVs to enable high mobility management. Our container-based monitoring and anomaly detection Network Functions (NFs) can be tuned to specific UAV models providing operators better insight during live, high-mobility deployments. We evaluate our architecture against telemetry from over 80flights from a scientific research UAV infrastructure.

Rapid melting dynamics of the Morteratsch glacier (Swiss Alps) from UAV photogrammetry and field spectroscopy data

NASA Astrophysics Data System (ADS)

Di Mauro, Biagio; Garzonio, Roberto; Rossini, Micol; Baccolo, Giovanni; Julitta, Tommaso; Cavallini, Giuseppe; Mattavelli, Matteo; Colombo, Roberto

2017-04-01

The impact of atmospheric impurities on the optical properties of snow and ice has been largely acknowledged in the scientific literature. Beyond this, the evaluation of the effect of specific organic and inorganic particles on melting dynamics remains a major challenge. In this contribution, we examine the annual melting dynamics of a large valley glacier of the Swiss Alps using UAV photogrammetry. We then compare the melting patterns to the presence of surface impurities on the glacier surface. Two surveys (in July and September 2016) with a lightweight Unmanned Aerial Vehicle (UAV) were organized on the ablation zone of the Morteratsch glacier (Swiss Alps). The UAV (DJI, Phantom 4) was equipped with a high resolution digital camera, and flew at a constant altitude of 150 from the glacier surface. 30 ground control points were placed on the glacier, and their coordinates were determined with a differential GPS (dGPS) for georeferencing UAV images. Contemporary to the UAV surveys, field spectroscopy data were collected on the glacier surface with an Analytical Spectral Device (ASD Field spec.) spectrometer covering the visible and near infrared spectral ranges, and ice samples were collected to determine the abundance of microorganism and algae. From the UAV RGB data, two point clouds were created using Structure from Motion (SfM) algorithms. The point clouds (each consisting of about 15M points) were then converted in Digital Surface Models (DSM) and orthomosaics by interpolation. The difference between the two DSM was calculated and converted in Snow Water Equivalent (SWE), in order to assess the ice lost by the glacier during the ablation season. The point clouds were compared and the displacement vectors were estimated using different algorithms. The elevation changes estimated from UAV data were compared with the abundance of microorganisms and algae. The reflectance spectra of ice with microorganisms and algae show a chlorophyll absorption feature at 680 nm

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing.

PubMed

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-07-17

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system.

Formation Flight of Multiple UAVs via Onboard Sensor Information Sharing

PubMed Central

Park, Chulwoo; Cho, Namhoon; Lee, Kyunghyun; Kim, Youdan

2015-01-01

To monitor large areas or simultaneously measure multiple points, multiple unmanned aerial vehicles (UAVs) must be flown in formation. To perform such flights, sensor information generated by each UAV should be shared via communications. Although a variety of studies have focused on the algorithms for formation flight, these studies have mainly demonstrated the performance of formation flight using numerical simulations or ground robots, which do not reflect the dynamic characteristics of UAVs. In this study, an onboard sensor information sharing system and formation flight algorithms for multiple UAVs are proposed. The communication delays of radiofrequency (RF) telemetry are analyzed to enable the implementation of the onboard sensor information sharing system. Using the sensor information sharing, the formation guidance law for multiple UAVs, which includes both a circular and close formation, is designed. The hardware system, which includes avionics and an airframe, is constructed for the proposed multi-UAV platform. A numerical simulation is performed to demonstrate the performance of the formation flight guidance and control system for multiple UAVs. Finally, a flight test is conducted to verify the proposed algorithm for the multi-UAV system. PMID:26193281

Slic Superpixels for Object Delineation from Uav Data

NASA Astrophysics Data System (ADS)

Crommelinck, S.; Bennett, R.; Gerke, M.; Koeva, M. N.; Yang, M. Y.; Vosselman, G.

2017-08-01

Unmanned aerial vehicles (UAV) are increasingly investigated with regard to their potential to create and update (cadastral) maps. UAVs provide a flexible and low-cost platform for high-resolution data, from which object outlines can be accurately delineated. This delineation could be automated with image analysis methods to improve existing mapping procedures that are cost, time and labor intensive and of little reproducibility. This study investigates a superpixel approach, namely simple linear iterative clustering (SLIC), in terms of its applicability to UAV data. The approach is investigated in terms of its applicability to high-resolution UAV orthoimages and in terms of its ability to delineate object outlines of roads and roofs. Results show that the approach is applicable to UAV orthoimages of 0.05 m GSD and extents of 100 million and 400 million pixels. Further, the approach delineates the objects with the high accuracy provided by the UAV orthoimages at completeness rates of up to 64 %. The approach is not suitable as a standalone approach for object delineation. However, it shows high potential for a combination with further methods that delineate objects at higher correctness rates in exchange of a lower localization quality. This study provides a basis for future work that will focus on the incorporation of multiple methods for an interactive, comprehensive and accurate object delineation from UAV data. This aims to support numerous application fields such as topographic and cadastral mapping.

Using Unmanned Aerial Vehicle (UAV) for spatio-temporal monitoring of soil erosion and roughness in Chania, Crete, Greece

NASA Astrophysics Data System (ADS)

Alexakis, Dimitrios; Seiradakis, Kostas; Tsanis, Ioannis

2016-04-01

This article presents a remote sensing approach for spatio-temporal monitoring of both soil erosion and roughness using an Unmanned Aerial Vehicle (UAV). Soil erosion by water is commonly known as one of the main reasons for land degradation. Gully erosion causes considerable soil loss and soil degradation. Furthermore, quantification of soil roughness (irregularities of the soil surface due to soil texture) is important and affects surface storage and infiltration. Soil roughness is one of the most susceptible to variation in time and space characteristics and depends on different parameters such as cultivation practices and soil aggregation. A UAV equipped with a digital camera was employed to monitor soil in terms of erosion and roughness in two different study areas in Chania, Crete, Greece. The UAV followed predicted flight paths computed by the relevant flight planning software. The photogrammetric image processing enabled the development of sophisticated Digital Terrain Models (DTMs) and ortho-image mosaics with very high resolution on a sub-decimeter level. The DTMs were developed using photogrammetric processing of more than 500 images acquired with the UAV from different heights above the ground level. As the geomorphic formations can be observed from above using UAVs, shadowing effects do not generally occur and the generated point clouds have very homogeneous and high point densities. The DTMs generated from UAV were compared in terms of vertical absolute accuracies with a Global Navigation Satellite System (GNSS) survey. The developed data products were used for quantifying gully erosion and soil roughness in 3D as well as for the analysis of the surrounding areas. The significant elevation changes from multi-temporal UAV elevation data were used for estimating diachronically soil loss and sediment delivery without installing sediment traps. Concerning roughness, statistical indicators of surface elevation point measurements were estimated and various

Precise attitude rate estimation using star images obtained by mission telescope for satellite missions

NASA Astrophysics Data System (ADS)

Inamori, Takaya; Hosonuma, Takayuki; Ikari, Satoshi; Saisutjarit, Phongsatorn; Sako, Nobutada; Nakasuka, Shinichi

2015-02-01

Recently, small satellites have been employed in various satellite missions such as astronomical observation and remote sensing. During these missions, the attitudes of small satellites should be stabilized to a higher accuracy to obtain accurate science data and images. To achieve precise attitude stabilization, these small satellites should estimate their attitude rate under the strict constraints of mass, space, and cost. This research presents a new method for small satellites to precisely estimate angular rate using star blurred images by employing a mission telescope to achieve precise attitude stabilization. In this method, the angular velocity is estimated by assessing the quality of a star image, based on how blurred it appears to be. Because the proposed method utilizes existing mission devices, a satellite does not require additional precise rate sensors, which makes it easier to achieve precise stabilization given the strict constraints possessed by small satellites. The research studied the relationship between estimation accuracy and parameters used to achieve an attitude rate estimation, which has a precision greater than 1 × 10-6 rad/s. The method can be applied to all attitude sensors, which use optics systems such as sun sensors and star trackers (STTs). Finally, the method is applied to the nano astrometry satellite Nano-JASMINE, and we investigate the problems that are expected to arise with real small satellites by performing numerical simulations.

Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV.

PubMed

Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad

2016-05-09

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability.

Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV

PubMed Central

Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad

2016-01-01

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability. PMID:27171084

Millimeter-wave micro-Doppler measurements of small UAVs

NASA Astrophysics Data System (ADS)

Rahman, Samiur; Robertson, Duncan A.

2017-05-01

This paper discusses the micro-Doppler signatures of small UAVs obtained from a millimeter-wave radar system. At first, simulation results are shown to demonstrate the theoretical concept. It is illustrated that whilst the propeller rotation rate of the small UAVs is quite high, millimeter-wave radar systems are capable of capturing the full micro-Doppler spread. Measurements of small UAVs have been performed with both CW and FMCW radars operating at 94 GHz. The CW radar was used for obtaining micro-Doppler signatures of individual propellers. The field test data of a flying small UAV was collected with the FMCW radar and was processed to extract micro-Doppler signatures. The high fidelity results clearly reveal features such as blade flashes and propeller rotation modulation lines which can be used to classify targets. This work confirms that millimeter-wave radar is suitable for the detection and classification of small UAVs at usefully long ranges.

Development of a bio-inspired UAV perching system

NASA Astrophysics Data System (ADS)

Xie, Pu

Although technologies of unmanned aerial vehicles (UAVs) including micro air vehicles (MAVs) have been greatly advanced in the recent years, it is still very difficult for a UAV to perform some very challenging tasks such as perching to any desired spot reliably and agilely like a bird. Unlike the UAVs, the biological control mechanism of birds has been optimized through millions of year evolution and hence, they can perform many extremely maneuverability tasks, such as perching or grasping accurately and robustly. Therefore, we have good reason to learn from the nature in order to significantly improve the capabilities of UAVs. The development of a UAV perching system is becoming feasible, especially after a lot of research contributions in ornithology which involve the analysis of the bird's functionalities. Meanwhile, as technology advances in many engineering fields, such as airframes, propulsion, sensors, batteries, micro-electromechanical-system (MEMS), and UAV technology is also advancing rapidly. All of these research efforts in ornithology and the fast growing development technologies in UAV applications are motivating further interests and development in the area of UAV perching and grasping research. During the last decade, the research contributions about UAV perching and grasping were mainly based on fixed-wing, flapping-wing, and rotorcraft UAVs. However, most of the current researches in UAV systems with perching and grasping capability are focusing on either active (powered) grasping and perching or passive (unpowered) perching. Although birds do have both active and passive perching capabilities depending on their needs, there is no UAV perching system with both capabilities. In this project, we focused on filling this gap. Inspired by the anatomy analysis of bird legs and feet, a novel perching system has been developed to implement the bionics action for both active grasping and passive perching. In addition, for developing a robust and

Speed Approach for UAV Collision Avoidance

NASA Astrophysics Data System (ADS)

Berdonosov, V. D.; Zivotova, A. A.; Htet Naing, Zaw; Zhuravlev, D. O.

2018-05-01

The article represents a new approach of defining potential collision of two or more UAVs in a common aviation area. UAVs trajectories are approximated by two or three trajectories’ points obtained from the ADS-B system. In the process of defining meeting points of trajectories, two cutoff values of the critical speed range, at which a UAVs collision is possible, are calculated. As calculation expressions for meeting points and cutoff values of the critical speed are represented in the analytical form, even if an on-board computer system has limited computational capacity, the time for calculation will be far less than the time of receiving data from ADS-B. For this reason, calculations can be updated at each cycle of new data receiving, and the trajectory approximation can be bounded by straight lines. Such approach allows developing the compact algorithm of collision avoidance, even for a significant amount of UAVs (more than several dozens). To proof the research adequacy, modeling was performed using a software system developed specifically for this purpose.

Comprehensive Evaluation of Attitude and Orbit Estimation Using Actual Earth Magnetic Field Data

NASA Technical Reports Server (NTRS)

Deutschmann, Julie K.; Bar-Itzhack, Itzhack Y.

2000-01-01

A single, augmented Extended Kalman Filter (EKF), which simultaneously and autonomously estimates spacecraft attitude and orbit has been developed and successfully tested with real magnetometer and gyro data only. Because the earth magnetic field is a function of time and position, and because time is known quite precisely, the differences between the computed and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft orbit, are a function of both orbit and attitude errors. Thus, conceivably these differences could be used to estimate both orbit and attitude; an observability study validated this assumption. The results of testing the EKF with actual magnetometer and gyro data, from four satellites supported by the NASA Goddard Space Flight Center (GSFC) Guidance, Navigation, and Control Center, are presented and evaluated. They confirm the assumption that a single EKF can estimate both attitude and orbit when using gyros and magnetometers only.

Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

NASA Astrophysics Data System (ADS)

Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

2017-09-01

Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

Research on UAV Intelligent Obstacle Avoidance Technology During Inspection of Transmission Line

NASA Astrophysics Data System (ADS)

Wei, Chuanhu; Zhang, Fei; Yin, Chaoyuan; Liu, Yue; Liu, Liang; Li, Zongyu; Wang, Wanguo

Autonomous obstacle avoidance of unmanned aerial vehicle (hereinafter referred to as UAV) in electric power line inspection process has important significance for operation safety and economy for UAV intelligent inspection system of transmission line as main content of UAV intelligent inspection system on transmission line. In the paper, principles of UAV inspection obstacle avoidance technology of transmission line are introduced. UAV inspection obstacle avoidance technology based on particle swarm global optimization algorithm is proposed after common obstacle avoidance technologies are studied. Stimulation comparison is implemented with traditional UAV inspection obstacle avoidance technology which adopts artificial potential field method. Results show that UAV inspection strategy of particle swarm optimization algorithm, adopted in the paper, is prominently better than UAV inspection strategy of artificial potential field method in the aspects of obstacle avoidance effect and the ability of returning to preset inspection track after passing through the obstacle. An effective method is provided for UAV inspection obstacle avoidance of transmission line.

a Study on Automatic Uav Image Mosaic Method for Paroxysmal Disaster

NASA Astrophysics Data System (ADS)

Li, M.; Li, D.; Fan, D.

2012-07-01

As everyone knows, some paroxysmal disasters, such as flood, can do a great damage in short time. Timely, accurate, and fast acquisition of sufficient disaster information is the prerequisite facing with disaster emergency. Due to UAV's superiority in acquiring disaster data, UAV, a rising remote sensed data has gradually become the first choice for departments of disaster prevention and mitigation to collect the disaster information at first hand. In this paper, a novel and fast strategy is proposed for registering and mosaicing UAV data. Firstly, the original images will not be zoomed in to be 2 times larger ones at the initial course of SIFT operator, and the total number of the pyramid octaves in scale space is reduced to speed up the matching process; sequentially, RANSAC(Random Sample Consensus) is used to eliminate the mismatching tie points. Then, bundle adjustment is introduced to solve all of the camera geometrical calibration parameters jointly. Finally, the best seamline searching strategy based on dynamic schedule is applied to solve the dodging problem arose by aeroplane's side-looking. Beside, a weighted fusion estimation algorithm is employed to eliminate the "fusion ghost" phenomenon.

A method of fast mosaic for massive UAV images

NASA Astrophysics Data System (ADS)

Xiang, Ren; Sun, Min; Jiang, Cheng; Liu, Lei; Zheng, Hui; Li, Xiaodong

2014-11-01

With the development of UAV technology, UAVs are used widely in multiple fields such as agriculture, forest protection, mineral exploration, natural disaster management and surveillances of public security events. In contrast of traditional manned aerial remote sensing platforms, UAVs are cheaper and more flexible to use. So users can obtain massive image data with UAVs, but this requires a lot of time to process the image data, for example, Pix4UAV need approximately 10 hours to process 1000 images in a high performance PC. But disaster management and many other fields require quick respond which is hard to realize with massive image data. Aiming at improving the disadvantage of high time consumption and manual interaction, in this article a solution of fast UAV image stitching is raised. GPS and POS data are used to pre-process the original images from UAV, belts and relation between belts and images are recognized automatically by the program, in the same time useless images are picked out. This can boost the progress of finding match points between images. Levenberg-Marquard algorithm is improved so that parallel computing can be applied to shorten the time of global optimization notably. Besides traditional mosaic result, it can also generate superoverlay result for Google Earth, which can provide a fast and easy way to show the result data. In order to verify the feasibility of this method, a fast mosaic system of massive UAV images is developed, which is fully automated and no manual interaction is needed after original images and GPS data are provided. A test using 800 images of Kelan River in Xinjiang Province shows that this system can reduce 35%-50% time consumption in contrast of traditional methods, and increases respond speed of UAV image processing rapidly.

Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

PubMed Central

Gökçe, Fatih; Üçoluk, Göktürk; Şahin, Erol; Kalkan, Sinan

2015-01-01

Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032×778 resolution) and 150 ms outdoors (1280×720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms. PMID:26393599

Accuracy Investigation of Creating Orthophotomaps Based on Images Obtained by Applying Trimble-UX5 UAV

NASA Astrophysics Data System (ADS)

Hlotov, Volodymyr; Hunina, Alla; Siejka, Zbigniew

2017-06-01

The main purpose of this work is to confirm the possibility of making largescale orthophotomaps applying unmanned aerial vehicle (UAV) Trimble- UX5. A planned altitude reference of the studying territory was carried out before to the aerial surveying. The studying territory has been marked with distinctive checkpoints in the form of triangles (0.5 × 0.5 × 0.2 m). The checkpoints used to precise the accuracy of orthophotomap have been marked with similar triangles. To determine marked reference point coordinates and check-points method of GNSS in real-time kinematics (RTK) measuring has been applied. Projecting of aerial surveying has been done with the help of installed Trimble Access Aerial Imaging, having been used to run out the UX5. Aerial survey out of the Trimble UX5 UAV has been done with the help of the digital camera SONY NEX-5R from 200m and 300 m altitude. These aerial surveying data have been calculated applying special photogrammetric software Pix 4D. The orthophotomap of the surveying objects has been made with its help. To determine the precise accuracy of the got results of aerial surveying the checkpoint coordinates according to the orthophotomap have been set. The average square error has been calculated according to the set coordinates applying GNSS measurements. A-priori accuracy estimation of spatial coordinates of the studying territory using the aerial surveying data have been calculated: mx=0.11 m, my=0.15 m, mz=0.23 m in the village of Remeniv and mx=0.26 m, my=0.38 m, mz=0.43 m in the town of Vynnyky. The accuracy of determining checkpoint coordinates has been investigated using images obtained out of UAV and the average square error of the reference points. Based on comparative analysis of the got results of the accuracy estimation of the made orthophotomap it can be concluded that the value the average square error does not exceed a-priori accuracy estimation. The possibility of applying Trimble UX5 UAV for making large

Obstacle Detection and Avoidance System Based on Monocular Camera and Size Expansion Algorithm for UAVs

PubMed Central

Al-Kaff, Abdulla; García, Fernando; Martín, David; De La Escalera, Arturo; Armingol, José María

2017-01-01

One of the most challenging problems in the domain of autonomous aerial vehicles is the designing of a robust real-time obstacle detection and avoidance system. This problem is complex, especially for the micro and small aerial vehicles, that is due to the Size, Weight and Power (SWaP) constraints. Therefore, using lightweight sensors (i.e., Digital camera) can be the best choice comparing with other sensors; such as laser or radar.For real-time applications, different works are based on stereo cameras in order to obtain a 3D model of the obstacles, or to estimate their depth. Instead, in this paper, a method that mimics the human behavior of detecting the collision state of the approaching obstacles using monocular camera is proposed. The key of the proposed algorithm is to analyze the size changes of the detected feature points, combined with the expansion ratios of the convex hull constructed around the detected feature points from consecutive frames. During the Aerial Vehicle (UAV) motion, the detection algorithm estimates the changes in the size of the area of the approaching obstacles. First, the method detects the feature points of the obstacles, then extracts the obstacles that have the probability of getting close toward the UAV. Secondly, by comparing the area ratio of the obstacle and the position of the UAV, the method decides if the detected obstacle may cause a collision. Finally, by estimating the obstacle 2D position in the image and combining with the tracked waypoints, the UAV performs the avoidance maneuver. The proposed algorithm was evaluated by performing real indoor and outdoor flights, and the obtained results show the accuracy of the proposed algorithm compared with other related works. PMID:28481277

Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

PubMed

Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

Uav Borne Low Altitude Photogrammetry System

NASA Astrophysics Data System (ADS)

Lin, Z.; Su, G.; Xie, F.

2012-07-01

In this paper，the aforementioned three major aspects related to the Unmanned Aerial Vehicles (UAV) system for low altitude aerial photogrammetry, i.e., flying platform, imaging sensor system and data processing software, are discussed. First of all, according to the technical requirements about the least cruising speed, the shortest taxiing distance, the level of the flight control and the performance of turbulence flying, the performance and suitability of the available UAV platforms (e.g., fixed wing UAVs, the unmanned helicopters and the unmanned airships) are compared and analyzed. Secondly, considering the restrictions on the load weight of a platform and the resolution pertaining to a sensor, together with the exposure equation and the theory of optical information, the principles of designing self-calibration and self-stabilizing combined wide-angle digital cameras (e.g., double-combined camera and four-combined camera) are placed more emphasis on. Finally, a software named MAP-AT, considering the specialty of UAV platforms and sensors, is developed and introduced. Apart from the common functions of aerial image processing, MAP-AT puts more effort on automatic extraction, automatic checking and artificial aided adding of the tie points for images with big tilt angles. Based on the recommended process for low altitude photogrammetry with UAVs in this paper, more than ten aerial photogrammetry missions have been accomplished, the accuracies of Aerial Triangulation, Digital orthophotos(DOM)and Digital Line Graphs(DLG) of which meet the standard requirement of 1:2000, 1:1000 and 1:500 mapping.

Wetland Vegetation Integrity Assessment with Low Altitude Multispectral Uav Imagery

NASA Astrophysics Data System (ADS)

Boon, M. A.; Tesfamichael, S.

2017-08-01

deteriorate (change score) in the future. However a lower impact score were determined utilising the multispectral UAV imagery and NDVI. The result is a more accurate estimation of the impacts in the wetland.

Beach Volume Change Using Uav Photogrammetry Songjung Beach, Korea

NASA Astrophysics Data System (ADS)

Yoo, C. I.; Oh, T. S.

2016-06-01

Natural beach is controlled by many factors related to wave and tidal forces, wind, sediment, and initial topography. For this reason, if numerous topographic data of beach is accurately collected, coastal erosion/acceleration is able to be assessed and clarified. Generally, however, many studies on coastal erosion have limitation to analyse the whole beach, carried out of partial area as like shoreline (horizontal 2D) and beach profile (vertical 2D) on account of limitation of numerical simulation. This is an important application for prevention of coastal erosion, and UAV photogrammetry is also used to 3D topographic data. This paper analyses the use of unmanned aerial vehicles (UAV) to 3D map and beach volume change. UAV (Quadcopter) equipped with a non-metric camera was used to acquire images in Songjung beach which is located south-east Korea peninsula. The dynamics of beach topography, its geometric properties and estimates of eroded and deposited sand volumes were determined by combining elevation data with quarterly RTK-VRS measurements. To explore the new possibilities for assessment of coastal change we have developed a methodology for 3D analysis of coastal topography evolution based on existing high resolution elevation data combined with low coast, UAV and on-ground RTK-VRS surveys. DSMs were obtained by stereo-matching using Agisoft Photoscan. Using GCPs the vertical accuracy of the DSMs was found to be 10 cm or better. The resulting datasets were integrated in a local coordinates and the method proved to be a very useful fool for the detection of areas where coastal erosion occurs and for the quantification of beach change. The value of such analysis is illustrated by applications to coastal of South Korea sites that face significant management challenges.

Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

PubMed Central

Xi jun, Gao; Zi li, Chen; Yong Jiang, Hu

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication. PMID:24977185

Development and evaluation of unmanned aerial vehicle (UAV) magnetometry systems

NASA Astrophysics Data System (ADS)

Parvar, Kiyavash

In this thesis, the procedure of conducting magnetic surveys from a UAV platform is investigated. In the process of evaluating UAVs for such surveys, magnetic sensors capable of operating on a UAV platform were tested using a terrestrial survey, as well as on a UAV-platform. Results were then compared to a model of the area generated using a proton precession magnetometer. Magnetic signature of the UAVs are discussed and impact values are calculated. For a better understanding of the magnetic fields around UAVs some micro-surveys were conducted with the help of a fluxgate magnetometer around two UAVs. Results of such surveys were used to determine a location to mount the magnetometer during the survey. A test survey over a known anomaly (a visible chromite outcrop in Oman) is conducted in order to determine the feasibility of using UAV-based magnetometry for chromite exploration. Observations were taken at two different elevations in order to generate a 3-D model of the magnetic field. Later, after applying upward continuation filters and comparing the calculated results to the real values, the reliability and uncertainty levels of such filters were investigated. Results show that magnetometery on UAV platforms is feasible. Unwanted signals can be noticeable and produce fake anomalies by the end of each line because of the swinging effect of the suspended magnetometer below the UAV. This should be reduced by hardware and software modifications i.e. applying non-linear filters and mounting the sensor on a rigid rod. Also, it was derived that the error level associated with upward continuation filters exceeds 45% and thus, using such filters instead of actual observations is not suggested in gradiometry. Moreover, 3-D magnetic gradient surveys can be beneficial for future inversion problems.

Coordinating UAV information for executing national security-oriented collaboration

NASA Astrophysics Data System (ADS)

Isenor, Anthony W.; Allard, Yannick; Lapinski, Anna-Liesa S.; Demers, Hugues; Radulescu, Dan

2014-10-01

Unmanned Aerial Vehicles (UAVs) are being used by numerous nations for defence-related missions. In some cases, the UAV is considered a cost-effective means to acquire data such as imagery over a location or object. Considering Canada's geographic expanse, UAVs are also being suggested as a potential platform for use in surveillance of remote areas, such as northern Canada. However, such activities are typically associated with security as opposed to defence. The use of a defence platform for security activities introduces the issue of information exchange between the defence and security communities and their software applications. This paper explores the flow of information from the system used by the UAVs employed by the Royal Canadian Navy. Multiple computers are setup, each with the information system used by the UAVs, including appropriate communication between the systems. Simulated data that may be expected from a typical maritime UAV mission is then fed into the information system. The information structures common to the Canadian security community are then used to store and transfer the simulated data. The resulting data flow from the defence-oriented UAV system to the security-oriented information structure is then displayed using an open source geospatial application. Use of the information structures and applications relevant to the security community avoids the distribution restrictions often associated with defence-specific applications.

Study on the Computational Estimation Performance and Computational Estimation Attitude of Elementary School Fifth Graders in Taiwan

ERIC Educational Resources Information Center

Tsao, Yea-Ling; Pan, Ting-Rung

2011-01-01

Main purpose of this study is to investigate what level of computational estimation performance is possessed by fifth graders and explore computational estimation attitude towards fifth graders. Two hundred and thirty-five Grade-5 students from four elementary schools in Taipei City were selected for "Computational Estimation Test" and…

Unmanned Aerial Vehicle (UAV) associated DTM quality evaluation and hazard assessment

NASA Astrophysics Data System (ADS)

Huang, Mei-Jen; Chen, Shao-Der; Chao, Yu-Jui; Chiang, Yi-Lin; Chang, Kuo-Jen

2014-05-01

Taiwan, due to the high seismicity and high annual rainfall, numerous landslides triggered every year and severe impacts affect the island. Concerning to the catastrophic landslides, the key information of landslide, including range of landslide, volume estimation and the subsequent evolution are important when analyzing the triggering mechanism, hazard assessment and mitigation. Thus, the morphological analysis gives a general overview for the landslides and been considered as one of the most fundamental information. We try to integrate several technologies, especially by Unmanned Aerial Vehicle (UAV) and multi-spectral camera, to decipher the consequence and the potential hazard, and the social impact. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precious information. Benefited of the advancing of informatics, remote-sensing and electric technologies, the Unmanned Aerial Vehicle (UAV) photogrammetry mas been improve significantly. The study tries to integrate several methods, including, 1) Remote-sensing images gathered by Unmanned Aerial Vehicle (UAV) and by aerial photos taken in different periods; 2) field in-situ geologic investigation; 3) Differential GPS, RTK GPS and Ground LiDAR field in-site geoinfomatics measurements; 4) Construct the DTMs before and after landslide, as well as the subsequent periods using UAV and aerial photos; 5) Discrete element method should be applied to understand the geomaterial composing the slope failure, for predicting earthquake-induced and rainfall-induced landslides displacement. First at all, we evaluate the Microdrones MD4-1000 UAV airphotos derived Digital Terrain Model (DTM). The ground resolution of the DSM point cloud of could be as high as 10 cm. By integrated 4 ground control point within an area of 56 hectares, compared with LiDAR DSM and filed RTK-GPS surveying, the mean error is as low as 6cm with a standard deviation of 17cm. The quality of the

Computational analysis of unmanned aerial vehicle (UAV)

NASA Astrophysics Data System (ADS)

Abudarag, Sakhr; Yagoub, Rashid; Elfatih, Hassan; Filipovic, Zoran

2017-01-01

A computational analysis has been performed to verify the aerodynamics properties of Unmanned Aerial Vehicle (UAV). The UAV-SUST has been designed and fabricated at the Department of Aeronautical Engineering at Sudan University of Science and Technology in order to meet the specifications required for surveillance and reconnaissance mission. It is classified as a medium range and medium endurance UAV. A commercial CFD solver is used to simulate steady and unsteady aerodynamics characteristics of the entire UAV. In addition to Lift Coefficient (CL), Drag Coefficient (CD), Pitching Moment Coefficient (CM) and Yawing Moment Coefficient (CN), the pressure and velocity contours are illustrated. The aerodynamics parameters are represented a very good agreement with the design consideration at angle of attack ranging from zero to 26 degrees. Moreover, the visualization of the velocity field and static pressure contours is indicated a satisfactory agreement with the proposed design. The turbulence is predicted by enhancing K-ω SST turbulence model within the computational fluid dynamics code.

Critical infrastructure monitoring using UAV imagery

NASA Astrophysics Data System (ADS)

Maltezos, Evangelos; Skitsas, Michael; Charalambous, Elisavet; Koutras, Nikolaos; Bliziotis, Dimitris; Themistocleous, Kyriacos

2016-08-01

The constant technological evolution in Computer Vision enabled the development of new techniques which in conjunction with the use of Unmanned Aerial Vehicles (UAVs) may extract high quality photogrammetric products for several applications. Dense Image Matching (DIM) is a Computer Vision technique that can generate a dense 3D point cloud of an area or object. The use of UAV systems and DIM techniques is not only a flexible and attractive solution to produce accurate and high qualitative photogrammetric results but also is a major contribution to cost effectiveness. In this context, this study aims to highlight the benefits of the use of the UAVs in critical infrastructure monitoring applying DIM. A Multi-View Stereo (MVS) approach using multiple images (RGB digital aerial and oblique images), to fully cover the area of interest, is implemented. The application area is an Olympic venue in Attica, Greece, at an area of 400 acres. The results of our study indicate that the UAV+DIM approach respond very well to the increasingly greater demands for accurate and cost effective applications when provided with, a 3D point cloud and orthomosaic.

A Discussion of Aerodynamic Control Effectors (ACEs) for Unmanned Air Vehicles (UAVs)

NASA Technical Reports Server (NTRS)

Wood, Richard M.

2002-01-01

A Reynolds number based, unmanned air vehicle classification structure has been developed which identifies four classes of unmanned air vehicle concepts. The four unmanned air vehicle (UAV) classes are; Micro UAV, Meso UAV, Macro UAV, and Mega UAV. In a similar fashion a labeling scheme for aerodynamic control effectors (ACE) was developed and eleven types of ACE concepts were identified. These eleven types of ACEs were laid out in a five (5) layer scheme. The final section of the paper correlated the various ACE concepts to the four UAV classes and ACE recommendations are offered for future design activities.

Heterogeneous CPU-GPU moving targets detection for UAV video

NASA Astrophysics Data System (ADS)

Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan

2017-07-01

Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.

Optimization of processing parameters of UAV integral structural components based on yield response

NASA Astrophysics Data System (ADS)

Chen, Yunsheng

2018-05-01

In order to improve the overall strength of unmanned aerial vehicle (UAV), it is necessary to optimize the processing parameters of UAV structural components, which is affected by initial residual stress in the process of UAV structural components processing. Because machining errors are easy to occur, an optimization model for machining parameters of UAV integral structural components based on yield response is proposed. The finite element method is used to simulate the machining parameters of UAV integral structural components. The prediction model of workpiece surface machining error is established, and the influence of the path of walking knife on residual stress of UAV integral structure is studied, according to the stress of UAV integral component. The yield response of the time-varying stiffness is analyzed, and the yield response and the stress evolution mechanism of the UAV integral structure are analyzed. The simulation results show that this method is used to optimize the machining parameters of UAV integral structural components and improve the precision of UAV milling processing. The machining error is reduced, and the deformation prediction and error compensation of UAV integral structural parts are realized, thus improving the quality of machining.

Comparison of Uncalibrated Rgbvi with Spectrometer-Based Ndvi Derived from Uav Sensing Systems on Field Scale

NASA Astrophysics Data System (ADS)

Bareth, G.; Bolten, A.; Gnyp, M. L.; Reusch, S.; Jasper, J.

2016-06-01

The development of UAV-based sensing systems for agronomic applications serves the improvement of crop management. The latter is in the focus of precision agriculture which intends to optimize yield, fertilizer input, and crop protection. Besides, in some cropping systems vehicle-based sensing devices are less suitable because fields cannot be entered from certain growing stages onwards. This is true for rice, maize, sorghum, and many more crops. Consequently, UAV-based sensing approaches fill a niche of very high resolution data acquisition on the field scale in space and time. While mounting RGB digital compact cameras to low-weight UAVs (< 5 kg) is well established, the miniaturization of sensors in the last years also enables hyperspectral data acquisition from those platforms. From both, RGB and hyperspectral data, vegetation indices (VIs) are computed to estimate crop growth parameters. In this contribution, we compare two different sensing approaches from a low-weight UAV platform (< 5 kg) for monitoring a nitrogen field experiment of winter wheat and a corresponding farmers' field in Western Germany. (i) A standard digital compact camera was flown to acquire RGB images which are used to compute the RGBVI and (ii) NDVI is computed from a newly modified version of the Yara N-Sensor. The latter is a well-established tractor-based hyperspectral sensor for crop management and is available on the market since a decade. It was modified for this study to fit the requirements of UAV-based data acquisition. Consequently, we focus on three objectives in this contribution: (1) to evaluate the potential of the uncalibrated RGBVI for monitoring nitrogen status in winter wheat, (2) investigate the UAV-based performance of the modified Yara N-Sensor, and (3) compare the results of the two different UAV-based sensing approaches for winter wheat.

Design of UAV high resolution image transmission system

NASA Astrophysics Data System (ADS)

Gao, Qiang; Ji, Ming; Pang, Lan; Jiang, Wen-tao; Fan, Pengcheng; Zhang, Xingcheng

2017-02-01

In order to solve the problem of the bandwidth limitation of the image transmission system on UAV, a scheme with image compression technology for mini UAV is proposed, based on the requirements of High-definition image transmission system of UAV. The video codec standard H.264 coding module and key technology was analyzed and studied for UAV area video communication. Based on the research of high-resolution image encoding and decoding technique and wireless transmit method, The high-resolution image transmission system was designed on architecture of Android and video codec chip; the constructed system was confirmed by experimentation in laboratory, the bit-rate could be controlled easily, QoS is stable, the low latency could meets most applied requirement not only for military use but also for industrial applications.

UAV formation control design with obstacle avoidance in dynamic three-dimensional environment.

PubMed

Chang, Kai; Xia, Yuanqing; Huang, Kaoli

2016-01-01

This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

Time-Critical Cooperative Path Following of Multiple UAVs: Case Studies

DTIC Science & Technology

2012-10-30

control algorithm for UAVs in 3D space. Section IV derives a strategy for time-critical cooperative path following of multiple UAVs that relies on the...UAVs in 3D space, in which a fleet of UAVs is tasked to converge to and follow a set of desired feasible paths so as to meet spatial and temporal...cooperative trajectory generation is not addressed in this paper. In fact, it is assumed that a set of desired 3D time trajectories pd,i(td) : R → R3

Classical Photogrammetry and Uav - Selected Ascpects

NASA Astrophysics Data System (ADS)

Mikrut, S.

2016-06-01

The UAV technology seems to be highly future-oriented due to its low costs as compared to traditional aerial images taken from classical photogrammetry aircrafts. The AGH University of Science and Technology in Cracow - Department of Geoinformation, Photogrammetry and Environmental Remote Sensing focuses mainly on geometry and radiometry of recorded images. Various scientific research centres all over the world have been conducting the relevant research for years. The paper presents selected aspects of processing digital images made with the UAV technology. It provides on a practical example a comparison between a digital image taken from an airborne (classical) height, and the one made from an UAV level. In his research the author of the paper is trying to find an answer to the question: to what extent does the UAV technology diverge today from classical photogrammetry, and what are the advantages and disadvantages of both methods? The flight plan was made over the Tokarnia Village Museum (more than 0.5 km2) for two separate flights: the first was made by an UAV - System FT-03A built by FlyTech Solution Ltd. The second was made with the use of a classical photogrammetric Cesna aircraft furnished with an airborne photogrammetric camera (Ultra Cam Eagle). Both sets of photographs were taken with pixel size of about 3 cm, in order to have reliable data allowing for both systems to be compared. The project has made aerotriangulation independently for the two flights. The DTM was generated automatically, and the last step was the generation of an orthophoto. The geometry of images was checked under the process of aerotriangulation. To compare the accuracy of these two flights, control and check points were used. RMSE were calculated. The radiometry was checked by a visual method and using the author's own algorithm for feature extraction (to define edges with subpixel accuracy). After initial pre-processing of data, the images were put together, and shown side by side

French Interim MALE UAV Program

DTIC Science & Technology

2003-09-02

MINISTÈRE DE LA DÉFENSE June, 13th 2002 Lcl Monsterleet FAF Staff J. Caron EADS S&DE-ISR FRENCH INTERIM MALE UAV PROGRAM 4 INDUSTRIAL STATUS Report...2003 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE French Interim Male UAV Program 5a. CONTRACT 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) EADS

Consensus-based distributed estimation in multi-agent systems with time delay

NASA Astrophysics Data System (ADS)

Abdelmawgoud, Ahmed

During the last years, research in the field of cooperative control of swarm of robots, especially Unmanned Aerial Vehicles (UAV); have been improved due to the increase of UAV applications. The ability to track targets using UAVs has a wide range of applications not only civilian but also military as well. For civilian applications, UAVs can perform tasks including, but not limited to: map an unknown area, weather forecasting, land survey, and search and rescue missions. On the other hand, for military personnel, UAV can track and locate a variety of objects, including the movement of enemy vehicles. Consensus problems arise in a number of applications including coordination of UAVs, information processing in wireless sensor networks, and distributed multi-agent optimization. We consider a widely studied consensus algorithms for processing sensed data by different sensors in wireless sensor networks of dynamic agents. Every agent involved in the network forms a weighted average of its own estimated value of some state with the values received from its neighboring agents. We introduced a novelty of consensus-based distributed estimation algorithms. We propose a new algorithm to reach a consensus given time delay constraints. The proposed algorithm performance was observed in a scenario where a swarm of UAVs measuring the location of a ground maneuvering target. We assume that each UAV computes its state prediction and shares it with its neighbors only. However, the shared information applied to different agents with variant time delays. The entire group of UAVs must reach a consensus on target state. Different scenarios were also simulated to examine the effectiveness and performance in terms of overall estimation error, disagreement between delayed and non-delayed agents, and time to reach a consensus for each parameter contributing on the proposed algorithm.

The development of a UGV-mounted automated refueling system for VTOL UAVs

NASA Astrophysics Data System (ADS)

Wills, Mike; Burmeister, Aaron; Nelson, Travis; Denewiler, Thomas; Mullens, Kathy

2006-05-01

This paper describes the latest efforts to develop an Automated UAV Mission System (AUMS) for small vertical takeoff and landing (VTOL) unmanned air vehicles (UAVs). In certain applications such as force protection, perimeter security, and urban surveillance a VTOL UAV can provide far greater utility than fixed-wing UAVs or ground-based sensors. The VTOL UAV can operate much closer to an object of interest and can provide a hover-and-stare capability to keep its sensors trained on an object, while the fixed wing UAV would be forced into a higher altitude loitering pattern where its sensors would be subject to intermittent blockage by obstacles and terrain. The most significant disadvantage of a VTOL UAV when compared to a fixed-wing UAV is its reduced flight endurance. AUMS addresses this disadvantage by providing forward staging, refueling, and recovery capabilities for the VTOL UAV through a host unmanned ground vehicle (UGV), which serves as a launch/recovery platform and service station. The UGV has sufficient payload capacity to carry UAV fuel for multiple launch, recovery, and refuel iterations. The UGV also provides a highly mobile means of forward deploying a small UAV into hazardous areas unsafe for personnel, such as chemically or biologically contaminated areas. Teaming small UAVs with large UGVs can decrease risk to personnel and expand mission capabilities and effectiveness. There are numerous technical challenges being addressed by these development efforts. Among the challenges is the development and integration of a precision landing system compact and light enough to allow it to be mounted on a small VTOL UAV while providing repeatable landing accuracy to safely land on the AUMS. Another challenge is the design of a UGV-transportable, expandable, self-centering landing pad that contains hardware and safety devices for automatically refueling the UAV. A third challenge is making the design flexible enough to accommodate different types of VTOL UAVs

Path planning and Ground Control Station simulator for UAV

NASA Astrophysics Data System (ADS)

Ajami, A.; Balmat, J.; Gauthier, J.-P.; Maillot, T.

In this paper we present a Universal and Interoperable Ground Control Station (UIGCS) simulator for fixed and rotary wing Unmanned Aerial Vehicles (UAVs), and all types of payloads. One of the major constraints is to operate and manage multiple legacy and future UAVs, taking into account the compliance with NATO Combined/Joint Services Operational Environment (STANAG 4586). Another purpose of the station is to assign the UAV a certain degree of autonomy, via autonomous planification/replanification strategies. The paper is organized as follows. In Section 2, we describe the non-linear models of the fixed and rotary wing UAVs that we use in the simulator. In Section 3, we describe the simulator architecture, which is based upon interacting modules programmed independently. This simulator is linked with an open source flight simulator, to simulate the video flow and the moving target in 3D. To conclude this part, we tackle briefly the problem of the Matlab/Simulink software connection (used to model the UAV's dynamic) with the simulation of the virtual environment. Section 5 deals with the control module of a flight path of the UAV. The control system is divided into four distinct hierarchical layers: flight path, navigation controller, autopilot and flight control surfaces controller. In the Section 6, we focus on the trajectory planification/replanification question for fixed wing UAV. Indeed, one of the goals of this work is to increase the autonomy of the UAV. We propose two types of algorithms, based upon 1) the methods of the tangent and 2) an original Lyapunov-type method. These algorithms allow either to join a fixed pattern or to track a moving target. Finally, Section 7 presents simulation results obtained on our simulator, concerning a rather complicated scenario of mission.

System and method for correcting attitude estimation

NASA Technical Reports Server (NTRS)

Josselson, Robert H. (Inventor)

2010-01-01

A system includes an angular rate sensor disposed in a vehicle for providing angular rates of the vehicle, and an instrument disposed in the vehicle for providing line-of-sight control with respect to a line-of-sight reference. The instrument includes an integrator which is configured to integrate the angular rates of the vehicle to form non-compensated attitudes. Also included is a compensator coupled across the integrator, in a feed-forward loop, for receiving the angular rates of the vehicle and outputting compensated angular rates of the vehicle. A summer combines the non-compensated attitudes and the compensated angular rates of the to vehicle to form estimated vehicle attitudes for controlling the instrument with respect to the line-of-sight reference. The compensator is configured to provide error compensation to the instrument free-of any feedback loop that uses an error signal. The compensator may include a transfer function providing a fixed gain to the received angular rates of the vehicle. The compensator may, alternatively, include a is transfer function providing a variable gain as a function of frequency to operate on the received angular rates of the vehicle.

Development of a GPS/INS/MAG navigation system and waypoint navigator for a VTOL UAV

NASA Astrophysics Data System (ADS)

Meister, Oliver; Mönikes, Ralf; Wendel, Jan; Frietsch, Natalie; Schlaile, Christian; Trommer, Gert F.

2007-04-01

Unmanned aerial vehicles (UAV) can be used for versatile surveillance and reconnaissance missions. If a UAV is capable of flying automatically on a predefined path the range of possible applications is widened significantly. This paper addresses the development of the integrated GPS/INS/MAG navigation system and a waypoint navigator for a small vertical take-off and landing (VTOL) unmanned four-rotor helicopter with a take-off weight below 1 kg. The core of the navigation system consists of low cost inertial sensors which are continuously aided with GPS, magnetometer compass, and a barometric height information. Due to the fact, that the yaw angle becomes unobservable during hovering flight, the integration with a magnetic compass is mandatory. This integration must be robust with respect to errors caused by the terrestrial magnetic field deviation and interferences from surrounding electronic devices as well as ferrite metals. The described integration concept with a Kalman filter overcomes the problem that erroneous magnetic measurements yield to an attitude error in the roll and pitch axis. The algorithm provides long-term stable navigation information even during GPS outages which is mandatory for the flight control of the UAV. In the second part of the paper the guidance algorithms are discussed in detail. These algorithms allow the UAV to operate in a semi-autonomous mode position hold as well an complete autonomous waypoint mode. In the position hold mode the helicopter maintains its position regardless of wind disturbances which ease the pilot job during hold-and-stare missions. The autonomous waypoint navigator enable the flight outside the range of vision and beyond the range of the radio link. Flight test results of the implemented modes of operation are shown.

Using Distance Sensors to Perform Collision Avoidance Maneuvres on Uav Applications

NASA Astrophysics Data System (ADS)

Raimundo, A.; Peres, D.; Santos, N.; Sebastião, P.; Souto, N.

2017-08-01

The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. "Sense and Avoid" algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a Light Detection and Ranging (LiDAR), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk's flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station and UAV are made via Wi-Fi or cellular third or fourth generation (3G/4G). Some tests were made in order to evaluate the "Sense and Avoid" algorithm's overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and "Brake" mode on a real outdoor, proving its concepts.

Current development of UAV sense and avoid system

NASA Astrophysics Data System (ADS)

Zhahir, A.; Razali, A.; Mohd Ajir, M. R.

2016-10-01

As unmanned aerial vehicles (UAVs) are now gaining high interests from civil and commercialised market, the automatic sense and avoid (SAA) system is currently one of the essential features in research spotlight of UAV. Several sensor types employed in current SAA research and technology of sensor fusion that offers a great opportunity in improving detection and tracking system are presented here. The purpose of this paper is to provide an overview of SAA system development in general, as well as the current challenges facing UAV researchers and designers.

Comprehensive evaluation of attitude and orbit estimation using real earth magnetic field data

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack

1997-01-01

A single, augmented extended Kalman filter (EKF) which simultaneously and autonomously estimates spacecraft attitude and orbit was developed and tested with simulated and real magnetometer and rate data. Since the earth's magnetic field is a function of time and position, and since time is accurately known, the differences between the computed and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft's orbit, are a function of orbit and attitude errors. These differences can be used to estimate the orbit and attitude. The test results of the EKF with magnetometer and gyro data from three NASA satellites are presented and evaluated.

A Natural Interaction Interface for UAVs Using Intuitive Gesture Recognition

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Trujillo, Anna; Shimada, Kenji; Allen, Danette

2016-01-01

The popularity of unmanned aerial vehicles (UAVs) is increasing as technological advancements boost their favorability for a broad range of applications. One application is science data collection. In fields like Earth and atmospheric science, researchers are seeking to use UAVs to augment their current portfolio of platforms and increase their accessibility to geographic areas of interest. By increasing the number of data collection platforms UAVs will significantly improve system robustness and allow for more sophisticated studies. Scientists would like be able to deploy an available fleet of UAVs to fly a desired flight path and collect sensor data without needing to understand the complex low-level controls required to describe and coordinate such a mission. A natural interaction interface for a Ground Control System (GCS) using gesture recognition is developed to allow non-expert users (e.g., scientists) to define a complex flight path for a UAV using intuitive hand gesture inputs from the constructed gesture library. The GCS calculates the combined trajectory on-line, verifies the trajectory with the user, and sends it to the UAV controller to be flown.

Pricise Target Geolocation Based on Integeration of Thermal Video Imagery and Rtk GPS in Uavs

NASA Astrophysics Data System (ADS)

Hosseinpoor, H. R.; Samadzadegan, F.; Dadras Javan, F.

2015-12-01

There are an increasingly large number of uses for Unmanned Aerial Vehicles (UAVs) from surveillance, mapping and target geolocation. However, most of commercial UAVs are equipped with low-cost navigation sensors such as C/A code GPS and a low-cost IMU on board, allowing a positioning accuracy of 5 to 10 meters. This low accuracy which implicates that it cannot be used in applications that require high precision data on cm-level. This paper presents a precise process for geolocation of ground targets based on thermal video imagery acquired by small UAV equipped with RTK GPS. The geolocation data is filtered using a linear Kalman filter, which provides a smoothed estimate of target location and target velocity. The accurate geo-locating of targets during image acquisition is conducted via traditional photogrammetric bundle adjustment equations using accurate exterior parameters achieved by on board IMU and RTK GPS sensors and Kalman filtering and interior orientation parameters of thermal camera from pre-flight laboratory calibration process.

Repurposing Radiosonde Sensors for UAV Integration

NASA Astrophysics Data System (ADS)

Clowney, F. A.

2015-12-01

Radiosondes provide accurate, high-resolution meteorological data for a variety of purposes but are inefficient for studying the atmospheric boundary layer. Tethered balloons can provide greater temporal resolution but are difficult to acquire, hard to manage and limited in vertical resolution. UAVs appear to offer a more cost-effective method for gathering low-level meteorological data in situ, with a strong possibility of adding atmospheric chemistry. This potential is enhanced by the availability of new generations of small sensors along with dramatic advances in low-cost UAVs, especially rotary-wing. InterMet is using its experience in radiosonde design and manufacturing to develop sensor packages for fixed and rotary-wing UAVs, with the goal of delivering high-quality data at low cost. The challenge is to adapt affordable, high-accuracy sensors to the different UAV flight modes. Equally important is learning from the research community what is required for this data to have useful scientific value. Specific topics to be covered include data sampling and output rates, sensor response times, calibration, sensor placement, data storage and transfer, power consumption, integration with flight management systems and wind calculations. Beta test results for the iMet-XQ and iMet-XF sensor packages will be presented if available.

Applications of UAVs for Remote Sensing of Critical Infrastructure

NASA Technical Reports Server (NTRS)

Wegener, Steve; Brass, James; Schoenung, Susan

2003-01-01

The surveillance of critical facilities and national infrastructure such as waterways, roadways, pipelines and utilities requires advanced technological tools to provide timely, up to date information on structure status and integrity. Unmanned Aerial Vehicles (UAVs) are uniquely suited for these tasks, having large payload and long duration capabilities. UAVs also have the capability to fly dangerous and dull missions, orbiting for 24 hours over a particular area or facility providing around the clock surveillance with no personnel onboard. New UAV platforms and systems are becoming available for commercial use. High altitude platforms are being tested for use in communications, remote sensing, agriculture, forestry and disaster management. New payloads are being built and demonstrated onboard the UAVs in support of these applications. Smaller, lighter, lower power consumption imaging systems are currently being tested over coffee fields to determine yield and over fires to detect fire fronts and hotspots. Communication systems that relay video, meteorological and chemical data via satellite to users on the ground in real-time have also been demonstrated. Interest in this technology for infrastructure characterization and mapping has increased dramatically in the past year. Many of the UAV technological developments required for resource and disaster monitoring are being used for the infrastructure and facility mapping activity. This paper documents the unique contributions from NASA;s Environmental Research Aircraft and Sensor Technology (ERAST) program to these applications. ERAST is a UAV technology development effort by a consortium of private aeronautical companies and NASA. Details of demonstrations of UAV capabilities currently underway are also presented.

Benchmarking real-time RGBD odometry for light-duty UAVs

NASA Astrophysics Data System (ADS)

Willis, Andrew R.; Sahawneh, Laith R.; Brink, Kevin M.

2016-06-01

This article describes the theoretical and implementation challenges associated with generating 3D odometry estimates (delta-pose) from RGBD sensor data in real-time to facilitate navigation in cluttered indoor environments. The underlying odometry algorithm applies to general 6DoF motion; however, the computational platforms, trajectories, and scene content are motivated by their intended use on indoor, light-duty UAVs. Discussion outlines the overall software pipeline for sensor processing and details how algorithm choices for the underlying feature detection and correspondence computation impact the real-time performance and accuracy of the estimated odometry and associated covariance. This article also explores the consistency of odometry covariance estimates and the correlation between successive odometry estimates. The analysis is intended to provide users information needed to better leverage RGBD odometry within the constraints of their systems.

Calculation and Identification of the Aerodynamic Parameters for Small-Scaled Fixed-Wing UAVs.

PubMed

Shen, Jieliang; Su, Yan; Liang, Qing; Zhu, Xinhua

2018-01-13

The establishment of the Aircraft Dynamic Model(ADM) constitutes the prerequisite for the design of the navigation and control system, but the aerodynamic parameters in the model could not be readily obtained especially for small-scaled fixed-wing UAVs. In this paper, the procedure of computing the aerodynamic parameters is developed. All the longitudinal and lateral aerodynamic derivatives are firstly calculated through semi-empirical method based on the aerodynamics, rather than the wind tunnel tests or fluid dynamics software analysis. Secondly, the residuals of each derivative are proposed to be identified or estimated further via Extended Kalman Filter(EKF), with the observations of the attitude and velocity from the airborne integrated navigation system. Meanwhile, the observability of the targeted parameters is analyzed and strengthened through multiple maneuvers. Based on a small-scaled fixed-wing aircraft driven by propeller, the airborne sensors are chosen and the model of the actuators are constructed. Then, real flight tests are implemented to verify the calculation and identification process. Test results tell the rationality of the semi-empirical method and show the improvement of accuracy of ADM after the compensation of the parameters.

Calculation and Identification of the Aerodynamic Parameters for Small-Scaled Fixed-Wing UAVs

PubMed Central

Shen, Jieliang; Su, Yan; Liang, Qing; Zhu, Xinhua

2018-01-01

The establishment of the Aircraft Dynamic Model (ADM) constitutes the prerequisite for the design of the navigation and control system, but the aerodynamic parameters in the model could not be readily obtained especially for small-scaled fixed-wing UAVs. In this paper, the procedure of computing the aerodynamic parameters is developed. All the longitudinal and lateral aerodynamic derivatives are firstly calculated through semi-empirical method based on the aerodynamics, rather than the wind tunnel tests or fluid dynamics software analysis. Secondly, the residuals of each derivative are proposed to be identified or estimated further via Extended Kalman Filter (EKF), with the observations of the attitude and velocity from the airborne integrated navigation system. Meanwhile, the observability of the targeted parameters is analyzed and strengthened through multiple maneuvers. Based on a small-scaled fixed-wing aircraft driven by propeller, the airborne sensors are chosen and the model of the actuators are constructed. Then, real flight tests are implemented to verify the calculation and identification process. Test results tell the rationality of the semi-empirical method and show the improvement of accuracy of ADM after the compensation of the parameters. PMID:29342856

Analysis of Landslide Kinematics using Multi-temporal UAV Imagery, La Honda, California

NASA Astrophysics Data System (ADS)

Carey, J.; Pickering, A.; Prentice, C. S.; Pinter, N.; DeLong, S.

2017-12-01

High-resolution topographic data are vital to studies of earth-surface processes. The combination of unmanned aerial vehicle (UAV) photography and structure-from-motion (SfM) digital photogrammetry provide a quickly deployable and cost-effective method for monitoring geomorphic change and landscape evolution. We acquired imagery of an active landslide in La Honda, California using a GPS-enabled quadcopter UAV with a 12.4 megapixel camera. Deep-seated landslides were previously documented in this region during the winter of 1997-98, with movement recurring and the landslide expanding during the winters of 2004-05 and 2005-06. This study documents the kinematics of a new and separate landslide immediately adjacent to the previous ones, throughout the winter of 2016-17. The roughly triangular-shaped, deep-seated landslide covers an area of approximately 10,000 m2. The area is underlain by SW dipping late Miocene to Pliocene sandstones and mudstones. A 3 m high head scarp stretches along the northeast portion of the slide for approximately 100 m. Internally, the direction of movement is towards the southwest, with two prominent NW-SE striking extensional grabens and numerous tension cracks across the landslide body. Here we calculate displaced landslide volumes and surface displacements from multi-temporal UAV surveys. Photogrammetric reconstruction of UAV/SfM-derived point clouds allowed creation of six digital elevation models (DEMs) with spatial resolutions ranging from 3 to 15 cm per pixel. We derived displacement magnitude, direction and rate by comparing multiple generations of DEMs and orthophotos, and estimated displaced volumes by differencing subsequent DEMs. We then correlated displacements with total rainfall and rainfall intensity measurements. Detailed geomorphic maps identify major landslide features, documenting dominant surface processes. Additionally, we compare the accuracy of the UAV/SfM-derived DEM with a DEM sourced from a synchronous terrestrial

Towards a Biosynthetic UAV

NASA Technical Reports Server (NTRS)

Block, Eli; Byemerwa, Jovita; Dispenza, Ross; Doughty, Benjamin; Gillyard, KaNesha; Godbole, Poorwa; Gonzales-Wright, Jeanette; Hull, Ian; Kannappan, Jotthe; Levine, Alexander;

Radar sensing via a Micro-UAV-borne system

NASA Astrophysics Data System (ADS)

Catapano, Ilaria; Ludeno, Giovanni; Gennarelli, Gianluca; Soldovieri, Francesco; Rodi Vetrella, Amedeo; Fasano, Giancarmine

2017-04-01

In recent years, the miniaturization of flight control systems and payloads has contributed to a fast and widespread diffusion of micro-UAV (Unmanned Aircraft Vehicle). While micro-UAV can be a powerful tool in several civil applications such as environmental monitoring and surveillance, unleashing their full potential for societal benefits requires augmenting their sensing capability beyond the realm of active/passive optical sensors [1]. In this frame, radar systems are drawing attention since they allow performing missions in all-weather and day/night conditions and, thanks to the microwave ability to penetrate opaque media, they enable the detection and localization not only of surface objects but also of sub-surface/hidden targets. However, micro-UAV-borne radar imaging represents still a new frontier, since it is much more than a matter of technology miniaturization or payload installation, which can take advantage of the newly developed ultralight systems. Indeed, micro-UAV-borne radar imaging entails scientific challenges in terms of electromagnetic modeling and knowledge of flight dynamics and control. As a consequence, despite Synthetic Aperture Radar (SAR) imaging is a traditional remote sensing tool, its adaptation to micro-UAV is an open issue and so far only few case studies concerning the integration of SAR and UAV technologies have been reported worldwide [2]. In addition, only early results concerning subsurface imaging by means of an UAV-mounted radar are available [3]. As a contribution to radar imaging via autonomous micro-UAV, this communication presents a proof-of-concept experiment. This experiment represents the first step towards the development of a general methodological approach that exploits expertise about (sub-)surface imaging and aerospace systems with the aim to provide high-resolution images of the surveyed scene. In details, at the conference, we will present the results of a flight campaign carried out by using a single radar

Spinning Spacecraft Attitude Estimation Using Markley Variables: Filter Implementation And Results

NASA Technical Reports Server (NTRS)

Sedlak, Joseph E.

2005-01-01

Attitude estimation is often more difficult for spinning spacecraft than for three-axis stabilized platforms due to the need to follow rapidly-varying state vector elements and the lack of three-axis rate measurements from gyros. The estimation problem simplifies when torques are negligible and nutation has damped out, but the general case requires a sequential filter with dynamics propagation. This paper describes the implementation and test results for an extended Kalman filter for spinning spacecraft attitude and rate estimation based on a novel set of variables suggested in a paper by Markley [AAS93-3301 (referred to hereafter as Markley variables). Markley has demonstrated that the new set of variables provides a superior parameterization for numerical integration of the attitude dynamics for spinning or momentum-biased spacecraft. The advantage is that the Markley variables have fewer rapidly-varying elements than other representations such as the attitude quaternion and rate vector. A filter based on these variables was expected to show improved performance due to the more accurate numerical state propagation. However, for a variety of test cases, it has been found that the new filter, as currently implemented, does not perform significantly better than a quaternion-based filter that was developed and tested in parallel. This paper reviews the mathematical background for a filter based on Markley variables. It also describes some features of the implementation and presents test results. The test cases are based on a mission using magnetometer and Sun sensor data and gyro measurements on two axes normal to the spin axis. The orbit and attitude scenarios and spacecraft parameters are modeled after one of the THEMIS (Time History of Events and Macroscale Interactions during Substorms) probes. Several tests are presented that demonstrate the filter accuracy and convergence properties. The tests include torque-free motion with various nutation angles, large

Recording animal vocalizations from a UAV: bat echolocation during roost re-entry.

PubMed

Kloepper, Laura N; Kinniry, Morgan

2018-05-17

Unmanned aerial vehicles (UAVs) are rising in popularity for wildlife monitoring, but direct recordings of animal vocalizations have not yet been accomplished, likely due to the noise generated by the UAV. Echolocating bats, especially Tadarida brasiliensis, are good candidates for UAV recording due to their high-speed, high-altitude flight. Here, we use a UAV to record the signals of bats during morning roost re-entry. We designed a UAV to block the noise of the propellers from the receiving microphone, and report on the characteristics of bioacoustic recordings from a UAV. We report the first published characteristics of echolocation signals from bats during group flight and cave re-entry. We found changes in inter-individual time-frequency shape, suggesting that bats may use differences in call design when sensing in complex groups. Furthermore, our first documented successful recordings of animals in their natural habitat demonstrate that UAVs can be important tools for bioacoustic monitoring, and we discuss the ethical considerations for such monitoring.

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

PubMed

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-05-22

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

Two NextGen Air Safety Tools: An ADS-B Equipped UAV and a Wake Turbulence Estimator

NASA Astrophysics Data System (ADS)

Handley, Ward A.

Two air safety tools are developed in the context of the FAA's NextGen program. The first tool addresses the alarming increase in the frequency of near-collisions between manned and unmanned aircraft by equipping a common hobby class UAV with an ADS-B transponder that broadcasts its position, speed, heading and unique identification number to all local air traffic. The second tool estimates and outputs the location of dangerous wake vortex corridors in real time based on the ADS-B data collected and processed using a custom software package developed for this project. The TRansponder based Position Information System (TRAPIS) consists of data packet decoders, an aircraft database, Graphical User Interface (GUI) and the wake vortex extension application. Output from TRAPIS can be visualized in Google Earth and alleviates the problem of pilots being left to imagine where invisible wake vortex corridors are based solely on intuition or verbal warnings from ATC. The result of these two tools is the increased situational awareness, and hence safety, of human pilots in the National Airspace System (NAS).

The Defense Airborne Reconnaissance Office Unmanned Aerial Vehicle (UAV) Annual Report FY 1996.

DTIC Science & Technology

1996-11-06

i>’ ’" UAV Annual Report FY1996 6 November 1996 L DEFENSE MRBOBNEiSCONNAGSAHCEC UAVANNUAL REPORT OUR SECOND UNMANNED AERIAL VEHICLE (UAV...ANNUAL REPORT provides an overview of the Defense Department’s UAV program activities for fiscal year (FY) 1996 . The Defense Airborne Reconnaissance...significant accomplishments that UAVs have achieved this past year, FY 1996 . Simply stated, UAVs are moving from words to deeds. They are being recognized in

The fusion of satellite and UAV data: simulation of high spatial resolution band

NASA Astrophysics Data System (ADS)

Jenerowicz, Agnieszka; Siok, Katarzyna; Woroszkiewicz, Malgorzata; Orych, Agata

2017-10-01

Remote sensing techniques used in the precision agriculture and farming that apply imagery data obtained with sensors mounted on UAV platforms became more popular in the last few years due to the availability of low- cost UAV platforms and low- cost sensors. Data obtained from low altitudes with low- cost sensors can be characterised by high spatial and radiometric resolution but quite low spectral resolution, therefore the application of imagery data obtained with such technology is quite limited and can be used only for the basic land cover classification. To enrich the spectral resolution of imagery data acquired with low- cost sensors from low altitudes, the authors proposed the fusion of RGB data obtained with UAV platform with multispectral satellite imagery. The fusion is based on the pansharpening process, that aims to integrate the spatial details of the high-resolution panchromatic image with the spectral information of lower resolution multispectral or hyperspectral imagery to obtain multispectral or hyperspectral images with high spatial resolution. The key of pansharpening is to properly estimate the missing spatial details of multispectral images while preserving their spectral properties. In the research, the authors presented the fusion of RGB images (with high spatial resolution) obtained with sensors mounted on low- cost UAV platforms and multispectral satellite imagery with satellite sensors, i.e. Landsat 8 OLI. To perform the fusion of UAV data with satellite imagery, the simulation of the panchromatic bands from RGB data based on the spectral channels linear combination, was conducted. Next, for simulated bands and multispectral satellite images, the Gram-Schmidt pansharpening method was applied. As a result of the fusion, the authors obtained several multispectral images with very high spatial resolution and then analysed the spatial and spectral accuracies of processed images.

Long Corridor Survey for High Voltage Power Lines Design Using Uav

NASA Astrophysics Data System (ADS)

Skarlatos, D.; Vamvakousis, V.

2017-11-01

The term Unmanned Aerial Vehicle (UAV) is often directly associated with the armed forces due to their widely-criticized use of such vehicles on the modern battlefield. However, with the advancement of UAV technology, the acquisition and operational cost of small civilian UAV have reduced while their functionalities have increased. Therefore, a wide variety of new civilian applications have emerged. Mapping industry has been benefited as affordable UAV can partially replace traditional platforms, such as helicopters and small aircrafts, for low altitude photography acquisition. Although relatively new to the industry, the use of UAV is rapidly commercialized and they are expected to have a sizeable impact on the mapping industry in the coming years. The aim of this work was to test the use of a low-cost UAV for orthophoto production and Digital Surface Model (DSM) creation, to be used for the design of a new 23km high voltage line of Electricity Authority of Cyprus.

Advanced Broadband Links for TIER III UAV Data Communication

NASA Astrophysics Data System (ADS)

Griethe, Wolfgang; Gregory, Mark; Heine, Frank; Kampfner, Hartmut

2011-08-01

Unmanned Aeronautical Vehicle (UAV) are getting more and more importance because of their prominent role as national reconnaissance systems, for disaster monitoring, and environmental mapping. However, the existence of reliable and robust data links are indispensable for Unmanned Aircraft System (UAS) missions. In particular for Beyond Line-Of-Sight operations (BLOS) of Tier III UAVs, satellite data links are a key element since extensive sensor data have to be transmitted preferably in real-time or near real-time.The paper demonstrates that the continuously increasing number of UAS and the intensified use of high resolution sensors will reveal RF-bandwidth as a limitating factor in the communication chain of Tier III UAVs. The RF-bandwidth gap can be partly closed by use of high-order modulation, of course, but much more progress in terms of bandwidth allocation can be achieved by using optical transmission technology. Consequently, the paper underlines that meanwhile this technology has been sufficiently verified in space, and shows that optical links are suited as well for broadband communications of Tier III UAVs. Moreover, the advantages of LaserCom in UAV scenarios and its importance for Network Centric Warfare (NCW) as well as for Command, Control, Communications, Computers, Intelligens, Surveillance, and Reconnaissance (C4ISR) are emphasized. Numerous practical topics and design requirements, relevant for the establishment of optical links onboard of Tier III UAVs, are discussed.

Evaluating the accuracy of orthophotos and 3D models from UAV photogrammetry

NASA Astrophysics Data System (ADS)

Julge, Kalev; Ellmann, Artu

2015-04-01

Rapid development of unmanned aerial vehicles (UAV) in recent years has made their use for various applications more feasible. This contribution evaluates the accuracy and quality of different UAV remote sensing products (i.e. orthorectified image, point cloud and 3D model). Two different autonomous fixed wing UAV systems were used to collect the aerial photographs. One is a mass-produced commercial UAV system, the other is a similar state-of-the-art UAV system. Three different study areas with varying sizes and characteristics (including urban areas, forests, fields, etc.) were surveyed. The UAV point clouds, 3D models and orthophotos were generated with three different commercial and free-ware software. The performance of each of these was evaluated. The effect of flying height on the accuracy of the results was explored, as well as the optimum number and placement of ground control points. Also the achieved results, when the only georeferencing data originates from the UAV system's on-board GNSS and inertial measurement unit, are investigated. Problems regarding the alignment of certain types of aerial photos (e.g. captured over forested areas) are discussed. The quality and accuracy of UAV photogrammetry products are evaluated by comparing them with control measurements made with GNSS-measurements on the ground, as well as high-resolution airborne laser scanning data and other available orthophotos (e.g. those acquired for large scale national mapping). Vertical comparisons are made on surfaces that have remained unchanged in all campaigns, e.g. paved roads. Planar comparisons are performed by control surveys of objects that are clearly identifiable on orthophotos. The statistics of these differences are used to evaluate the accuracy of UAV remote sensing. Some recommendations are given on how to conduct UAV mapping campaigns cost-effectively and with minimal time-consumption while still ensuring the quality and accuracy of the UAV data products. Also the

a Three-Dimensional Simulation and Visualization System for Uav Photogrammetry

NASA Astrophysics Data System (ADS)

Liang, Y.; Qu, Y.; Cui, T.

2017-08-01

Nowadays UAVs has been widely used for large-scale surveying and mapping. Compared with manned aircraft, UAVs are more cost-effective and responsive. However, UAVs are usually more sensitive to wind condition, which greatly influences their positions and orientations. The flight height of a UAV is relative low, and the relief of the terrain may result in serious occlusions. Moreover, the observations acquired by the Position and Orientation System (POS) are usually less accurate than those acquired in manned aerial photogrammetry. All of these factors bring in uncertainties to UAV photogrammetry. To investigate these uncertainties, a three-dimensional simulation and visualization system has been developed. The system is demonstrated with flight plan evaluation, image matching, POS-supported direct georeferencing, and ortho-mosaicing. Experimental results show that the presented system is effective for flight plan evaluation. The generated image pairs are accurate and false matches can be effectively filtered. The presented system dynamically visualizes the results of direct georeferencing in three-dimensions, which is informative and effective for real-time target tracking and positioning. The dynamically generated orthomosaic can be used in emergency applications. The presented system has also been used for teaching theories and applications of UAV photogrammetry.

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs.

PubMed

Wang, Xiaoliang; Jiang, Peng; Li, Deshi; Sun, Tao

2017-09-19

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region.

UAV based 3D digital surface model to estimate paleolandscape in high mountainous environment

NASA Astrophysics Data System (ADS)

Mészáros, János; Árvai, Mátyás; Kohán, Balázs; Deák, Márton; Nagy, Balázs

2016-04-01

Our method to present current state of a peat bog was focused on the possible use of a UAV-system and later Structure-from-motion algorithms as processing technique. The peat bog site is located on the Vinderel Plateau, Farcǎu Massif, Maramures Mountains (Romania). The peat bog (1530 m a.s.l., N47°54'11", E24°26'37") lies below Rugasu ridge (c. 1820 m a.s.l.) and the locality serves as a conservation area for fallen down coniferous trees. Peat deposits were formed in a landslide concavity on the western slope of Farcǎu Massif. Nowadays the site is surrounded by a completely deforested landscape, and Farcǎu Massif lies above the depressed treeline. The peat bog has an extraordinary geomorphological situation, because a gully reached the bog and drained the water. In the recent past sedimentological and dendrochronological researches have been initiated. However, an accurate 3D digital surface model also needed for a complex paleoenvironmental research. Last autumn the bog and its surroundings were finally surveyed by a multirotor UAV developed in-house based on an open-source flight management unit and its firmware. During this survey a lightweight action camera (mainly to decrease payload weight) was used to take aerial photographs. While our quadcopter is capable to fly automatically on a predefined flight route, several over- and sidelapping flight lines were generated prior to the actual survey on the ground using a control software running on a notebook. Despite those precautions, limited number of batteries and severe weather affected our final flights, resulting a reduced surveyed area around peat bog. Later, during the processing we looked for a reliable tool which powerful enough to process more than 500 photos taken during flights. After testing several software Agisoft PhotoScan was used to create 3D point cloud and mesh about bog and its environment. Due to large number of photographs PhotoScan had to be configured for network processing to get

Filtering Methods for Error Reduction in Spacecraft Attitude Estimation Using Quaternion Star Trackers

NASA Technical Reports Server (NTRS)

Calhoun, Philip C.; Sedlak, Joseph E.; Superfin, Emil

2011-01-01

Precision attitude determination for recent and planned space missions typically includes quaternion star trackers (ST) and a three-axis inertial reference unit (IRU). Sensor selection is based on estimates of knowledge accuracy attainable from a Kalman filter (KF), which provides the optimal solution for the case of linear dynamics with measurement and process errors characterized by random Gaussian noise with white spectrum. Non-Gaussian systematic errors in quaternion STs are often quite large and have an unpredictable time-varying nature, particularly when used in non-inertial pointing applications. Two filtering methods are proposed to reduce the attitude estimation error resulting from ST systematic errors, 1) extended Kalman filter (EKF) augmented with Markov states, 2) Unscented Kalman filter (UKF) with a periodic measurement model. Realistic assessments of the attitude estimation performance gains are demonstrated with both simulation and flight telemetry data from the Lunar Reconnaissance Orbiter.

UAV Flight Control Using Distributed Actuation and Sensing

NASA Technical Reports Server (NTRS)

Barnwell, William G.; Heinzen, Stearns N.; Hall, Charles E., Jr.; Chokani, Ndaona; Raney, David L. (Technical Monitor)

2003-01-01

An array of effectors and sensors has been designed, tested and implemented on a Blended Wing Body Uninhabited Aerial Vehicle (UAV). This UAV is modified to serve as a flying, controls research, testbed. This effectorhensor array provides for the dynamic vehicle testing of controller designs and the study of decentralized control techniques. Each wing of the UAV is equipped with 12 distributed effectors that comprise a segmented array of independently actuated, contoured control surfaces. A single pressure sensor is installed near the base of each effector to provide a measure of deflections of the effectors. The UAV wings were tested in the North Carolina State University Subsonic Wind Tunnel and the pressure distribution that result from the deflections of the effectors are characterized. The results of the experiments are used to develop a simple, but accurate, prediction method, such that for any arrangement of the effector array the corresponding pressure distribution can be determined. Numerical analysis using the panel code CMARC verifies this prediction method.

Towards FAA Certification of UAVs

NASA Technical Reports Server (NTRS)

Nelson, Stacy

2003-01-01

As of June 30, 2003, all Unmanned Aerial Vehicles (UAV), no matter how small, must adhere to the same FAA regulations as human-piloted aircraft. These regulations include certification for flying in controlled airspace and certification of flight software based on RTCA DO-178B. This paper provides an overview of the steps necessary to obtain certification, as well as a discussion about the challenges UAV's face when trying to meet these requirements. It is divided into two parts: 1) Certifications for Flying in Controlled Airspace; 2) Certification of Flight Software per RTCA DO-178B.

Real-time target tracking and locating system for UAV

NASA Astrophysics Data System (ADS)

Zhang, Chao; Tang, Linbo; Fu, Huiquan; Li, Maowen

2017-07-01

In order to achieve real-time target tracking and locating for UAV, a reliable processing system is built on the embedded platform. Firstly, the video image is acquired in real time by the photovoltaic system on the UAV. When the target information is known, KCF tracking algorithm is adopted to track the target. Then, the servo is controlled to rotate with the target, when the target is in the center of the image, the laser ranging module is opened to obtain the distance between the UAV and the target. Finally, to combine with UAV flight parameters obtained by BeiDou navigation system, through the target location algorithm to calculate the geodetic coordinates of the target. The results show that the system is stable for real-time tracking of targets and positioning.

Extended Kalman filter for attitude estimation of the earth radiation budget satellite

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack Y.

1989-01-01

The design and testing of an Extended Kalman Filter (EKF) for ground attitude determination, misalignment estimation and sensor calibration of the Earth Radiation Budget Satellite (ERBS) are described. Attitude is represented by the quaternion of rotation and the attitude estimation error is defined as an additive error. Quaternion normalization is used for increasing the convergence rate and for minimizing the need for filter tuning. The development of the filter dynamic model, the gyro error model and the measurement models of the Sun sensors, the IR horizon scanner and the magnetometers which are used to generate vector measurements are also presented. The filter is applied to real data transmitted by ERBS sensors. Results are presented and analyzed and the EKF advantages as well as sensitivities are discussed. On the whole the filter meets the expected synergism, accuracy and robustness.

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time

PubMed Central

Avellar, Gustavo S. C.; Pereira, Guilherme A. S.; Pimenta, Luciano C. A.; Iscold, Paulo

2015-01-01

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem’s (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles’ maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs. PMID:26540055

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

PubMed

Avellar, Gustavo S C; Pereira, Guilherme A S; Pimenta, Luciano C A; Iscold, Paulo

2015-11-02

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem's (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles' maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

UAV visual signature suppression via adaptive materials

NASA Astrophysics Data System (ADS)

Barrett, Ron; Melkert, Joris

2005-05-01

Visual signature suppression (VSS) methods for several classes of aircraft from WWII on are examined and historically summarized. This study shows that for some classes of uninhabited aerial vehicles (UAVs), primary mission threats do not stem from infrared or radar signatures, but from the amount that an aircraft visually stands out against the sky. The paper shows that such visual mismatch can often jeopardize mission success and/or induce the destruction of the entire aircraft. A psycho-physioptical study was conducted to establish the definition and benchmarks of a Visual Cross Section (VCS) for airborne objects. This study was centered on combining the effects of size, shape, color and luminosity or effective illumance (EI) of a given aircraft to arrive at a VCS. A series of tests were conducted with a 6.6ft (2m) UAV which was fitted with optically adaptive electroluminescent sheets at altitudes of up to 1000 ft (300m). It was shown that with proper tailoring of the color and luminosity, the VCS of the aircraft dropped from more than 4,200cm2 to less than 1.8cm2 at 100m (the observed lower limit of the 20-20 human eye in this study). In laypersons terms this indicated that the UAV essentially "disappeared". This study concludes with an assessment of the weight and volume impact of such a Visual Suppression System (VSS) on the UAV, showing that VCS levels on this class UAV can be suppressed to below 1.8cm2 for aircraft gross weight penalties of only 9.8%.

Robust all-source positioning of UAVs based on belief propagation

NASA Astrophysics Data System (ADS)

Chen, Xi; Gao, Wenyun; Wang, Jiabo

2013-12-01

For unmanned air vehicles (UAVs) to survive hostile operational environments, it is always preferable to utilize all wireless positioning sources available to fuse a robust position. While belief propagation is a well-established method for all source data fusion, it is not an easy job to handle all the mathematics therein. In this work, a comprehensive mathematical framework for belief propagation-based all-source positioning of UAVs is developed, taking wireless sources including Global Navigation Satellite Systems (GNSS) space vehicles, peer UAVs, ground control stations, and signal of opportunities. Based on the mathematical framework, a positioning algorithm named Belief propagation-based Opportunistic Positioning of UAVs (BOPU) is proposed, with an unscented particle filter for Bayesian approximation. The robustness of the proposed BOPU is evaluated by a fictitious scenario that a group of formation flying UAVs encounter GNSS countermeasures en route. Four different configurations of measurements availability are simulated. The results show that the performance of BOPU varies only slightly with different measurements availability.

The use of UAVs for monitoring land degradation

NASA Astrophysics Data System (ADS)

Themistocleous, Kyriacos

2017-10-01

Land degradation is one of the causes of desertification of drylands in the Mediterranean. UAVs can be used to monitor and document the various variables that cause desertification in drylands, including overgrazing, aridity, vegetation loss, etc. This paper examines the use of UAVs and accompanying sensors to monitor overgrazing, vegetation stress and aridity in the study area. UAV images can be used to generate digital elevation models (DEMs) to examine the changes in microtopography as well as ortho-photos were used to detect changes in vegetation patterns. The combined data of the digital elevation models and the orthophotos can be used to identify the mechanisms for desertification in the study area.

A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification

PubMed Central

Kumar, G. Ajay; Patil, Ashok Kumar; Patil, Rekha; Park, Seong Sill; Chai, Young Ho

2017-01-01

Mapping the environment of a vehicle and localizing a vehicle within that unknown environment are complex issues. Although many approaches based on various types of sensory inputs and computational concepts have been successfully utilized for ground robot localization, there is difficulty in localizing an unmanned aerial vehicle (UAV) due to variation in altitude and motion dynamics. This paper proposes a robust and efficient indoor mapping and localization solution for a UAV integrated with low-cost Light Detection and Ranging (LiDAR) and Inertial Measurement Unit (IMU) sensors. Considering the advantage of the typical geometric structure of indoor environments, the planar position of UAVs can be efficiently calculated from a point-to-point scan matching algorithm using measurements from a horizontally scanning primary LiDAR. The altitude of the UAV with respect to the floor can be estimated accurately using a vertically scanning secondary LiDAR scanner, which is mounted orthogonally to the primary LiDAR. Furthermore, a Kalman filter is used to derive the 3D position by fusing primary and secondary LiDAR data. Additionally, this work presents a novel method for its application in the real-time classification of a pipeline in an indoor map by integrating the proposed navigation approach. Classification of the pipeline is based on the pipe radius estimation considering the region of interest (ROI) and the typical angle. The ROI is selected by finding the nearest neighbors of the selected seed point in the pipeline point cloud, and the typical angle is estimated with the directional histogram. Experimental results are provided to determine the feasibility of the proposed navigation system and its integration with real-time application in industrial plant engineering. PMID:28574474

Evaluation of low- and medium-cost IMUs for airborne gravimetry with UAVs

NASA Astrophysics Data System (ADS)

Deurloo, R. A.; Bastos, M. L.; Geng, Y.; Yan, W.

2011-12-01

The use of Unmanned Aerial Vehicles (UAVs) has increased in a large number of fields and is proving to be a good alternative to aerial surveys with traditional (manned) aircraft. In the scope of the PITVANT (Projecto de Investigação e Tecnologia em Veículos Aéreos Não-Tripulados) project, a research project funded by the Portuguese Ministry of Defence that aims at the development and demonstration of tools and technologies for UAVs, the Astronomical Observatory of the Faculty of Sciences of the University of Porto is investigating the use of UAVs for regional airborne gravimetry. The goal is to implement a so-called strapdown gravimetry system, based on the integrated use of GNSS and a low- to medium-cost IMU (Inertial Measurement Unit) that can be setup on board the UAVs developed within PITVANT. Two basic approaches exist in strapdown GNSS/IMU gravimetry: - to compute gravity disturbances directly from the combination of GNSS derived accelerations with accelerations measured by the IMU (the accelerometry approach); - to estimate the gravity disturbances as part of an inertial navigation solution using an (extended) Kalman filter (the inertial navigation approach). Because of the limitation of low- to medium-cost inertial systems the latter approach was used here. This method has proven to be effective in previous studies with this type of GNSS/IMU systems. To define the final system architecture, the performance of several different inertial systems was recently tested during an airborne survey with a regular aircraft, i.e. a CASA C212 from the Portuguese Air Force (PAF). Among the systems on board were a medium-cost Litton LN-200 and a low-cost Crossbow AHRS440, combined with a single GNSS receiver. Different Kalman filter configurations and GNSS processing options were investigated for each of the systems. The main goal was to assess the limits of the integrated GNSS/IMU systems to sense the gravity field (scalar gravimetry) and to evaluate their use and

An evaluation of a UAV guidance system with consumer grade GPS receivers

NASA Astrophysics Data System (ADS)

Rosenberg, Abigail Stella

Remote sensing has been demonstrated an important tool in agricultural and natural resource management and research applications, however there are limitations that exist with traditional platforms (i.e., hand held sensors, linear moves, vehicle mounted, airplanes, remotely piloted vehicles (RPVs), unmanned aerial vehicles (UAVs) and satellites). Rapid technological advances in electronics, computers, software applications, and the aerospace industry have dramatically reduced the cost and increased the availability of remote sensing technologies. Remote sensing imagery vary in spectral, spatial, and temporal resolutions and are available from numerous providers. Appendix A presented results of a test project that acquired high-resolution aerial photography with a RPV to map the boundary of a 0.42 km2 fire area. The project mapped the boundaries of the fire area from a mosaic of the aerial images collected and compared this with ground-based measurements. The project achieved a 92.4% correlation between the aerial assessment and the ground truth data. Appendix B used multi-objective analysis to quantitatively assess the tradeoffs between different sensor platform attributes to identify the best overall technology. Experts were surveyed to identify the best overall technology at three different pixel sizes. Appendix C evaluated the positional accuracy of a relatively low cost UAV designed for high resolution remote sensing of small areas in order to determine the positional accuracy of sensor readings. The study evaluated the accuracy and uncertainty of a UAV flight route with respect to the programmed waypoints and of the UAV's GPS position, respectively. In addition, the potential displacement of sensor data was evaluated based on (1) GPS measurements on board the aircraft and (2) the autopilot's circuit board with 3-axis gyros and accelerometers (i.e., roll, pitch, and yaw). The accuracies were estimated based on a 95% confidence interval or similar methods. The

UAV-based Radar Sounding of Antarctic Ice

NASA Astrophysics Data System (ADS)

Leuschen, Carl; Yan, Jie-Bang; Mahmood, Ali; Rodriguez-Morales, Fernando; Hale, Rick; Camps-Raga, Bruno; Metz, Lynsey; Wang, Zongbo; Paden, John; Bowman, Alec; Keshmiri, Shahriar; Gogineni, Sivaprasad

2014-05-01

We developed a compact radar for use on a small UAV to conduct measurements over the ice sheets in Greenland and Antarctica. It operates at center frequencies of 14 and 35 MHz with bandwidths of 1 MHz and 4 MHz, respectively. The radar weighs about 2 kgs and is housed in a box with dimensions of 20.3 cm x 15.2 cm x 13.2 cm. It transmits a signal power of 100 W at a pulse repletion frequency of 10 kHz and requires average power of about 20 W. The antennas for operating the radar are integrated into the wings and airframe of a small UAV with a wingspan of 5.3 m. We selected the frequencies of 14 and 35 MHz based on previous successful soundings of temperate ice in Alaska with a 12.5 MHz impulse radar [Arcone, 2002] and temperate glaciers in Patagonia with a 30 MHz monocycle radar [Blindow et al., 2012]. We developed the radar-equipped UAV to perform surveys over a 2-D grid, which allows us to synthesize a large two-dimensional aperture and obtain fine resolution in both the along- and cross-track directions. Low-frequency, high-sensitivity radars with 2-D aperture synthesis capability are needed to overcome the surface and volume scatter that masks weak echoes from the ice-bed interface of fast-flowing glaciers. We collected data with the radar-equipped UAV on sub-glacial ice near Lake Whillans at both 14 and 35 MHz. We acquired data to evaluate the concept of 2-D aperture synthesis and successfully demonstrated the first successful sounding of ice with a radar on an UAV. We are planning to build multiple radar-equipped UAVs for collecting fine-resolution data near the grounding lines of fast-flowing glaciers. In this presentation we will provide a brief overview of the radar and UAV, as well as present results obtained at both 14 and 35 MHz. Arcone, S. 2002. Airborne-radar stratigraphy and electrical structure of temperate firn: Bagley Ice Field, Alaska, U.S.A. Journal of Glaciology, 48, 317-334. Blindow, N., C. Salat, and G. Casassa. 2012. Airborne GPR sounding of

Developing stochastic model of thrust and flight dynamics for small UAVs

NASA Astrophysics Data System (ADS)

Tjhai, Chandra

This thesis presents a stochastic thrust model and aerodynamic model for small propeller driven UAVs whose power plant is a small electric motor. First a model which relates thrust generated by a small propeller driven electric motor as a function of throttle setting and commanded engine RPM is developed. A perturbation of this model is then used to relate the uncertainty in throttle and engine RPM commanded to the error in the predicted thrust. Such a stochastic model is indispensable in the design of state estimation and control systems for UAVs where the performance requirements of the systems are specied in stochastic terms. It is shown that thrust prediction models for small UAVs are not a simple, explicit functions relating throttle input and RPM command to thrust generated. Rather they are non-linear, iterative procedures which depend on a geometric description of the propeller and mathematical model of the motor. A detailed derivation of the iterative procedure is presented and the impact of errors which arise from inaccurate propeller and motor descriptions are discussed. Validation results from a series of wind tunnel tests are presented. The results show a favorable statistical agreement between the thrust uncertainty predicted by the model and the errors measured in the wind tunnel. The uncertainty model of aircraft aerodynamic coefficients developed based on wind tunnel experiment will be discussed at the end of this thesis.

Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs

PubMed Central

Jiang, Peng; Li, Deshi; Sun, Tao

2017-01-01

Unmanned Aerial Vehicles (UAVs) play an important role in applications such as data collection and target reconnaissance. An accurate and optimal path can effectively increase the mission success rate in the case of small UAVs. Although path planning for UAVs is similar to that for traditional mobile robots, the special kinematic characteristics of UAVs (such as their minimum turning radius) have not been taken into account in previous studies. In this paper, we propose a locally-adjustable, continuous-curvature, bounded path-planning algorithm for fixed-wing UAVs. To deal with the curvature discontinuity problem, an optimal interpolation algorithm and a key-point shift algorithm are proposed based on the derivation of a curvature continuity condition. To meet the upper bound for curvature and to render the curvature extrema controllable, a local replanning scheme is designed by combining arcs and Bezier curves with monotonic curvature. In particular, a path transition mechanism is built for the replanning phase using minimum curvature circles for a planning philosophy. Numerical results demonstrate that the analytical planning algorithm can effectively generate continuous-curvature paths, while satisfying the curvature upper bound constraint and allowing UAVs to pass through all predefined waypoints in the desired mission region. PMID:28925960

Lessons Learned from NASA UAV Science Demonstration Program Missions

NASA Technical Reports Server (NTRS)

Wegener, Steven S.; Schoenung, Susan M.

2003-01-01

During the summer of 2002, two airborne missions were flown as part of a NASA Earth Science Enterprise program to demonstrate the use of uninhabited aerial vehicles (UAVs) to perform earth science. One mission, the Altus Cumulus Electrification Study (ACES), successfully measured lightning storms in the vicinity of Key West, Florida, during storm season using a high-altitude Altus(TM) UAV. In the other, a solar-powered UAV, the Pathfinder Plus, flew a high-resolution imaging mission over coffee fields in Kauai, Hawaii, to help guide the harvest.

Comprehensive UAV agricultural remote-sensing research at Texas A M University

NASA Astrophysics Data System (ADS)

Thomasson, J. Alex; Shi, Yeyin; Olsenholler, Jeffrey; Valasek, John; Murray, Seth C.; Bishop, Michael P.

2016-05-01

Unmanned aerial vehicles (UAVs) have advantages over manned vehicles for agricultural remote sensing. Flying UAVs is less expensive, is more flexible in scheduling, enables lower altitudes, uses lower speeds, and provides better spatial resolution for imaging. The main disadvantage is that, at lower altitudes and speeds, only small areas can be imaged. However, on large farms with contiguous fields, high-quality images can be collected regularly by using UAVs with appropriate sensing technologies that enable high-quality image mosaics to be created with sufficient metadata and ground-control points. In the United States, rules governing the use of aircraft are promulgated and enforced by the Federal Aviation Administration (FAA), and rules governing UAVs are currently in flux. Operators must apply for appropriate permissions to fly UAVs. In the summer of 2015 Texas A&M University's agricultural research agency, Texas A&M AgriLife Research, embarked on a comprehensive program of remote sensing with UAVs at its 568-ha Brazos Bottom Research Farm. This farm is made up of numerous fields where various crops are grown in plots or complete fields. The crops include cotton, corn, sorghum, and wheat. After gaining FAA permission to fly at the farm, the research team used multiple fixed-wing and rotary-wing UAVs along with various sensors to collect images over all parts of the farm at least once per week. This article reports on details of flight operations and sensing and analysis protocols, and it includes some lessons learned in the process of developing a UAV remote-sensing effort of this sort.

Experiment on Uav Photogrammetry and Terrestrial Laser Scanning for Ict-Integrated Construction

NASA Astrophysics Data System (ADS)

Takahashi, N.; Wakutsu, R.; Kato, T.; Wakaizumi, T.; Ooishi, T.; Matsuoka, R.

2017-08-01

In the 2016 fiscal year the Ministry of Land, Infrastructure, Transport and Tourism of Japan started a program integrating construction and ICT in earthwork and concrete placing. The new program named "i-Construction" focusing on productivity improvement adopts such new technologies as UAV photogrammetry and TLS. We report a field experiment to investigate whether the procedures of UAV photogrammetry and TLS following the standards for "i-Construction" are feasible or not. In the experiment we measured an embankment of about 80 metres by 160 metres immediately after earthwork was done on the embankment. We used two sets of UAV and camera in the experiment. One is a larger UAV enRoute Zion QC730 and its onboard camera Sony α6000. The other is a smaller UAV DJI Phantom 4 and its dedicated onboard camera. Moreover, we used a terrestrial laser scanner FARO Focus3D X330 based on the phase shift principle. The experiment results indicate that the procedures of UAV photogrammetry using a QC730 with an α6000 and TLS using a Focus3D X330 following the standards for "i-Construction" would be feasible. Furthermore, the experiment results show that UAV photogrammetry using a lower price UAV Phantom 4 was unable to satisfy the accuracy requirement for "i-Construction." The cause of the low accuracy by Phantom 4 is under investigation. We also found that the difference of image resolution on the ground would not have a great influence on the measurement accuracy in UAV photogrammetry.

Optimal estimation for the satellite attitude using star tracker measurements

NASA Technical Reports Server (NTRS)

Lo, J. T.-H.

1986-01-01

An optimal estimation scheme is presented, which determines the satellite attitude using the gyro readings and the star tracker measurements of a commonly used satellite attitude measuring unit. The scheme is mainly based on the exponential Fourier densities that have the desirable closure property under conditioning. By updating a finite and fixed number of parameters, the conditional probability density, which is an exponential Fourier density, is recursively determined. Simulation results indicate that the scheme is more accurate and robust than extended Kalman filtering. It is believed that this approach is applicable to many other attitude measuring units. As no linearization and approximation are necessary in the approach, it is ideal for systems involving high levels of randomness and/or low levels of observability and systems for which accuracy is of overriding importance.

Spectral Imaging from Uavs Under Varying Illumination Conditions

NASA Astrophysics Data System (ADS)

Hakala, T.; Honkavaara, E.; Saari, H.; Mäkynen, J.; Kaivosoja, J.; Pesonen, L.; Pölönen, I.

2013-08-01

Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. For applications requiring aerial images, a simple consumer camera provides acceptable data. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. These images can be assembled in spectral data cubes with stereoscopic overlaps. On field the weather conditions vary and the UAV operator often has to decide between flight in sub optimal conditions and no flight. Our objective was to investigate methods for quantitative radiometric processing of images taken under varying illumination conditions, thus expanding the range of weather conditions during which successful imaging flights can be made. A new method that is based on insitu measurement of irradiance either in UAV platform or in ground was developed. We tested the methods in a precision agriculture application using realistic data collected in difficult illumination conditions. Internal homogeneity of the original image data (average coefficient of variation in overlapping images) was 0.14-0.18. In the corrected data, the homogeneity was 0.10-0.12 with a correction based on broadband irradiance measured in UAV, 0.07-0.09 with a correction based on spectral irradiance measurement on ground, and 0.05-0.08 with a radiometric block adjustment based on image data. Our results were very promising, indicating that quantitative UAV based remote sensing could be operational in diverse conditions, which is prerequisite for many environmental remote sensing applications.

Precise Positioning of Uavs - Dealing with Challenging Rtk-Gps Measurement Conditions during Automated Uav Flights

NASA Astrophysics Data System (ADS)

Zimmermann, F.; Eling, C.; Klingbeil, L.; Kuhlmann, H.

2017-08-01

For some years now, UAVs (unmanned aerial vehicles) are commonly used for different mobile mapping applications, such as in the fields of surveying, mining or archeology. To improve the efficiency of these applications an automation of the flight as well as the processing of the collected data is currently aimed at. One precondition for an automated mapping with UAVs is that the georeferencing is performed directly with cm-accuracies or better. Usually, a cm-accurate direct positioning of UAVs is based on an onboard multi-sensor system, which consists of an RTK-capable (real-time kinematic) GPS (global positioning system) receiver and additional sensors (e.g. inertial sensors). In this case, the absolute positioning accuracy essentially depends on the local GPS measurement conditions. Especially during mobile mapping applications in urban areas, these conditions can be very challenging, due to a satellite shadowing, non-line-of sight receptions, signal diffraction or multipath effects. In this paper, two straightforward and easy to implement strategies will be described and analyzed, which improve the direct positioning accuracies for UAV-based mapping and surveying applications under challenging GPS measurement conditions. Based on a 3D model of the surrounding buildings and vegetation in the area of interest, a GPS geometry map is determined, which can be integrated in the flight planning process, to avoid GPS challenging environments as far as possible. If these challenging environments cannot be avoided, the GPS positioning solution is improved by using obstruction adaptive elevation masks, to mitigate systematic GPS errors in the RTK-GPS positioning. Simulations and results of field tests demonstrate the profit of both strategies.

Guidance and control for an autonomous soaring UAV

NASA Technical Reports Server (NTRS)

Allen, Michael J. (Inventor)

2008-01-01

The present invention provides a practical method for UAVs to take advantage of thermals in a manner similar to piloted aircrafts and soaring birds. In general, the invention is a method for a UAV to autonomously locate a thermal and be guided to the thermal to greatly improve range and endurance of the aircraft.

Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

NASA Astrophysics Data System (ADS)

Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

2018-04-01

Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

Magnetometer-Only Attitude and Rate Estimates for Spinning Spacecraft

NASA Technical Reports Server (NTRS)

Challa, M.; Natanson, G.; Ottenstein, N.

2000-01-01

A deterministic algorithm and a Kalman filter for gyroless spacecraft are used independently to estimate the three-axis attitude and rates of rapidly spinning spacecraft using only magnetometer data. In-flight data from the Wide-Field Infrared Explorer (WIRE) during its tumble, and the Fast Auroral Snapshot Explorer (FAST) during its nominal mission mode are used to show that the algorithms can successfully estimate the above in spite of the high rates. Results using simulated data are used to illustrate the importance of accurate and frequent data.

Cost and effectiveness analysis on unmanned aerial vehicle (UAV) use at border security

NASA Astrophysics Data System (ADS)

Yilmaz, Bahadır.

2013-06-01

Drones and Remotely Piloted Vehicles are types of Unmanned Aerial Vehicles. UAVs began to be used with the war of Vietnam, they had a great interest when Israel used them in Bekaa Valley Operations of 1982. UAVs have been used by different countries with different aims with the help of emerging technology and investments. In this article, in the context of areas of UAV usage in national security, benefits and disadvantages of UAVs are put forward. Particularly, it has been evaluated on the basis of cost-effectiveness by focusing the use of UAV in the border security. UAVs have been studied by taking cost analysis, procurement and operational costs into consideration. Analysis of effectiveness has been done with illegal passages of people and drugs from flight times of UAVs. Although the procurement cost of the medium-level UAVs is low, its operational costs are high. For this reason, the idea of less costly alternative systems have been revealed for the border security. As the costs are reduced to acceptable level involving national security and border security in future with high-technology products in their structure, it will continue to be used in an increasing proportion.

Numerical RCS and micro-Doppler investigations of a consumer UAV

NASA Astrophysics Data System (ADS)

Schröder, Arne; Aulenbacher, Uwe; Renker, Matthias; Böniger, Urs; Oechslin, Roland; Murk, Axel; Wellig, Peter

2016-10-01

This contribution gives an overview of recent investigations regarding the detection of a consumer market unmanned aerial vehicles (UAV). The steadily increasing number of such drones gives rise to the threat of UAVs interfering civil air traffic. Technologies for monitoring UAVs which are flying in restricted air space, i. e. close to airports or even over airports, are desperately needed. One promising way for tracking drones is to employ radar systems. For the detection and classification of UAVs, the knowledge about their radar cross section (RCS) and micro-Doppler signature is of particular importance. We have carried out numerical and experimental studies of the RCS and the micro-Doppler of an example commercial drone in order to study its detectability with radar systems.

Common Operating Picture: UAV Security Study

NASA Technical Reports Server (NTRS)

2004-01-01

This initial communication security study is a top-level assessment of basic security issues related to the operation of Unmanned Aerial Vehicles (UAVs) in the National Airspace System (NAS). Security considerations will include information relating to the use of International Civil Aviation Organization (ICAO) Aeronautical Telecommunications Network (ATN) protocols and applications identifying their maturity, as well as the use of IPV4 and a version of mobile IPV6. The purpose of this assessment is to provide an initial analysis of the security implications of introducing UAVs into the NAS.

Survey on the novel hybrid aquatic-aerial amphibious aircraft: Aquatic unmanned aerial vehicle (AquaUAV)

NASA Astrophysics Data System (ADS)

Yang, Xingbang; Wang, Tianmiao; Liang, Jianhong; Yao, Guocai; Liu, Miao

2015-04-01

The aquatic unmanned aerial vehicle (AquaUAV), a kind of vehicle that can operate both in the air and the water, has been regarded as a new breakthrough to broaden the application scenario of UAV. Wide application prospects in military and civil field are more than bright, therefore many institutions have focused on the development of such a vehicle. However, due to the significant difference of the physical properties between the air and the water, it is rather difficult to design a fully-featured AquaUAV. Until now, majority of partially-featured AquaUAVs have been developed and used to verify the feasibility of an aquatic-aerial vehicle. In the present work, we classify the current partially-featured AquaUAV into three categories from the scope of the whole UAV field, i.e., the seaplane UAV, the submarine-launched UAV, and the submersible UAV. Then the recent advancements and common characteristics of the three kinds of AquaUAVs are reviewed in detail respectively. Then the applications of bionics in the design of AquaUAV, the transition mode between the air and the water, the morphing wing structure for air-water adaptation, and the power source and the propulsion type are summarized and discussed. The tradeoff analyses for different transition methods between the air and the water are presented. Furthermore, it indicates that applying the bionics into the design and development of the AquaUAV will be essential and significant. Finally, the significant technical challenges for the AquaUAV to change from a conception to a practical prototype are indicated.

RAVEN-2: Around-The-World UAV Project

DTIC Science & Technology

2003-09-02

RAVEN-2 Around-The-World UAV Project By Chris Burleigh MSc., C.Eng., MRAeS. Black Art Composites Ltd., UK INTRODUCTION The Raven around-the-world UAV...NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Black Art Composites Ltd., UK 8. PERFORMING...Consultant, Black Art Composites Limited, UK. Chris Burleigh entered the aerospace industry in 1973 as an apprentice with Hawker Siddeley Aviation Ltd

Thermocouple-based Temperature Sensing System for Chemical Cell Inside Micro UAV Device

NASA Astrophysics Data System (ADS)

Han, Yanhui; Feng, Yue; Lou, Haozhe; Zhang, Xinzhao

2018-03-01

Environmental temperature of UAV system is crucial for chemical cell component inside. Once the temperature of this chemical cell is over 259 °C and keeps more than 20 min, the high thermal accumulation would result in an explosion, which seriously damage the whole UAV system. Therefore, we develop a micro temperature sensing system for monitoring the temperature of chemical cell thermally influenced by UAV device deployed in a 300 °C temperature environment, which is quite useful for insensitive munitions and UAV safety enhancement technologies.

Analyzing the threat of unmanned aerial vehicles (UAV) to nuclear facilities

DOE PAGES

Solodov, Alexander; Williams, Adam; Al Hanaei, Sara; ...

2017-04-18

Unmanned aerial vehicles (UAV) are among the major growing technologies that have many beneficial applications, yet they can also pose a significant threat. Recently, several incidents occurred with UAVs violating privacy of the public and security of sensitive facilities, including several nuclear power plants in France. The threat of UAVs to the security of nuclear facilities is of great importance and is the focus of this work. This paper presents an overview of UAV technology and classification, as well as its applications and potential threats. We show several examples of recent security incidents involving UAVs in France, USA, and Unitedmore » Arab Emirates. Further, the potential threats to nuclear facilities and measures to prevent them are evaluated. The importance of measures for detection, delay, and response (neutralization) of UAVs at nuclear facilities are discussed. An overview of existing technologies along with their strength and weaknesses are shown. Finally, the results of a gap analysis in existing approaches and technologies is presented in the form of potential technological and procedural areas for research and development. Furthermore based on this analysis, directions for future work in the field can be devised and prioritized.« less

Distributed subterranean exploration and mapping with teams of UAVs

NASA Astrophysics Data System (ADS)

Rogers, John G.; Sherrill, Ryan E.; Schang, Arthur; Meadows, Shava L.; Cox, Eric P.; Byrne, Brendan; Baran, David G.; Curtis, J. Willard; Brink, Kevin M.

2017-05-01

Teams of small autonomous UAVs can be used to map and explore unknown environments which are inaccessible to teams of human operators in humanitarian assistance and disaster relief efforts (HA/DR). In addition to HA/DR applications, teams of small autonomous UAVs can enhance Warfighter capabilities and provide operational stand-off for military operations such as cordon and search, counter-WMD, and other intelligence, surveillance, and reconnaissance (ISR) operations. This paper will present a hardware platform and software architecture to enable distributed teams of heterogeneous UAVs to navigate, explore, and coordinate their activities to accomplish a search task in a previously unknown environment.

Implementation and Testing of Low Cost Uav Platform for Orthophoto Imaging

NASA Astrophysics Data System (ADS)

Brucas, D.; Suziedelyte-Visockiene, J.; Ragauskas, U.; Berteska, E.; Rudinskas, D.

2013-08-01

Implementation of Unmanned Aerial Vehicles for civilian applications is rapidly increasing. Technologies which were expensive and available only for military use have recently spread on civilian market. There is a vast number of low cost open source components and systems for implementation on UAVs available. Using of low cost hobby and open source components ensures considerable decrease of UAV price, though in some cases compromising its reliability. In Space Science and Technology Institute (SSTI) in collaboration with Vilnius Gediminas Technical University (VGTU) researches have been performed in field of constructing and implementation of small UAVs composed of low cost open source components (and own developments). Most obvious and simple implementation of such UAVs - orthophoto imaging with data download and processing after the flight. The construction, implementation of UAVs, flight experience, data processing and data implementation will be further covered in the paper and presentation.

Object Based Building Extraction and Building Period Estimation from Unmanned Aerial Vehicle Data

NASA Astrophysics Data System (ADS)

Comert, Resul; Kaplan, Onur

2018-04-01

The aim of this study is to examine whether it is possible to estimate the building periods with respect to the building heights in the urban scale seismic performance assessment studies by using the building height retrieved from the unmanned aerial vehicle (UAV) data. For this purpose, a small area, which includes eight residential reinforced concrete buildings, was selected in Eskisehir (Turkey) city center. In this paper, the possibilities of obtaining the building heights that are used in the estimation of building periods from UAV based data, have been investigated. The investigations were carried out in 3 stages; (i) Building boundary extraction with Object Based Image Analysis (OBIA), (ii) height calculation for buildings of interest from nDSM and accuracy assessment with the terrestrial survey. (iii) Estimation of building period using height information. The average difference between the periods estimated according to the heights obtained from field measurements and from the UAV data is 2.86 % and the maximum difference is 13.2 %. Results of this study have shown that the building heights retrieved from the UAV data can be used in the building period estimation in the urban scale vulnerability assessments.

Cooperative Monocular-Based SLAM for Multi-UAV Systems in GPS-Denied Environments.

PubMed

Trujillo, Juan-Carlos; Munguia, Rodrigo; Guerra, Edmundo; Grau, Antoni

2018-04-26

This work presents a cooperative monocular-based SLAM approach for multi-UAV systems that can operate in GPS-denied environments. The main contribution of the work is to show that, using visual information obtained from monocular cameras mounted onboard aerial vehicles flying in formation, the observability properties of the whole system are improved. This fact is especially notorious when compared with other related visual SLAM configurations. In order to improve the observability properties, some measurements of the relative distance between the UAVs are included in the system. These relative distances are also obtained from visual information. The proposed approach is theoretically validated by means of a nonlinear observability analysis. Furthermore, an extensive set of computer simulations is presented in order to validate the proposed approach. The numerical simulation results show that the proposed system is able to provide a good position and orientation estimation of the aerial vehicles flying in formation.

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images

PubMed Central

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-01-01

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. PMID:26007744

The Effect of Sensor Failure on the Attitude and Rate Estimation of MAP Spacecraft

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.; Harman, Richard R.

2003-01-01

This work describes two algorithms for computing the angular rate and attitude in case of a gyro and a Star Tracker failure in the Microwave Anisotropy Probe (MAP) satellite, which was placed in the L2 parking point from where it collects data to determine the origin of the universe. The nature of the problem is described, two algorithms are suggested, an observability study is carried out and real MAP data are used to determine the merit of the algorithms. It is shown that one of the algorithms yields a good estimate of the rates but not of the attitude whereas the other algorithm yields a good estimate of the rate as well as two of the three attitude angles. The estimation of the third angle depends on the initial state estimate. There is a contradiction between this result and the outcome of the observability analysis. An explanation of this contradiction is given in the paper. Although this work treats a particular spacecraft, its conclusions are more general.

Performance Evaluation of 3d Modeling Software for Uav Photogrammetry

NASA Astrophysics Data System (ADS)

Yanagi, H.; Chikatsu, H.

2016-06-01

UAV (Unmanned Aerial Vehicle) photogrammetry, which combines UAV and freely available internet-based 3D modeling software, is widely used as a low-cost and user-friendly photogrammetry technique in the fields such as remote sensing and geosciences. In UAV photogrammetry, only the platform used in conventional aerial photogrammetry is changed. Consequently, 3D modeling software contributes significantly to its expansion. However, the algorithms of the 3D modelling software are black box algorithms. As a result, only a few studies have been able to evaluate their accuracy using 3D coordinate check points. With this motive, Smart3DCapture and Pix4Dmapper were downloaded from the Internet and commercial software PhotoScan was also employed; investigations were performed in this paper using check points and images obtained from UAV.

UAV-guided navigation for ground robot tele-operation in a military reconnaissance environment.

PubMed

Chen, Jessie Y C

2010-08-01

A military reconnaissance environment was simulated to examine the performance of ground robotics operators who were instructed to utilise streaming video from an unmanned aerial vehicle (UAV) to navigate his/her ground robot to the locations of the targets. The effects of participants' spatial ability on their performance and workload were also investigated. Results showed that participants' overall performance (speed and accuracy) was better when she/he had access to images from larger UAVs with fixed orientations, compared with other UAV conditions (baseline- no UAV, micro air vehicle and UAV with orbiting views). Participants experienced the highest workload when the UAV was orbiting. Those individuals with higher spatial ability performed significantly better and reported less workload than those with lower spatial ability. The results of the current study will further understanding of ground robot operators' target search performance based on streaming video from UAVs. The results will also facilitate the implementation of ground/air robots in military environments and will be useful to the future military system design and training community.

Atmospheric radiation measurement unmanned aerospace vehicle (ARM-UAV) program

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

Bolton, W.R.

1996-11-01

ARM-UAV is part of the multi-agency U.S. Global Change Research Program and is addressing the largest source of uncertainty in predicting climatic response: the interaction of clouds and the sun`s energy in the Earth`s atmosphere. An important aspect of the program is the use of unmanned aerospace vehicles (UAVs) as the primary airborne platform. The ARM-UAV Program has completed two major flight series: The first series conducted in April, 1994, using an existing UAV (the General Atomics Gnat 750) consisted of eight highly successful flights at the DOE climate site in Oklahoma. The second series conducted in September/October, 1995, usingmore » two piloted aircraft (Egrett and Twin Otter), featured simultaneous measurements above and below clouds and in clear sky. Additional flight series are planned to continue study of the cloudy and clear sky energy budget in the Spring and Fall of 1996 over the DOE climate site in Oklahoma. 3 refs., 4 figs., 1 tab.« less

Autonomous target tracking of UAVs based on low-power neural network hardware

NASA Astrophysics Data System (ADS)

Yang, Wei; Jin, Zhanpeng; Thiem, Clare; Wysocki, Bryant; Shen, Dan; Chen, Genshe

2014-05-01

Detecting and identifying targets in unmanned aerial vehicle (UAV) images and videos have been challenging problems due to various types of image distortion. Moreover, the significantly high processing overhead of existing image/video processing techniques and the limited computing resources available on UAVs force most of the processing tasks to be performed by the ground control station (GCS) in an off-line manner. In order to achieve fast and autonomous target identification on UAVs, it is thus imperative to investigate novel processing paradigms that can fulfill the real-time processing requirements, while fitting the size, weight, and power (SWaP) constrained environment. In this paper, we present a new autonomous target identification approach on UAVs, leveraging the emerging neuromorphic hardware which is capable of massively parallel pattern recognition processing and demands only a limited level of power consumption. A proof-of-concept prototype was developed based on a micro-UAV platform (Parrot AR Drone) and the CogniMemTMneural network chip, for processing the video data acquired from a UAV camera on the y. The aim of this study was to demonstrate the feasibility and potential of incorporating emerging neuromorphic hardware into next-generation UAVs and their superior performance and power advantages towards the real-time, autonomous target tracking.

Comparing Methods for UAV-Based Autonomous Surveillance

NASA Technical Reports Server (NTRS)

Freed, Michael; Harris, Robert; Shafto, Michael

2004-01-01

We describe an approach to evaluating algorithmic and human performance in directing UAV-based surveillance. Its key elements are a decision-theoretic framework for measuring the utility of a surveillance schedule and an evaluation testbed consisting of 243 scenarios covering a well-defined space of possible missions. We apply this approach to two example UAV-based surveillance methods, a TSP-based algorithm and a human-directed approach, then compare them to identify general strengths, and weaknesses of each method.

Mini-Uav LIDAR for Power Line Inspection

NASA Astrophysics Data System (ADS)

Teng, G. E.; Zhou, M.; Li, C. R.; Wu, H. H.; Li, W.; Meng, F. R.; Zhou, C. C.; Ma, L.

2017-09-01

Light detection and ranging (LIDAR) system based on unmanned aerial vehicles (UAVs) recently are in rapid advancement, meanwhile portable and flexible mini-UAV-borne laser scanners have been a hot research field, especially for the complex terrain survey in the mountains and other areas. This study proposes a power line inspection system solution based on mini-UAV-borne LIDAR system-AOEagle, developed by Academy of Opto-Electronics, Chinese Academy of Sciences, which mounted on a Multi-rotor unmanned aerial vehicle for complex terrain survey according to real test. Furthermore, the point cloud data was explored to validate its applicability for power line inspection, in terms of corridor and line laser point clouds; deformation detection of power towers, etc. The feasibility and advantages of AOEagle have been demonstrated by the promising results based on the real-measured data in the field of power line inspection.

Cameras and settings for optimal image capture from UAVs

NASA Astrophysics Data System (ADS)

Smith, Mike; O'Connor, James; James, Mike R.

2017-04-01

Aerial image capture has become very common within the geosciences due to the increasing affordability of low payload (<20 kg) Unmanned Aerial Vehicles (UAVs) for consumer markets. Their application to surveying has led to many studies being undertaken using UAV imagery captured from consumer grade cameras as primary data sources. However, image quality and the principles of image capture are seldom given rigorous discussion which can lead to experiments being difficult to accurately reproduce. In this contribution we revisit the underpinning concepts behind image capture, from which the requirements for acquiring sharp, well exposed and suitable imagery are derived. This then leads to discussion of how to optimise the platform, camera, lens and imaging settings relevant to image quality planning, presenting some worked examples as a guide. Finally, we challenge the community to make their image data open for review in order to ensure confidence in the outputs/error estimates, allow reproducibility of the results and have these comparable with future studies. We recommend providing open access imagery where possible, a range of example images, and detailed metadata to rigorously describe the image capture process.

Control of fixed-wing UAV at levelling phase using artificial intelligence

NASA Astrophysics Data System (ADS)

Sayfeddine, Daher

2018-03-01

The increase in the share of fly-by-wire and software controlled UAV is explained by the need to release the human-operator and the desire to reduce the degree of influence of the human factor errors that account for 26% of aircraft accidents. An important reason for the introduction of new control algorithms is also the high level of UAV failures due loss of communication channels and possible hacking. This accounts for 17% of the total number of accidents. The comparison with manned flights shows that the frequency of accidents of unmanned flights is 27,000 times higher. This means that the UAV has 1611 failures per million flight hours and only 0.06 failures at the same time for the manned flight. In view of that, this paper studies the flight autonomy of fixed-wing UAV at the levelling phase. Landing parameters of the UAV are described. They will be used to setup a control scheme for an autopilot based on fuzzy logic algorithm.

Evaluation and development of unmanned aircraft (UAV) for UDOT needs.

DOT National Transportation Integrated Search

2012-05-01

This research involved the use of high-resolution aerial photography obtained from Unmanned Aerial Vehicles (UAV) to aid UDOT in monitoring and documenting State Roadway structures and associated issues. Using geo-referenced UAV high resolution aeria...

Adaptive pattern for autonomous UAV guidance

NASA Astrophysics Data System (ADS)

Sung, Chen-Ko; Segor, Florian

2013-09-01

The research done at the Fraunhofer IOSB in Karlsruhe within the AMFIS project is focusing on a mobile system to support rescue forces in accidents or disasters. The system consists of a ground control station which has the capability to communicate with a large number of heterogeneous sensors and sensor carriers and provides several open interfaces to allow easy integration of additional sensors into the system. Within this research we focus mainly on UAV such as VTOL (Vertical takeoff and Landing) systems because of their ease of use and their high maneuverability. To increase the positioning capability of the UAV, different onboard processing chains of image exploitation for real time detection of patterns on the ground and the interfacing technology for controlling the UAV from the payload during flight were examined. The earlier proposed static ground pattern was extended by an adaptive component which admits an additional visual communication channel to the aircraft. For this purpose different components were conceived to transfer additive information using changeable patterns on the ground. The adaptive ground pattern and their application suitability had to be tested under external influence. Beside the adaptive ground pattern, the onboard process chains and the adaptations to the demands of changing patterns are introduced in this paper. The tracking of the guiding points, the UAV navigation and the conversion of the guiding point positions from the images to real world co-ordinates in video sequences, as well as use limits and the possibilities of an adaptable pattern are examined.

Mission-Oriented Sensor Arrays and UAVs - a Case Study on Environmental Monitoring

NASA Astrophysics Data System (ADS)

Figueira, N. M.; Freire, I. L.; Trindade, O.; Simões, E.

2015-08-01

This paper presents a new concept of UAV mission design in geomatics, applied to the generation of thematic maps for a multitude of civilian and military applications. We discuss the architecture of Mission-Oriented Sensors Arrays (MOSA), proposed in Figueira et Al. (2013), aimed at splitting and decoupling the mission-oriented part of the system (non safety-critical hardware and software) from the aircraft control systems (safety-critical). As a case study, we present an environmental monitoring application for the automatic generation of thematic maps to track gunshot activity in conservation areas. The MOSA modeled for this application integrates information from a thermal camera and an on-the-ground microphone array. The use of microphone arrays technology is of particular interest in this paper. These arrays allow estimation of the direction-of-arrival (DOA) of the incoming sound waves. Information about events of interest is obtained by the fusion of the data provided by the microphone array, captured by the UAV, fused with information from the termal image processing. Preliminary results show the feasibility of the on-the-ground sound processing array and the simulation of the main processing module, to be embedded into an UAV in a future work. The main contributions of this paper are the proposed MOSA system, including concepts, models and architecture.

DTM Generation with Uav Based Photogrammetric Point Cloud

NASA Astrophysics Data System (ADS)

Polat, N.; Uysal, M.

2017-11-01

Nowadays Unmanned Aerial Vehicles (UAVs) are widely used in many applications for different purposes. Their benefits however are not entirely detected due to the integration capabilities of other equipment such as; digital camera, GPS, or laser scanner. The main scope of this paper is evaluating performance of cameras integrated UAV for geomatic applications by the way of Digital Terrain Model (DTM) generation in a small area. In this purpose, 7 ground control points are surveyed with RTK and 420 photographs are captured. Over 30 million georeferenced points were used in DTM generation process. Accuracy of the DTM was evaluated with 5 check points. The root mean square error is calculated as 17.1 cm for an altitude of 100 m. Besides, a LiDAR derived DTM is used as reference in order to calculate correlation. The UAV based DTM has o 94.5 % correlation with reference DTM. Outcomes of the study show that it is possible to use the UAV Photogrammetry data as map producing, surveying, and some other engineering applications with the advantages of low-cost, time conservation, and minimum field work.

Investigation of Models and Estimation Techniques for GPS Attitude Determination

NASA Technical Reports Server (NTRS)

Garrick, J.

1996-01-01

Much work has been done in the Flight Dynamics Analysis Branch (FDAB) in developing algorithms to met the new and growing field of attitude determination using the Global Positioning SYstem (GPS) constellation of satellites. Flight Dynamics has the responsibility to investigate any new technology and incorporate the innovations in the attitude ground support systems developed to support future missions. The work presented here is an investigative analysis that will produce the needed adaptation to allow the Flight Dynamics Support System (FDSS) to incorporate GPS phase measurements and produce observation measurements compatible with the FDSS. A simulator was developed to produce the necessary measurement data to test the models developed for the different estimation techniques used by FDAB. This paper gives an overview of the current modeling capabilities of the simulator models and algorithms for the adaptation of GPS measurement data and results from each of the estimation techniques. Future analysis efforts to evaluate the simulator and models against inflight GPS measurement data are also outlined.

Unmanned Aerial Vehicles (UAVs): a new tool in counterterrorism operations?

NASA Astrophysics Data System (ADS)

Dörtbudak, Mehmet F.

2015-05-01

Terrorism is not a new phenomenon to the world, yet it remains difficult to define and counter. Countering terrorism requires several measures that must be taken simultaneously; however, counterterrorism strategies of many countries mostly depend on military measures. In the aftermath of the 2001 terrorist attack on the Twin Towers of the World Trade Center, the United States (U.S.) has started and led the campaign of Global War on Terrorism. They have invaded Afghanistan and Iraq and have encountered insurgencies run by terrorist organizations, such as al-Qaeda and its affiliates. The U.S. made the utilization of Air and Space Power very intensively during these operations. In order to implement operations; Intelligence, Surveillance, and Reconnaissance (ISR) assets were used to collect the necessary information. Before the successful insertion of a small number of U.S. Special Operation Force (SOF) teams into Afghanistan, the U.S. Air Force attacked al-Qaeda and Taliban's targets such as infrastructure, airfields, ground forces, command-control facilities etc. As soon as the U.S. troops got on the ground and started to marshal to Kabul, the Air Force supported them by attacking jointly determined targets. The Air Force continued to carry out the missions and played a significant role to achieve the objective of operation during all the time. This is not the only example of utilization of Air and Space Power in counterterrorism and counterinsurgency operations. All around the world, many countries have also made the utilization of Air Power in different missions ranging from ISR to attacking. Thinking that terrorism has a psychological dimension and losing a pilot during operations may result in decreasing the population support to operations, Unmanned Aerial Vehicles (UAVs) started to be used by practitioners and took priority over other assets. Although UAVs have been on the theatre for a long time used for ISR mission in conventional conflicts, with the advent

Interactive Cadastral Boundary Delineation from Uav Data

NASA Astrophysics Data System (ADS)

Crommelinck, S.; Höfle, B.; Koeva, M. N.; Yang, M. Y.; Vosselman, G.

2018-05-01

Unmanned aerial vehicles (UAV) are evolving as an alternative tool to acquire land tenure data. UAVs can capture geospatial data at high quality and resolution in a cost-effective, transparent and flexible manner, from which visible land parcel boundaries, i.e., cadastral boundaries are delineable. This delineation is to no extent automated, even though physical objects automatically retrievable through image analysis methods mark a large portion of cadastral boundaries. This study proposes (i) a methodology that automatically extracts and processes candidate cadastral boundary features from UAV data, and (ii) a procedure for a subsequent interactive delineation. Part (i) consists of two state-of-the-art computer vision methods, namely gPb contour detection and SLIC superpixels, as well as a classification part assigning costs to each outline according to local boundary knowledge. Part (ii) allows a user-guided delineation by calculating least-cost paths along previously extracted and weighted lines. The approach is tested on visible road outlines in two UAV datasets from Germany. Results show that all roads can be delineated comprehensively. Compared to manual delineation, the number of clicks per 100 m is reduced by up to 86 %, while obtaining a similar localization quality. The approach shows promising results to reduce the effort of manual delineation that is currently employed for indirect (cadastral) surveying.

Establishing a Disruptive New Capability for NASA to Fly UAV's into Hazardous Conditions

NASA Technical Reports Server (NTRS)

Ely, Jay; Nguyen, Truong; Wilson, Jennifer; Brown, Robert; Laughter, Sean; Teets, Ed; Parker, Allen; Chan, Patrick Hon Man; Richards, Lance

2015-01-01

A 2015 NASA Aeronautics Mission "Seedling" Proposal is described for a Severe-Environment UAV (SE-UAV) that can perform in-situ measurements in hazardous atmospheric conditions like lightning, volcanic ash and radiation. Specifically, this paper describes the design of a proof-of-concept vehicle and measurement system that can survive lightning attachment during flight operations into thunderstorms. Elements from three NASA centers draw together for the SE-UAV concept. 1) The NASA KSC Genesis UAV was developed in collaboration with the DARPA Nimbus program to measure electric field and X-rays present within thunderstorms. 2) A novel NASA LaRC fiber-optic sensor uses Faraday-effect polarization rotation to measure total lightning electric current on an air vehicle fuselage. 3) NASA AFRC's state-of-the-art Fiber Optics and Systems Integration Laboratory is envisioned to transition the Faraday system to a compact, light-weight, all-fiber design. The SE-UAV will provide in-flight lightning electric-current return stroke and recoil leader data, and serve as a platform for development of emerging sensors and new missions into hazardous environments. NASA's Aeronautics and Science Missions are interested in a capability to perform in-situ volcanic plume measurements and long-endurance UAV operations in various weather conditions. (Figure 1 shows an artist concept of a SE-UAV flying near a volcano.) This paper concludes with an overview of the NASA Aeronautics Strategic Vision, Programs, and how a SE-UAV is envisioned to impact them. The SE-UAV concept leverages high-value legacy research products into a new capability for NASA to fly a pathfinder UAV into hazardous conditions, and is presented in the SPIE DSS venue to explore teaming, collaboration and advocacy opportunities outside NASA.

Establishing a disruptive new capability for NASA to fly UAV's into hazardous conditions

NASA Astrophysics Data System (ADS)

Ely, Jay; Nguyen, Truong; Wilson, Jennifer; Brown, Robert; Laughter, Sean; Teets, Ed; Parker, Allen; Chan, Hon M.; Richards, Lance

2015-05-01

A 2015 NASA Aeronautics Mission "Seedling" Proposal is described for a Severe-Environment UAV (SE-UAV) that can perform in-situ measurements in hazardous atmospheric conditions like lightning, volcanic ash and radiation. Specifically, this paper describes the design of a proof-of-concept vehicle and measurement system that can survive lightning attachment during flight operations into thunderstorms. Elements from three NASA centers draw together for the SE-UAV concept. 1) The NASA KSC Genesis UAV was developed in collaboration with the DARPA Nimbus program to measure electric field and X-rays present within thunderstorms. 2) A novel NASA LaRC fiber-optic sensor uses Faraday-effect polarization rotation to measure total lightning electric current on an air vehicle fuselage. 3) NASA AFRC's state-of-the-art Fiber Optics and Systems Integration Laboratory is envisioned to transition the Faraday system to a compact, light-weight, all-fiber design. The SE-UAV will provide in-flight lightning electric-current return stroke and recoil leader data, and serve as a platform for development of emerging sensors and new missions into hazardous environments. NASA's Aeronautics and Science Missions are interested in a capability to perform in-situ volcanic plume measurements and long-endurance UAV operations in various weather conditions. (Figure 1 shows an artist concept of a SE-UAV flying near a volcano.) This paper concludes with an overview of the NASA Aeronautics Strategic Vision, Programs, and how a SE-UAV is envisioned to impact them. The SE-UAV concept leverages high-value legacy research products into a new capability for NASA to fly a pathfinder UAV into hazardous conditions, and is presented in the SPIE DSS venue to explore teaming, collaboration and advocacy opportunities outside NASA.

Using UAV photogrammetry to study topographic change: application to Saskatchewan Glacier, Alberta, Canada

NASA Astrophysics Data System (ADS)

Meunier Cardinal, G.; Demuth, M. N.; Kinnard, C.

2016-12-01

Glaciers are an important source of fresh water in the headwaters of the Canadian Rocky Mountains, and ongoing climate warming could reduce their future hydrological contribution. Unmanned Aerial Vehicles UAVs) are an emergent technology that allow studying glacial processes with an unprecedented level of detail, but their usefulness for deriving accurate topographic data on glaciers has not yet been fully assessed. In this perspective we tested the use of a UAV platform to acquire images at a very high spatial resolution (<10cm) in order to estimate topographical and dynamic changes over a one year period on the ablation zone of Saskatchewan glacier, the main outlet of the Columbia Icefield in Alberta, Canada (52°06N, 117°15W). Two data acquisition campaigns were carried out, in August 2014 and 2015. Orthomosaics and digital elevation models (DEMs) with a high spatial resolution (<10cm) were produced for each year, using the Structure from Motion (SfM) algorithm. A detailed assessment of DEM errors was performed by cross-validation of an network of ground control points (GCPs) deployed on the glacier surface. The influence of checkpoint position in the network, border effects, number of photos calibrated and GPS accuracy were examined. Topographical changes were measured from the DEM difference and surface displacements estimated by applying feature tracking techniques to the orthomosaics. Further, the dominant scales of topographic spatial variability were examined using a semivariogram analysis of the DEMs. Results show that UAV-based photogrammetry is promising to further our understanding of high-resolution glacier surface processes and to perform repeat, on-demand monitoring of glacier changes, but their application on remote glaciers remains challenging.

Using Public Network Infrastructures for UAV Remote Sensing in Civilian Security Operations

DTIC Science & Technology

2011-03-01

leveraging public wireless communication networks for UAV-based sensor networks with respect to existing constraints and user requirements...Detection with an Autonomous Micro UAV Mesh Network . In the near future police departments, fire brigades and other homeland security ...UAV-based sensor networks with respect to existing constraints and user requirements. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION

'Fly Like This': Natural Language Interface for UAV Mission Planning

NASA Technical Reports Server (NTRS)

Chandarana, Meghan; Meszaros, Erica L.; Trujillo, Anna; Allen, B. Danette

2017-01-01

With the increasing presence of unmanned aerial vehicles (UAVs) in everyday environments, the user base of these powerful and potentially intelligent machines is expanding beyond exclusively highly trained vehicle operators to include non-expert system users. Scientists seeking to augment costly and often inflexible methods of data collection historically used are turning towards lower cost and reconfigurable UAVs. These new users require more intuitive and natural methods for UAV mission planning. This paper explores two natural language interfaces - gesture and speech - for UAV flight path generation through individual user studies. Subjects who participated in the user studies also used a mouse-based interface for a baseline comparison. Each interface allowed the user to build flight paths from a library of twelve individual trajectory segments. Individual user studies evaluated performance, efficacy, and ease-of-use of each interface using background surveys, subjective questionnaires, and observations on time and correctness. Analysis indicates that natural language interfaces are promising alternatives to traditional interfaces. The user study data collected on the efficacy and potential of each interface will be used to inform future intuitive UAV interface design for non-expert users.

Wetland Assessment Using Unmanned Aerial Vehicle (uav) Photogrammetry

NASA Astrophysics Data System (ADS)

Boon, M. A.; Greenfield, R.; Tesfamichael, S.

2016-06-01

The use of Unmanned Arial Vehicle (UAV) photogrammetry is a valuable tool to enhance our understanding of wetlands. Accurate planning derived from this technological advancement allows for more effective management and conservation of wetland areas. This paper presents results of a study that aimed at investigating the use of UAV photogrammetry as a tool to enhance the assessment of wetland ecosystems. The UAV images were collected during a single flight within 2½ hours over a 100 ha area at the Kameelzynkraal farm, Gauteng Province, South Africa. An AKS Y-6 MKII multi-rotor UAV and a digital camera on a motion compensated gimbal mount were utilised for the survey. Twenty ground control points (GCPs) were surveyed using a Trimble GPS to achieve geometrical precision and georeferencing accuracy. Structure-from-Motion (SfM) computer vision techniques were used to derive ultra-high resolution point clouds, orthophotos and 3D models from the multi-view photos. The geometric accuracy of the data based on the 20 GCP's were 0.018 m for the overall, 0.0025 m for the vertical root mean squared error (RMSE) and an over all root mean square reprojection error of 0.18 pixel. The UAV products were then edited and subsequently analysed, interpreted and key attributes extracted using a selection of tools/ software applications to enhance the wetland assessment. The results exceeded our expectations and provided a valuable and accurate enhancement to the wetland delineation, classification and health assessment which even with detailed field studies would have been difficult to achieve.

Prospect theory based estimation of drivers' risk attitudes in route choice behaviors.

PubMed

Zhou, Lizhen; Zhong, Shiquan; Ma, Shoufeng; Jia, Ning

2014-12-01

This paper applied prospect theory (PT) to describe drivers' route choice behavior under Variable Message Sign (VMS), which presented visual traffic information to assist them to make route choice decisions. A quite rich empirical data from questionnaire and field spot was used to estimate parameters of PT. In order to make the parameters more realistic with drivers' attitudes, they were classified into different types by significant factors influencing their behaviors. Based on the travel time distribution of alternative routes and route choice results from questionnaire, the parameterized value function of each category was figured out, which represented drivers' risk attitudes and choice characteristics. The empirical verification showed that the estimates were acceptable and effective. The result showed drivers' risk attitudes and route choice characteristics could be captured by PT under real-time information shown on VMS. For practical application, once drivers' route choice characteristics and parameters were identified, their route choice behavior under different road conditions could be predicted accurately, which was the basis of traffic guidance measures formulation and implementation for targeted traffic management. Moreover, the heterogeneous risk attitudes among drivers should be considered when releasing traffic information and regulating traffic flow. Copyright © 2014 Elsevier Ltd. All rights reserved.

Applications of UAVs in row-crop agriculture: advantages and limitations

NASA Astrophysics Data System (ADS)

Basso, B.; Putnam, G.; Price, R.; Zhang, J.

2016-12-01

The application of Unmanned Aerial Vehicles (UAV) to monitor agricultural fields has increased over the last few years due to advances in the technology, sensors, post-processing software for image analysis, along with more favorable regulations that allowed UAVs to be flown for commercial use. UAV have several capabilities depending on the type of sensors that are mounted onboard. The most widely used application remains crop scouting to identify areas within fields where the crops underperform for various reasons (nutritional status and water stress, presence of weeds, poor stands etc). In this talk, we present the preliminary results of UAVs field based research to better understand spatial and temporal variability of crop yield. Their advantage in providing timely information is critical, but adaptive management requires a system approach to account for the interactions occurring between genetics, environment and management.

Simulation analysis of photometric data for attitude estimation of unresolved space objects

NASA Astrophysics Data System (ADS)

Du, Xiaoping; Gou, Ruixin; Liu, Hao; Hu, Heng; Wang, Yang

2017-10-01

The attitude information acquisition of unresolved space objects, such as micro-nano satellites and GEO objects under the way of ground-based optical observations, is a challenge to space surveillance. In this paper, a useful method is proposed to estimate the SO attitude state according to the simulation analysis of photometric data in different attitude states. The object shape model was established and the parameters of the BRDF model were determined, then the space object photometric model was established. Furthermore, the photometric data of space objects in different states are analyzed by simulation and the regular characteristics of the photometric curves are summarized. The simulation results show that the photometric characteristics are useful for attitude inversion in a unique way. Thus, a new idea is provided for space object identification in this paper.

Uav for Geodata Acquisition in Agricultureal and Forestal Applications

NASA Astrophysics Data System (ADS)

Reidelstürz, P.; Schrenk, L.; Littmann, W.

2011-09-01

In the field of precision-farming research, solutions are worked out to combine ecological and economical requirements in a harmonic way. Integrating hightech in agricultural machinery, natural differences in the fields (biodiversity) can be detected and considered to economize agricultural resources and to give respect to natural ecological variability at the same time. Using precision farming resources, machining - and labour time can be economized, productivness can be improved, environmental burden can be discharged and documentation of production processes can be improved. To realize precision farming it is essential to make contemporary large scale data of the biodiversity in the field available. In the last years effectual traktor based equipment for real time precision farming applications was developed. Using remote sensing, biomass diversity of the field can be considered while applicating operating ressources economicly. Because these large scale data aquisition depends on expensive tractor based inspections, capable Unmanned Aerial Vehicles (UAVs) could complement or in special situations even replace such tractor based data aquisition needed for the realization of precision farming strategies. The specific advantages and application slots of UAVs seems to be ideal for the usage in the field of precision farming. For example the size of even large agricultural fields in germany can be managed even by smaller UAVs. Data can be captured spontaneously, promptly, in large scale, with less respect of weather conditions. In agricultural regions UAV flights can be arranged in visual range as actually the legislator requires in germany, especially because the use of autopilotsystems in fact is nessecary to assure regular area-wide data without gaps but not to fly in non-visible regions. Also a minimized risk of hazard is given, flying UAVs over deserted agricultural areas. In a first stage CIS GmbH cooperated with "Institute For Flightsystems" of the University

Computer simulation results of attitude estimation of earth orbiting satellites

NASA Technical Reports Server (NTRS)

Kou, S. R.

1976-01-01

Computer simulation results of attitude estimation of Earth-orbiting satellites (including Space Telescope) subjected to environmental disturbances and noises are presented. Decomposed linear recursive filter and Kalman filter were used as estimation tools. Six programs were developed for this simulation, and all were written in the basic language and were run on HP 9830A and HP 9866A computers. Simulation results show that a decomposed linear recursive filter is accurate in estimation and fast in response time. Furthermore, for higher order systems, this filter has computational advantages (i.e., less integration errors and roundoff errors) over a Kalman filter.

Confidential and Authenticated Communications in a Large Fixed-Wing UAV Swarm

DTIC Science & Technology

2016-12-01

either a UAV or a ground station. Asymmetric cryptography is not an option for swarm communications. It is a potential option for initially keying or...each UAV grows ten bytes for each UAV in the swarm, and a 30% overhead is added on for worst case cryptography . The resulting throughput is...analysis in Section IV, we can predict the burden that cryptography places on the ODroid computer. Given that the average unencrypted message size was

UAV measurements of aerosol properties at the Cyprus institute

NASA Astrophysics Data System (ADS)

Neitola, Kimmo; Sciare, Jean; Keleshis, Christos; Pikridas, Michael; Argyrides, Marios; Vouterakos, Panagiotis; Antoniou, Panyiota; Apostolou, Apostolos; Savvides, Constantinos; Vrekoussis, Mihalis; Mihalopoulos, Nikos; Biskos, George; Gao, Ru-Shan; Murphy, Daniel; Schrod, Jann; Weber, Daniel; Bingemer, Heinz; Mocnik, Grisa

2017-04-01

Unmanned Aerial Vehicles (UAVs) provide a cost-effective and easy-to-use method to document the vertical profiles of aerosol particles and their physical and optical properties, within and above the boundary layer. These observations combined with satellite and ground data together can provide important information and model constrains regarding the impact of aerosols on the air quality and regional climate. Cyprus is a unique place to observe long-range transported pollution and dust originating from different areas (Europe, Africa, Turkey, and Middle East) and perform such aerosol profiling. The USRL team at the Cyprus Institute has recently started weekly routine flights with a newly developed UAV fleet to build a unique dataset of vertical profile observations. Instrumentation on the UAVs includes miniature Scanning Aerosol Sun Photometer (miniSASP, Murphy et al., 2015), Printed Optical Particle Spectrometer (POPS, Gao et al., 2016), Ice nuclei sampler (IN) and Dual Wavelength absorption Prototype (DWP) together with the measured meteorological parameters (P, T and RH). The UAV fleet is still expanding, as well as the instrumentation, and preliminary test flights have led to very promising results. The UAV ascend up to approximately the middle of the boundary layer, defined by LIDAR measurements at Limassol, where the UAV will fly on one altitude for several minutes ensuring stable data collection. After flying on one altitude, the UAV will continue ascending above the boundary layer, where another level flight will take place for data gathering, before descending for safe landing. The miniSASP measures the sun irradiance and sky radiance at four wavelengths (460, 550, 670 and 680nm) by doing continuous almucantar scans every 30 s. The instrument installation compensates for the pitch and roll of the UAV with 4 Hz frequency. For this reason, the flights are designed to maintain level flight conditions, to ensure proper data acquisition, and to obtain data from

[Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

PubMed

Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

2015-05-01

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

The Combination of Uav Survey and Landsat Imagery for Monitoring of Crop Vigor in Precision Agriculture

NASA Astrophysics Data System (ADS)

Lukas, V.; Novák, J.; Neudert, L.; Svobodova, I.; Rodriguez-Moreno, F.; Edrees, M.; Kren, J.

2016-06-01

Mapping of the with-in field variability of crop vigor has a long tradition with a success rate ranging from medium to high depending on the local conditions of the study. Information about the development of agronomical relevant crop parameters, such as above-ground biomass and crop nutritional status, provides high reliability for yield estimation and recommendation for variable rate application of fertilizers. The aim of this study was to utilize unmanned and satellite multispectral imaging for estimation of basic crop parameters during the growing season. The experimental part of work was carried out in 2014 at the winter wheat field with an area of 69 ha located in the South Moravia region of the Czech Republic. An UAV imaging was done in April 2014 using Sensefly eBee, which was equipped by visible and near infrared (red edge) multispectral cameras. For ground truth calibration the spectral signatures were measured on 20 sites using portable spectroradiometer ASD Handheld 2 and simultaneously plant samples were taken at BBCH 32 (April 2014) and BBCH 59 (Mai 2014) for estimation of above-ground biomass and nitrogen content. The UAV survey was later extended by selected cloud-free Landsat 8 OLI satellite imagery, downloaded from USGS web application Earth Explorer. After standard pre-processing procedures, a set of vegetation indices was calculated from remotely and ground sensed data. As the next step, a correlation analysis was computed among crop vigor parameters and vegetation indices. Both, amount of above-ground biomass and nitrogen content were highly correlated (r > 0.85) with ground spectrometric measurement by ASD Handheld 2 in BBCH 32, especially for narrow band vegetation indices (e.g. Red Edge Inflection Point). UAV and Landsat broadband vegetation indices varied in range of r = 0.5 - 0.7, highest values of the correlation coefficients were obtained for crop biomass by using GNDVI. In all cases results from BBCH 59 vegetation stage showed lower

Tracking, aiming, and hitting the UAV with ordinary assault rifle

NASA Astrophysics Data System (ADS)

Racek, František; Baláž, Teodor; Krejčí, Jaroslav; Procházka, Stanislav; Macko, Martin

2017-10-01

The usage small-unmanned aerial vehicles (UAVs) is significantly increasing nowadays. They are being used as a carrier of military spy and reconnaissance devices (taking photos, live video streaming and so on), or as a carrier of potentially dangerous cargo (intended for destruction and killing). Both ways of utilizing the UAV cause the necessity to disable it. From the military point of view, to disable the UAV means to bring it down by a weapon of an ordinary soldier that is the assault rifle. This task can be challenging for the soldier because he needs visually detect and identify the target, track the target visually and aim on the target. The final success of the soldier's mission depends not only on the said visual tasks, but also on the properties of the weapon and ammunition. The paper deals with possible methods of prediction of probability of hitting the UAV targets.

Data Gathering and Energy Transfer Dilemma in UAV-Assisted Flying Access Network for IoT

PubMed Central

Arabi, Sara; Sadik, Mohamed

2018-01-01

Recently, Unmanned Aerial Vehicles (UAVs) have emerged as an alternative solution to assist wireless networks, thanks to numerous advantages they offer in comparison to terrestrial fixed base stations. For instance, a UAV can be used to embed a flying base station providing an on-demand nomadic access to network services. A UAV can also be used to wirelessly recharge out-of-battery ground devices. In this paper, we aim to deal with both data collection and recharging depleted ground Internet-of-Things (IoT) devices through a UAV station used as a flying base station. To extend the network lifetime, we present a novel use of UAV with energy harvesting module and wireless recharging capabilities. However, the UAV is used as an energy source to empower depleted IoT devices. On one hand, the UAV charges depleted ground IoT devices under three policies: (1) low-battery first scheme; (2) high-battery first scheme; and (3) random scheme. On the other hand, the UAV station collects data from IoT devices that have sufficient energy to transmit their packets, and in the same phase, the UAV exploits the Radio Frequency (RF) signals transmitted by IoT devices to extract and harvest energy. Furthermore, and as the UAV station has a limited coverage time due to its energy constraints, we propose and investigate an efficient trade-off between ground users recharging time and data gathering time. Furthermore, we suggest to control and optimize the UAV trajectory in order to complete its travel within a minimum time, while minimizing the energy spent and/or enhancing the network lifetime. Extensive numerical results and simulations show how the system behaves under different scenarios and using various metrics in which we examine the added value of UAV with energy harvesting module. PMID:29751662

Data Gathering and Energy Transfer Dilemma in UAV-Assisted Flying Access Network for IoT.

PubMed

Arabi, Sara; Sabir, Essaid; Elbiaze, Halima; Sadik, Mohamed

2018-05-11

Recently, Unmanned Aerial Vehicles (UAVs) have emerged as an alternative solution to assist wireless networks, thanks to numerous advantages they offer in comparison to terrestrial fixed base stations. For instance, a UAV can be used to embed a flying base station providing an on-demand nomadic access to network services. A UAV can also be used to wirelessly recharge out-of-battery ground devices. In this paper, we aim to deal with both data collection and recharging depleted ground Internet-of-Things (IoT) devices through a UAV station used as a flying base station. To extend the network lifetime, we present a novel use of UAV with energy harvesting module and wireless recharging capabilities. However, the UAV is used as an energy source to empower depleted IoT devices. On one hand, the UAV charges depleted ground IoT devices under three policies: (1) low-battery first scheme; (2) high-battery first scheme; and (3) random scheme. On the other hand, the UAV station collects data from IoT devices that have sufficient energy to transmit their packets, and in the same phase, the UAV exploits the Radio Frequency (RF) signals transmitted by IoT devices to extract and harvest energy. Furthermore, and as the UAV station has a limited coverage time due to its energy constraints, we propose and investigate an efficient trade-off between ground users recharging time and data gathering time. Furthermore, we suggest to control and optimize the UAV trajectory in order to complete its travel within a minimum time, while minimizing the energy spent and/or enhancing the network lifetime. Extensive numerical results and simulations show how the system behaves under different scenarios and using various metrics in which we examine the added value of UAV with energy harvesting module.

Cloud-Assisted UAV Data Collection for Multiple Emerging Events in Distributed WSNs.

PubMed

Cao, Huiru; Liu, Yongxin; Yue, Xuejun; Zhu, Wenjian

2017-08-07

In recent years, UAVs (Unmanned Aerial Vehicles) have been widely applied for data collection and image capture. Specifically, UAVs have been integrated with wireless sensor networks (WSNs) to create data collection platforms with high flexibility. However, most studies in this domain focus on system architecture and UAVs' flight trajectory planning while event-related factors and other important issues are neglected. To address these challenges, we propose a cloud-assisted data gathering strategy for UAV-based WSN in the light of emerging events. We also provide a cloud-assisted approach for deriving UAV's optimal flying and data acquisition sequence of a WSN cluster. We validate our approach through simulations and experiments. It has been proved that our methodology outperforms conventional approaches in terms of flying time, energy consumption, and integrity of data acquisition. We also conducted a real-world experiment using a UAV to collect data wirelessly from multiple clusters of sensor nodes for monitoring an emerging event, which are deployed in a farm. Compared against the traditional method, this proposed approach requires less than half the flying time and achieves almost perfect data integrity.

Coastal areas mapping using UAV photogrammetry

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Kozarski, Dimitrios; Kogkas, Stefanos

2017-10-01

The coastal areas in the Patras Gulf suffer degradation due to the sea action and other natural and human-induced causes. Changes in beaches, ports, and other man made constructions need to be assessed, both after severe events and on a regular basis, to build models that can predict the evolution in the future. Thus, reliable spatial data acquisition is a critical process for the identification of the coastline and the broader coastal zones for geologists and other scientists involved in the study of coastal morphology. High resolution satellite data, airphotos and airborne Lidar provided in the past the necessary data for the coastline monitoring. High-resolution digital surface models (DSMs) and orthophoto maps had become a necessity in order to map with accuracy all the variations in costal environments. Recently, unmanned aerial vehicles (UAV) photogrammetry offers an alternative solution to the acquisition of high accuracy spatial data along the coastline. This paper presents the use of UAV to map the coastline in Rio area Western Greece. Multiple photogrammetric aerial campaigns were performed. A small commercial UAV (DJI Phantom 3 Advance) was used to acquire thousands of images with spatial resolutions better than 5 cm. Different photogrammetric software's were used to orientate the images, extract point clouds, build a digital surface model and produce orthoimage mosaics. In order to achieve the best positional accuracy signalised ground control points were measured with a differential GNSS receiver. The results of this coastal monitoring programme proved that UAVs can replace many of the conventional surveys, with considerable gains in the cost of the data acquisition and without any loss in the accuracy.

High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology

PubMed Central

Torres-Sánchez, Jorge; López-Granados, Francisca; Serrano, Nicolás; Arquero, Octavio; Peña, José M.

2015-01-01

The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications. PMID:26107174

High-Throughput 3-D Monitoring of Agricultural-Tree Plantations with Unmanned Aerial Vehicle (UAV) Technology.

PubMed

Torres-Sánchez, Jorge; López-Granados, Francisca; Serrano, Nicolás; Arquero, Octavio; Peña, José M

2015-01-01

The geometric features of agricultural trees such as canopy area, tree height and crown volume provide useful information about plantation status and crop production. However, these variables are mostly estimated after a time-consuming and hard field work and applying equations that treat the trees as geometric solids, which produce inconsistent results. As an alternative, this work presents an innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: 1) generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and 2) use of object-based image analysis techniques. Our UAV-based procedure produced successful results both in single-tree and in tree-row plantations, reporting up to 97% accuracy on area quantification and minimal deviations compared to in-field estimations of tree heights and crown volumes. The maps generated could be used to understand the linkages between tree grown and field-related factors or to optimize crop management operations in the context of precision agriculture with relevant agro-environmental implications.

Cooperative Search by UAV Teams: A Model Predictive Approach Using Dynamic Graphs

DTIC Science & Technology

2011-10-01

decentralized processing and control architecture. SLAMEM asset models accurately represent the Unicorn UAV platforms and other standard military platforms in...IMPLEMENTATION The CGBMPS algorithm has been successfully field-tested using both Unicorn [27] and Raven [20] UAV platforms. This section describes...the hardware-software system setup and implementation used for testing with Unicorns , Toyon’s UAV test platform. We also present some results from the

a Comparison of Uav and Tls Data for Soil Roughness Assessment

NASA Astrophysics Data System (ADS)

Milenković, M.; Karel, W.; Ressl, C.; Pfeifer, N.

2016-06-01

Soil roughness represents fine-scale surface geometry which figures in many geophysical models. While static photogrammetric techniques (terrestrial images and laser scanning) have been recently proposed as a new source for deriving roughness heights, there is still need to overcome acquisition scale and viewing geometry issues. By contrast to the static techniques, images taken from unmanned aerial vehicles (UAV) can maintain near-nadir looking geometry over scales of several agricultural fields. This paper presents a pilot study on high-resolution, soil roughness reconstruction and assessment from UAV images over an agricultural plot. As a reference method, terrestrial laser scanning (TLS) was applied on a 10 m x 1.5 m subplot. The UAV images were self-calibrated and oriented within a bundle adjustment, and processed further up to a dense-matched digital surface model (DSM). The analysis of the UAV- and TLS-DSMs were performed in the spatial domain based on the surface autocorrelation function and the correlation length, and in the frequency domain based on the roughness spectrum and the surface fractal dimension (spectral slope). The TLS- and UAV-DSM differences were found to be under ±1 cm, while the UAV DSM showed a systematic pattern below this scale, which was explained by weakly tied sub-blocks of the bundle block. The results also confirmed that the existing TLS methods leads to roughness assessment up to 5 mm resolution. However, for our UAV data, this was not possible to achieve, though it was shown that for spatial scales of 12 cm and larger, both methods appear to be usable. Additionally, this paper suggests a method to propagate measurement errors to the correlation length.

Accuracy of Orthomosaic Generated by Different Methods in Example of UAV Platform MUST Q

NASA Astrophysics Data System (ADS)

Liba, N.; Berg-Jürgens, J.

2015-11-01

Development of photogrammetry has reached a new level due to the use of unmanned aerial vehicles (UAV). In Estonia, the main areas of use of UAVs are monitoring overhead power lines for energy companies and fields in agriculture, and estimating the use of stockpile in mining. The project was carried out by the order of the City of Tartu for future road construction. In this research, automation of UAV platform MUST Q aerial image processing and reduction of time spent on the use of ground control points (GCP) is studied. For that two projects were created with software Pix4D. First one was processed automatically without GCP. Second one did use GCP, but all the processing was done automatically. As the result of the project, two orthomosaics with the pixel size of 5 cm were composed. Projects allowed ensuring accuracy limit of three times of the pixel size. The project that turned out to be the most accurate was the one using ground control points to do the levelling, which remained within the error limit allowed and the accuracy of the orthomosaic was 0.132 m. The project that didn't use ground control points had the accuracy of 1.417 m.

Development and Testing of a Two-UAV Communication Relay System.

PubMed

Li, Boyang; Jiang, Yifan; Sun, Jingxuan; Cai, Lingfeng; Wen, Chih-Yung

2016-10-13

In the development of beyond-line-of-sight (BLOS) Unmanned Aerial Vehicle (UAV) systems, communication between the UAVs and the ground control station (GCS) is of critical importance. The commonly used economical wireless modules are restricted by the short communication range and are easily blocked by obstacles. The use of a communication relay system provides a practical way to solve these problems, improving the performance of UAV communication in BLOS and cross-obstacle operations. In this study, a communication relay system, in which a quadrotor was used to relay radio communication for another quadrotor was developed and tested. First, the UAVs used as the airborne platform were constructed, and the hardware for the communication relay system was selected and built up. Second, a set of software programs and protocol for autonomous mission control, communication relay control, and ground control were developed. Finally, the system was fully integrated into the airborne platform and tested both indoor and in-flight. The Received Signal Strength Indication (RSSI) and noise value in two typical application scenarios were recorded. The test results demonstrated the ability of this system to extend the communication range and build communication over obstacles. This system also shows the feasibility to coordinate multiple UAVs' communication with the same relay structure.

Lightweight Hyperspectral Mapping System and a Novel Photogrammetric Processing Chain for UAV-based Sensing

NASA Astrophysics Data System (ADS)

Suomalainen, Juha; Franke, Jappe; Anders, Niels; Iqbal, Shahzad; Wenting, Philip; Becker, Rolf; Kooistra, Lammert

2014-05-01

We have developed a lightweight Hyperspectral Mapping System (HYMSY) and a novel processing chain for UAV based mapping. The HYMSY consists of a custom pushbroom spectrometer (range 450-950nm, FWHM 9nm, ~20 lines/s, 328 pixels/line), a consumer camera (collecting 16MPix raw image every 2 seconds), a GPS-Inertia Navigation System (GPS-INS), and synchronization and data storage units. The weight of the system at take-off is 2.0kg allowing us to mount it on a relatively small octocopter. The novel processing chain exploits photogrammetry in the georectification process of the hyperspectral data. At first stage the photos are processed in a photogrammetric software producing a high-resolution RGB orthomosaic, a Digital Surface Model (DSM), and photogrammetric UAV/camera position and attitude at the moment of each photo. These photogrammetric camera positions are then used to enhance the internal accuracy of GPS-INS data. These enhanced GPS-INS data are then used to project the hyperspectral data over the photogrammetric DSM, producing a georectified end product. The presented photogrammetric processing chain allows fully automated georectification of hyperspectral data using a compact GPS-INS unit while still producingin UAV use higher georeferencing accuracy than would be possible using the traditional processing method. During 2013, we have operated HYMSY on 150+ octocopter flights at 60+ sites or days. On typical flight we have produced for a 2-10ha area: a RGB orthoimagemosaic at 1-5cm resolution, a DSM in 5-10cm resolution, and hyperspectral datacube at 10-50cm resolution. The targets have mostly consisted of vegetated targets including potatoes, wheat, sugar beets, onions, tulips, coral reefs, and heathlands,. In this poster we present the Hyperspectral Mapping System and the photogrammetric processing chain with some of our first mapping results.

Infrared search and track performance estimates for detection of commercial unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Nicholas, Robert; Driggers, Ronald; Shelton, David; Furxhi, Orges

2018-04-01

Unmanned aerial vehicles (UAVs) have become more readily available in the past 5 years and are proliferating rapidly. New aviation regulations are accelerating the use of UAVs in many applications. As a result, there are increasing concerns of potential air threats in situational environments including commercial airport security and drug trafficking. In this study, radiometric signatures of commercially available miniature UAVs is determined for long-wave infrared (LWIR) bands in both clear sky and partial cloudy conditions. Results are presented that compare LWIR performance estimates for the detection of commercial UAVs via infrared search and track (IRST) systems with two candidate sensors.

UAV Research, Operations, and Flight Test at the NASA Dryden Flight Research Center

NASA Technical Reports Server (NTRS)

Cosentino, Gary B.

2009-01-01

This slide presentation reviews some of the projects that have extended NASA Dryden's capabilities in designing, testing, and using Unmanned Aerial Vehicles (UAV's). Some of the UAV's have been for Science and experimental applications, some have been for flight research and demonstration purposes, and some have been small UAV's for other customers.

A Multi-Purpose Simulation Environment for UAV Research

DTIC Science & Technology

2003-05-01

Maximum 200 Words) Unmanned aerial vehicles (UAVs) are playing an important role in today’s military initiatives. UAVs have proven to be invaluable in...battlefield commanders. Integration of new technologies necessitates simulation prior to fielding new systems in order to avoid costly er- rors. The unique...collection ofinformation if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD

Distinguishing plant population and variety with UAV-derived vegetation indices

NASA Astrophysics Data System (ADS)

Oakes, Joseph; Balota, Maria

2017-05-01

Variety selection and seeding rate are two important choice that a peanut grower must make. High yielding varieties can increase profit with no additional input costs, while seeding rate often determines input cost a grower will incur from seed costs. The overall purpose of this study was to examine the effect that seeding rate has on different peanut varieties. With the advent of new UAV technology, we now have the possibility to use indices collected with the UAV to measure emergence, seeding rate, growth rate, and perhaps make yield predictions. This information could enable growers to make management decisions early in the season based on low plant populations due to poor emergence, and could be a useful tool for growers to use to estimate plant population and growth rate in order to help achieve desired crop stands. Red-Green-Blue (RGB) and near-infrared (NIR) images were collected from a UAV platform starting two weeks after planting and continued weekly for the next six weeks. Ground NDVI was also collected each time aerial images were collected. Vegetation indices were derived from both the RGB and NIR images. Greener area (GGA- the proportion of green pixels with a hue angle from 80° to 120°) and a* (the average red/green color of the image) were derived from the RGB images while Normalized Differential Vegetative Index (NDVI) was derived from NIR images. Aerial indices were successful in distinguishing seeding rates and determining emergence during the first few weeks after planting, but not later in the season. Meanwhile, these aerial indices are not an adequate predictor of yield in peanut at this point.

A debugging method of the Quadrotor UAV based on infrared thermal imaging

NASA Astrophysics Data System (ADS)

Cui, Guangjie; Hao, Qian; Yang, Jianguo; Chen, Lizhi; Hu, Hongkang; Zhang, Lijun

2018-01-01

High-performance UAV has been popular and in great need in recent years. The paper introduces a new method in debugging Quadrotor UAVs. Based on the infrared thermal technology and heat transfer theory, a UAV is under debugging above a hot-wire grid which is composed of 14 heated nichrome wires. And the air flow propelled by the rotating rotors has an influence on the temperature distribution of the hot-wire grid. An infrared thermal imager below observes the distribution and gets thermal images of the hot-wire grid. With the assistance of mathematic model and some experiments, the paper discusses the relationship between thermal images and the speed of rotors. By means of getting debugged UAVs into test, the standard information and thermal images can be acquired. The paper demonstrates that comparing to the standard thermal images, a UAV being debugging in the same test can draw some critical data directly or after interpolation. The results are shown in the paper and the advantages are discussed.

Aircraft Survivability: UAVs and Manned Aircraft - Increasing Effectiveness and Survivability, Fall 2002

DTIC Science & Technology

2002-01-01

techniques that interface with the composite structure to attach opaque armor(s) to compos- ite aircraft structure. Over a period of four years...2002 2. REPORT TYPE 3. DATES COVERED 00-00-2002 to 00-00-2002 4. TITLE AND SUBTITLE Aircraft Survivability: UAVs and Manned Aircraft ...survivability concepts to UAV program offices and airframe manufacturers. 11 Aircraft Fire Protection Techniques—Application to UAVs by Ms. Ginger Bennett

Exploitation of Self Organization in UAV Swarms for Optimization in Combat Environments

DTIC Science & Technology

2008-03-01

behaviors and entangled hierarchy into Swarmfare [59] UAV simulation environment to include these models. • Validate this new model’s success through...Figure 4.3. The hierarchy of control emerges from the entangled hierarchy of the state relations at the simulation , swarm and rule/behaviors level...majors, major) Abstract Model Types (AMT) Figure A.1: SO Abstract Model Type Table 142 Appendix B. Simulators Comparision Name MATLAB Multi UAV MultiUAV

Integrating critical interface elements for intuitive single-display aviation control of UAVs

NASA Astrophysics Data System (ADS)

Cooper, Joseph L.; Goodrich, Michael A.

2006-05-01

Although advancing levels of technology allow UAV operators to give increasingly complex commands with expanding temporal scope, it is unlikely that the need for immediate situation awareness and local, short-term flight adjustment will ever be completely superseded. Local awareness and control are particularly important when the operator uses the UAV to perform a search or inspection task. There are many different tasks which would be facilitated by search and inspection capabilities of a camera-equipped UAV. These tasks range from bridge inspection and news reporting to wilderness search and rescue. The system should be simple, inexpensive, and intuitive for non-pilots. An appropriately designed interface should (a) provide a context for interpreting video and (b) support UAV tasking and control, all within a single display screen. In this paper, we present and analyze an interface that attempts to accomplish this goal. The interface utilizes a georeferenced terrain map rendered from publicly available altitude data and terrain imagery to create a context in which the location of the UAV and the source of the video are communicated to the operator. Rotated and transformed imagery from the UAV provides a stable frame of reference for the operator and integrates cleanly into the terrain model. Simple icons overlaid onto the main display provide intuitive control and feedback when necessary but fade to a semi-transparent state when not in use to avoid distracting the operator's attention from the video signal. With various interface elements integrated into a single display, the interface runs nicely on a small, portable, inexpensive system with a single display screen and simple input device, but is powerful enough to allow a single operator to deploy, control, and recover a small UAV when coupled with appropriate autonomy. As we present elements of the interface design, we will identify concepts that can be leveraged into a large class of UAV applications.

Estimating the prevalence of negative attitudes towards people with disability: a comparison of direct questioning, projective questioning and randomised response.

PubMed

Ostapczuk, Martin; Musch, Jochen

2011-01-01

Despite being susceptible to social desirability bias, attitudes towards people with disabilities are traditionally assessed via self-report. We investigated two methods presumably providing more valid prevalence estimates of sensitive attitudes than direct questioning (DQ). Most people projective questioning (MPPQ) attempts to reduce bias by asking interviewees to estimate the number of other people holding a sensitive attribute, rather than confirming or denying the attribute for themselves. The randomised-response technique (RRT) tries to reduce bias by assuring confidentiality through a random scrambling of the respondent's answers. We assessed negative attitudes towards people with physical and mental disability via MPPQ, RRT and DQ to compare the resulting estimates. The MPPQ estimates exceeded the DQ estimates. Employing a cheating-detection extension of the RRT, we determined the proportion of respondents disregarding the RRT instructions and computed an upper bound for the prevalence of negative attitudes. MPPQ estimates exceeded this upper bound and were thus shown to overestimate the prevalence. Furthermore, we found more negative attitudes towards people with mental disabilities than those with physical disabilities in all three questioning conditions. We recommend employing the cheating-detection variant of the RRT to gain additional insight in future studies on attitudes towards people with disabilities.

Three-Axis Attitude Estimation With a High-Bandwidth Angular Rate Sensor

NASA Technical Reports Server (NTRS)

Bayard, David S.; Green, Joseph J.

2013-01-01

A continuing challenge for modern instrument pointing control systems is to meet the increasingly stringent pointing performance requirements imposed by emerging advanced scientific, defense, and civilian payloads. Instruments such as adaptive optics telescopes, space interferometers, and optical communications make unprecedented demands on precision pointing capabilities. A cost-effective method was developed for increasing the pointing performance for this class of NASA applications. The solution was to develop an attitude estimator that fuses star tracker and gyro measurements with a high-bandwidth angular rotation sensor (ARS). An ARS is a rate sensor whose bandwidth extends well beyond that of the gyro, typically up to 1,000 Hz or higher. The most promising ARS sensor technology is based on a magnetohydrodynamic concept, and has recently become available commercially. The key idea is that the sensor fusion of the star tracker, gyro, and ARS provides a high-bandwidth attitude estimate suitable for supporting pointing control with a fast-steering mirror or other type of tip/tilt correction for increased performance. The ARS is relatively inexpensive and can be bolted directly next to the gyro and star tracker on the spacecraft bus. The high-bandwidth attitude estimator fuses an ARS sensor with a standard three-axis suite comprised of a gyro and star tracker. The estimation architecture is based on a dual-complementary filter (DCF) structure. The DCF takes a frequency- weighted combination of the sensors such that each sensor is most heavily weighted in a frequency region where it has the lowest noise. An important property of the DCF is that it avoids the need to model disturbance torques in the filter mechanization. This is important because the disturbance torques are generally not known in applications. This property represents an advantage over the prior art because it overcomes a weakness of the Kalman filter that arises when fusing more than one rate

Possibilities of Use of UAVS for Technical Inspection of Buildings and Constructions

NASA Astrophysics Data System (ADS)

Banaszek, Anna; Banaszek, Sebastian; Cellmer, Anna

2017-12-01

In recent years, Unmanned Aerial Vehicles (UAVs) have been used in various sectors of the economy. This is due to the development of new technologies for acquiring and processing geospatial data. The paper presents the results of experiments using UAV, equipped with a high resolution digital camera, for a visual assessment of the technical condition of the building roof and for the inventory of energy infrastructure and its surroundings. The usefulness of digital images obtained from the UAV deck is presented in concrete examples. The use of UAV offers new opportunities in the area of technical inspection due to the detail and accuracy of the data, low operating costs and fast data acquisition.

The Evaluation of GPS techniques for UAV-based Photogrammetry in Urban Area

NASA Astrophysics Data System (ADS)

Yeh, M. L.; Chou, Y. T.; Yang, L. S.

2016-06-01

The efficiency and high mobility of Unmanned Aerial Vehicle (UAV) made them essential to aerial photography assisted survey and mapping. Especially for urban land use and land cover, that they often changes, and need UAVs to obtain new terrain data and the new changes of land use. This study aims to collect image data and three dimensional ground control points in Taichung city area with Unmanned Aerial Vehicle (UAV), general camera and Real-Time Kinematic with positioning accuracy down to centimetre. The study area is an ecological park that has a low topography which support the city as a detention basin. A digital surface model was also built with Agisoft PhotoScan, and there will also be a high resolution orthophotos. There will be two conditions for this study, with or without ground control points and both were discussed and compared for the accuracy level of each of the digital surface models. According to check point deviation estimate, the model without ground control points has an average two-dimension error up to 40 centimeter, altitude error within one meter. The GCP-free RTK-airborne approach produces centimeter-level accuracy with excellent to low risk to the UAS operators. As in the case of the model with ground control points, the accuracy of x, y, z coordinates has gone up 54.62%, 49.07%, and 87.74%, and the accuracy of altitude has improved the most.

Using UAV data for soil surface change detection at a loess field plot

NASA Astrophysics Data System (ADS)

Eltner, Anette; Baumgart, Philipp

2014-05-01

Application of unmanned aerial vehicles (UAV) denotes an increasing interest in geosciences due to major developments within the last years. Today, UAV are economical, reliable and flexible in usage. They provide a non-invasive method to measure the soil surface and its changes - e.g. due to erosion - with high resolution. Advances in digital photogrammetry and computer vision allow for fast and dense digital surface reconstruction from overlapping images. The study site is located in the Saxonian loess (Germany). The area is fragile due to erodible soils and intense agricultural utilisation. Hence, detectable soil surface changes are expected. The size of the field plot is 20 x 30 meters and the period of investigation lasts from October 2012 till July 2013 at which four surveys were performed. The UAV deployed in this study is equipped with a compact camera which is attached to an active stabilising camera mount. In addition, the micro drone integrates GPS and IMU that enables autonomous surveys with programmed flight patterns. About 100 photos are needed to cover the study site at a minimal flying height of eight metres and 65%/80% image overlap. For multi-temporal comparison a stable local reference system is established. Total station control of the signalised ground control points confirms two mm accuracy for the study period. To estimate the accuracy of the digital surface models (DSM) derived from the UAV images a comparison to DSM from terrestrial laser scanning (TLS) is conducted. The standard deviation of differences amounts five millimetres. To analyse surface changes methods from image processing are applied to the DSM. Erosion rills could be extracted for quantitative and qualitative consideration. Furthermore, volumetric changes are measured. First results indicate levelling processes during the winter season and reveal rill and inter-rill erosion during spring and summer season.

Automated geographic registration and radiometric correction for UAV-based mosaics

USDA-ARS?s Scientific Manuscript database

Texas A&M University has been operating a large-scale, UAV-based, agricultural remote-sensing research project since 2015. To use UAV-based images in agricultural production, many high-resolution images must be mosaicked together to create an image of an agricultural field. Two key difficulties to s...

Searching Lost People with Uavs: the System and Results of the Close-Search Project

NASA Astrophysics Data System (ADS)

Molina, P.; Colomina, I.; Vitoria, T.; Silva, P. F.; Skaloud, J.; Kornus, W.; Prades, R.; Aguilera, C.

2012-07-01

This paper will introduce the goals, concept and results of the project named CLOSE-SEARCH, which stands for 'Accurate and safe EGNOS-SoL Navigation for UAV-based low-cost Search-And-Rescue (SAR) operations'. The main goal is to integrate a medium-size, helicopter-type Unmanned Aerial Vehicle (UAV), a thermal imaging sensor and an EGNOS-based multi-sensor navigation system, including an Autonomous Integrity Monitoring (AIM) capability, to support search operations in difficult-to-access areas and/or night operations. The focus of the paper is three-fold. Firstly, the operational and technical challenges of the proposed approach are discussed, such as ultra-safe multi-sensor navigation system, the use of combined thermal and optical vision (infrared plus visible) for person recognition and Beyond-Line-Of-Sight communications among others. Secondly, the implementation of the integrity concept for UAV platforms is discussed herein through the AIM approach. Based on the potential of the geodetic quality analysis and on the use of the European EGNOS system as a navigation performance starting point, AIM approaches integrity from the precision standpoint; that is, the derivation of Horizontal and Vertical Protection Levels (HPLs, VPLs) from a realistic precision estimation of the position parameters is performed and compared to predefined Alert Limits (ALs). Finally, some results from the project test campaigns are described to report on particular project achievements. Together with actual Search-and-Rescue teams, the system was operated in realistic, user-chosen test scenarios. In this context, and specially focusing on the EGNOS-based UAV navigation, the AIM capability and also the RGB/thermal imaging subsystem, a summary of the results is presented.

Cross Validation on the Equality of Uav-Based and Contour-Based Dems

NASA Astrophysics Data System (ADS)

Ma, R.; Xu, Z.; Wu, L.; Liu, S.

2018-04-01

Unmanned Aerial Vehicles (UAV) have been widely used for Digital Elevation Model (DEM) generation in geographic applications. This paper proposes a novel framework of generating DEM from UAV images. It starts with the generation of the point clouds by image matching, where the flight control data are used as reference for searching for the corresponding images, leading to a significant time saving. Besides, a set of ground control points (GCP) obtained from field surveying are used to transform the point clouds to the user's coordinate system. Following that, we use a multi-feature based supervised classification method for discriminating non-ground points from ground ones. In the end, we generate DEM by constructing triangular irregular networks and rasterization. The experiments are conducted in the east of Jilin province in China, which has been suffered from soil erosion for several years. The quality of UAV based DEM (UAV-DEM) is compared with that generated from contour interpolation (Contour-DEM). The comparison shows a higher resolution, as well as higher accuracy of UAV-DEMs, which contains more geographic information. In addition, the RMSE errors of the UAV-DEMs generated from point clouds with and without GCPs are ±0.5 m and ±20 m, respectively.

Assessing UAV platform types and optical sensor specifications

NASA Astrophysics Data System (ADS)

Altena, B.; Goedemé, T.

2014-05-01

Photogrammetric acquisition with unmanned aerial vehicles (UAV) has grown extensively over the last couple of years. Such mobile platforms and their processing software have matured, resulting in a market which offers off-the-shelf mapping solutions to surveying companies and geospatial enterprises. Different approaches in platform type and optical instruments exist, though its resulting products have similar specifications. To demonstrate differences in acquisitioning practice, a case study over an open mine was flown with two different off-the-shelf UAVs (a fixed-wing and a multi-rotor). The resulting imagery is analyzed to clarify the differences in collection quality. We look at image settings, and stress the fact of photographic experience if manual setting are applied. For mapping production it might be safest to set the camera on automatic. Furthermore, we try to estimate if blur is present due to image motion. A subtle trend seems to be present, for the fast flying platform though its extent is of similar order to the slow moving one. It shows both systems operate at their limits. Finally, the lens distortion is assessed with special attention to chromatic aberration. Here we see that through calibration such aberrations could be present, however detecting this phenomena directly on imagery is not straightforward. For such effects a normal lens is sufficient, though a better lens and collimator does give significant improvement.

Development of collision avoidance system for useful UAV applications using image sensors with laser transmitter

NASA Astrophysics Data System (ADS)

Cheong, M. K.; Bahiki, M. R.; Azrad, S.

2016-10-01

The main goal of this study is to demonstrate the approach of achieving collision avoidance on Quadrotor Unmanned Aerial Vehicle (QUAV) using image sensors with colour- based tracking method. A pair of high definition (HD) stereo cameras were chosen as the stereo vision sensor to obtain depth data from flat object surfaces. Laser transmitter was utilized to project high contrast tracking spot for depth calculation using common triangulation. Stereo vision algorithm was developed to acquire the distance from tracked point to QUAV and the control algorithm was designed to manipulate QUAV's response based on depth calculated. Attitude and position controller were designed using the non-linear model with the help of Optitrack motion tracking system. A number of collision avoidance flight tests were carried out to validate the performance of the stereo vision and control algorithm based on image sensors. In the results, the UAV was able to hover with fairly good accuracy in both static and dynamic collision avoidance for short range collision avoidance. Collision avoidance performance of the UAV was better with obstacle of dull surfaces in comparison to shiny surfaces. The minimum collision avoidance distance achievable was 0.4 m. The approach was suitable to be applied in short range collision avoidance.

A Robust Nonlinear Observer for Real-Time Attitude Estimation Using Low-Cost MEMS Inertial Sensors

PubMed Central

Guerrero-Castellanos, José Fermi; Madrigal-Sastre, Heberto; Durand, Sylvain; Torres, Lizeth; Muñoz-Hernández, German Ardul

2013-01-01

This paper deals with the attitude estimation of a rigid body equipped with angular velocity sensors and reference vector sensors. A quaternion-based nonlinear observer is proposed in order to fuse all information sources and to obtain an accurate estimation of the attitude. It is shown that the observer error dynamics can be separated into two passive subsystems connected in “feedback”. Then, this property is used to show that the error dynamics is input-to-state stable when the measurement disturbance is seen as an input and the error as the state. These results allow one to affirm that the observer is “robustly stable”. The proposed observer is evaluated in real-time with the design and implementation of an Attitude and Heading Reference System (AHRS) based on low-cost MEMS (Micro-Electro-Mechanical Systems) Inertial Measure Unit (IMU) and magnetic sensors and a 16-bit microcontroller. The resulting estimates are compared with a high precision motion system to demonstrate its performance. PMID:24201316

Comparison of a UAV-derived point-cloud to Lidar data at Haig Glacier, Alberta, Canada

NASA Astrophysics Data System (ADS)

Bash, E. A.; Moorman, B.; Montaghi, A.; Menounos, B.; Marshall, S. J.

2016-12-01

The use of unmanned aerial vehicles (UAVs) is expanding rapidly in glaciological research as a result of technological improvements that make UAVs a cost-effective solution for collecting high resolution datasets with relative ease. The cost and difficult access traditionally associated with performing fieldwork in glacial environments makes UAVs a particularly attractive tool. In the small, but growing, body of literature using UAVs in glaciology the accuracy of UAV data is tested through the comparison of a UAV-derived DEM to measured control points. A field campaign combining simultaneous lidar and UAV flights over Haig Glacier in April 2015, provided the unique opportunity to directly compare UAV data to lidar. The UAV was a six-propeller Mikrokopter carrying a Panasonic Lumix DMC-GF1 camera with a 12 Megapixel Live MOS sensor and Lumix G 20 mm lens flown at a height of 90 m, resulting in sub-centimetre ground resolution per image pixel. Lidar data collection took place April 20, while UAV flights were conducted April 20-21. A set of 65 control points were laid out and surveyed on the glacier surface on April 19 and 21 using a RTK GPS with a vertical uncertainty of 5 cm. A direct comparison of lidar points to these control points revealed a 9 cm offset between the control points and the lidar points on average, but the difference changed distinctly from points collected on April 19 versus those collected April 21 (7 cm and 12 cm). Agisoft Photoscan was used to create a point-cloud from imagery collected with the UAV and CloudCompare was used to calculate the difference between this and the lidar point cloud, revealing an average difference of less than 17 cm. This field campaign also highlighted some of the benefits and drawbacks of using a rotary UAV for glaciological research. The vertical takeoff and landing capabilities, combined with quick responsiveness and higher carrying capacity, make the rotary vehicle favourable for high-resolution photos when

Advantages of estimating rate corrections during dynamic propagation of spacecraft rates: Applications to real-time attitude determination of SAMPEX

NASA Technical Reports Server (NTRS)

Challa, M. S.; Natanson, G. A.; Baker, D. F.; Deutschmann, J. K.

1994-01-01

This paper describes real-time attitude determination results for the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX), a gyroless spacecraft, using a Kalman filter/Euler equation approach denoted the real-time sequential filter (RTSF). The RTSF is an extended Kalman filter whose state vector includes the attitude quaternion and corrections to the rates, which are modeled as Markov processes with small time constants. The rate corrections impart a significant robustness to the RTSF against errors in modeling the environmental and control torques, as well as errors in the initial attitude and rates, while maintaining a small state vector. SAMPLEX flight data from various mission phases are used to demonstrate the robustness of the RTSF against a priori attitude and rate errors of up to 90 deg and 0.5 deg/sec, respectively, as well as a sensitivity of 0.0003 deg/sec in estimating rate corrections in torque computations. In contrast, it is shown that the RTSF attitude estimates without the rate corrections can degrade rapidly. RTSF advantages over single-frame attitude determination algorithms are also demonstrated through (1) substantial improvements in attitude solutions during sun-magnetic field coalignment and (2) magnetic-field-only attitude and rate estimation during the spacecraft's sun-acquisition mode. A robust magnetometer-only attitude-and-rate determination method is also developed to provide for the contingency when both sun data as well as a priori knowledge of the spacecraft state are unavailable. This method includes a deterministic algorithm used to initialize the RTSF with coarse estimates of the spacecraft attitude and rates. The combined algorithm has been found effective, yielding accuracies of 1.5 deg in attitude and 0.01 deg/sec in the rates and convergence times as little as 400 sec.

An automated 3D reconstruction method of UAV images

NASA Astrophysics Data System (ADS)

Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

2015-10-01

In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

PubMed Central

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-01-01

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

PubMed

Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

2018-02-11

In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

Technologies Advance UAVs for Science, Military

NASA Technical Reports Server (NTRS)

2010-01-01

A Space Act Agreement with Goddard Space Flight Center and West Virginia University enabled Aurora Flight Sciences Corporation, of Manassas, Virginia, to develop cost-effective composite manufacturing capabilities and open a facility in West Virginia. The company now employs 160 workers at the plant, tasked with crafting airframe components for the Global Hawk unmanned aerial vehicle (UAV) program. While one third of the company's workforce focuses on Global Hawk production, the rest of the company develops advanced UAV technologies that are redefining traditional approaches to unmanned aviation. Since the company's founding, Aurora s cutting-edge work has been supported with funding from NASA's Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs.

State-Dependent Pseudo-Linear Filter for Spacecraft Attitude and Rate Estimation

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.; Harman, Richard R.

2001-01-01

This paper presents the development and performance of a special algorithm for estimating the attitude and angular rate of a spacecraft. The algorithm is a pseudo-linear Kalman filter, which is an ordinary linear Kalman filter that operates on a linear model whose matrices are current state estimate dependent. The nonlinear rotational dynamics equation of the spacecraft is presented in the state space as a state-dependent linear system. Two types of measurements are considered. One type is a measurement of the quaternion of rotation, which is obtained from a newly introduced star tracker based apparatus. The other type of measurement is that of vectors, which permits the use of a variety of vector measuring sensors like sun sensors and magnetometers. While quaternion measurements are related linearly to the state vector, vector measurements constitute a nonlinear function of the state vector. Therefore, in this paper, a state-dependent linear measurement equation is developed for the vector measurement case. The state-dependent pseudo linear filter is applied to simulated spacecraft rotations and adequate estimates of the spacecraft attitude and rate are obtained for the case of quaternion measurements as well as of vector measurements.

Cooperative Monocular-Based SLAM for Multi-UAV Systems in GPS-Denied Environments †

PubMed Central

Guerra, Edmundo

2018-01-01

This work presents a cooperative monocular-based SLAM approach for multi-UAV systems that can operate in GPS-denied environments. The main contribution of the work is to show that, using visual information obtained from monocular cameras mounted onboard aerial vehicles flying in formation, the observability properties of the whole system are improved. This fact is especially notorious when compared with other related visual SLAM configurations. In order to improve the observability properties, some measurements of the relative distance between the UAVs are included in the system. These relative distances are also obtained from visual information. The proposed approach is theoretically validated by means of a nonlinear observability analysis. Furthermore, an extensive set of computer simulations is presented in order to validate the proposed approach. The numerical simulation results show that the proposed system is able to provide a good position and orientation estimation of the aerial vehicles flying in formation. PMID:29701722

Sense and avoid technology for Global Hawk and Predator UAVs

NASA Astrophysics Data System (ADS)

McCalmont, John F.; Utt, James; Deschenes, Michael; Taylor, Michael J.

2005-05-01

The Sensors Directorate at the Air Force Research Laboratory (AFRL) along with Defense Research Associates, Inc. (DRA) conducted a flight demonstration of technology that could potentially satisfy the Federal Aviation Administration's (FAA) requirement for Unmanned Aerial Vehicles (UAVs) to sense and avoid local air traffic sufficient to provide an "...equivalent level of safety, comparable to see-and-avoid requirements for manned aircraft". This FAA requirement must be satisfied for autonomous UAV operation within the national airspace. The real-time on-board system passively detects approaching aircraft, both cooperative and non-cooperative, using imaging sensors operating in the visible/near infrared band and a passive moving target indicator algorithm. Detection range requirements for RQ-4 and MQ-9 UAVs were determined based on analysis of flight geometries, avoidance maneuver timelines, system latencies and human pilot performance. Flight data and UAV operating parameters were provided by the system program offices, prime contractors, and flight-test personnel. Flight demonstrations were conducted using a surrogate UAV (Aero Commander) and an intruder aircraft (Beech Bonanza). The system demonstrated target detection ranges out to 3 nautical miles in nose-to-nose scenarios and marginal visual meteorological conditions. (VMC) This paper will describe the sense and avoid requirements definition process and the system concept (sensors, algorithms, processor, and flight rest results) that has demonstrated the potential to satisfy the FAA sense and avoid requirements.

UAV field demonstration of social media enabled tactical data link

NASA Astrophysics Data System (ADS)

Olson, Christopher C.; Xu, Da; Martin, Sean R.; Castelli, Jonathan C.; Newman, Andrew J.

2015-05-01

This paper addresses the problem of enabling Command and Control (C2) and data exfiltration functions for missions using small, unmanned, airborne surveillance and reconnaissance platforms. The authors demonstrated the feasibility of using existing commercial wireless networks as the data transmission infrastructure to support Unmanned Aerial Vehicle (UAV) autonomy functions such as transmission of commands, imagery, metadata, and multi-vehicle coordination messages. The authors developed and integrated a C2 Android application for ground users with a common smart phone, a C2 and data exfiltration Android application deployed on-board the UAVs, and a web server with database to disseminate the collected data to distributed users using standard web browsers. The authors performed a mission-relevant field test and demonstration in which operators commanded a UAV from an Android device to search and loiter; and remote users viewed imagery, video, and metadata via web server to identify and track a vehicle on the ground. Social media served as the tactical data link for all command messages, images, videos, and metadata during the field demonstration. Imagery, video, and metadata were transmitted from the UAV to the web server via multiple Twitter, Flickr, Facebook, YouTube, and similar media accounts. The web server reassembled images and video with corresponding metadata for distributed users. The UAV autopilot communicated with the on-board Android device via on-board Bluetooth network.

Multiple Event Localization in a Sparse Acoustic Sensor Network Using UAVs as Data Mules

DTIC Science & Technology

2012-12-01

necessarily reflect the position or the policy of the Government , and no official endorsement should be inferred. Path Acoustic Sensor Communication Footprint...a Microhard radio to forward the ToAs to the mule-UAV. Two Procerus Unicorn UAVs were used with different payloads. The imaging- UAV was equipped

UAV Monitoring for Enviromental Management in Galapagos Islands

NASA Astrophysics Data System (ADS)

Ballari, D.; Orellana, D.; Acosta, E.; Espinoza, A.; Morocho, V.

2016-06-01

In the Galapagos Islands, where 97% of the territory is protected and ecosystem dynamics are highly vulnerable, timely and accurate information is key for decision making. An appropriate monitoring system must meet two key features: on one hand, being able to capture information in a systematic and regular basis, and on the other hand, to quickly gather information on demand for specific purposes. The lack of such a system for geographic information limits the ability of Galapagos Islands' institutions to evaluate and act upon environmental threats such as invasive species spread and vegetation degradation. In this context, the use of UAVs (unmanned aerial vehicles) for capturing georeferenced images is a promising technology for environmental monitoring and management. This paper explores the potential of UAV images for monitoring degradation of littoral vegetation in Puerto Villamil (Isabela Island, Galapagos, Ecuador). Imagery was captured using two camera types: Red Green Blue (RGB) and Infrarred Red Green (NIR). First, vegetation presence was identified through NDVI. Second, object-based classification was carried out for characterization of vegetation vigor. Results demonstrates the feasibility of UAV technology for base-line studies and monitoring on the amount and vigorousness of littoral vegetation in the Galapagos Islands. It is also showed that UAV images are not only useful for visual interpretation and object delineation, but also to timely produce useful thematic information for environmental management.

a Light-Weight Laser Scanner for Uav Applications

NASA Astrophysics Data System (ADS)

Tommaselli, A. M. G.; Torres, F. M.

2016-06-01

Unmanned Aerial Vehicles (UAV) have been recognized as a tool for geospatial data acquisition due to their flexibility and favourable cost benefit ratio. The practical use of laser scanning devices on-board UAVs is also developing with new experimental and commercial systems. This paper describes a light-weight laser scanning system composed of an IbeoLux scanner, an Inertial Navigation System Span-IGM-S1, from Novatel, a Raspberry PI portable computer, which records data from both systems and an octopter UAV. The performance of this light-weight system was assessed both for accuracy and with respect to point density, using Ground Control Points (GCP) as reference. Two flights were performed with the UAV octopter carrying the equipment. In the first trial, the flight height was 100 m with six strips over a parking area. The second trial was carried out over an urban park with some buildings and artificial targets serving as reference Ground Control Points. In this experiment a flight height of 70 m was chosen to improve target response. Accuracy was assessed based on control points the coordinates of which were measured in the field. Results showed that vertical accuracy with this prototype is around 30 cm, which is acceptable for forest applications but this accuracy can be improved using further refinements in direct georeferencing and in the system calibration.

Position-adaptive explosive detection concepts for swarming micro-UAVs

NASA Astrophysics Data System (ADS)

Selmic, Rastko R.; Mitra, Atindra

2008-04-01

We have formulated a series of position-adaptive sensor concepts for explosive detection applications using swarms of micro-UAV's. These concepts are a generalization of position-adaptive radar concepts developed for challenging conditions such as urban environments. For radar applications, this concept is developed with platforms within a UAV swarm that spatially-adapt to signal leakage points on the perimeter of complex clutter environments to collect information on embedded objects-of-interest. The concept is generalized for additional sensors applications by, for example, considering a wooden cart that contains explosives. We can formulate system-of-systems concepts for a swarm of micro-UAV's in an effort to detect whether or not a given cart contains explosives. Under this new concept, some of the members of the UAV swarm can serve as position-adaptive "transmitters" by blowing air over the cart and some of the members of the UAV swarm can serve as position-adaptive "receivers" that are equipped with chem./bio sensors that function as "electronic noses". The final objective can be defined as improving the particle count for the explosives in the air that surrounds a cart via development of intelligent position-adaptive control algorithms in order to improve the detection and false-alarm statistics. We report on recent simulation results with regard to designing optimal sensor placement for explosive or other chemical agent detection. This type of information enables the development of intelligent control algorithms for UAV swarm applications and is intended for the design of future system-of-systems with adaptive intelligence for advanced surveillance of unknown regions. Results are reported as part of a parametric investigation where it is found that the probability of contaminant detection depends on the air flow that carries contaminant particles, geometry of the surrounding space, leakage areas, and other factors. We present a concept of position

Automatic detection of blurred images in UAV image sets

NASA Astrophysics Data System (ADS)

Sieberth, Till; Wackrow, Rene; Chandler, Jim H.

2016-12-01

Unmanned aerial vehicles (UAV) have become an interesting and active research topic for photogrammetry. Current research is based on images acquired by an UAV, which have a high ground resolution and good spectral and radiometrical resolution, due to the low flight altitudes combined with a high resolution camera. UAV image flights are also cost effective and have become attractive for many applications including, change detection in small scale areas. One of the main problems preventing full automation of data processing of UAV imagery is the degradation effect of blur caused by camera movement during image acquisition. This can be caused by the normal flight movement of the UAV as well as strong winds, turbulence or sudden operator inputs. This blur disturbs the visual analysis and interpretation of the data, causes errors and can degrade the accuracy in automatic photogrammetric processing algorithms. The detection and removal of these images is currently achieved manually, which is both time consuming and prone to error, particularly for large image-sets. To increase the quality of data processing an automated process is necessary, which must be both reliable and quick. This paper describes the development of an automatic filtering process, which is based upon the quantification of blur in an image. Images with known blur are processed digitally to determine a quantifiable measure of image blur. The algorithm is required to process UAV images fast and reliably to relieve the operator from detecting blurred images manually. The newly developed method makes it possible to detect blur caused by linear camera displacement and is based on human detection of blur. Humans detect blurred images best by comparing it to other images in order to establish whether an image is blurred or not. The developed algorithm simulates this procedure by creating an image for comparison using image processing. Creating internally a comparable image makes the method independent of

Magnetic dipole moment estimation and compensation for an accurate attitude control in nano-satellite missions

NASA Astrophysics Data System (ADS)

Inamori, Takaya; Sako, Nobutada; Nakasuka, Shinichi

2011-06-01

Nano-satellites provide space access to broader range of satellite developers and attract interests as an application of the space developments. These days several new nano-satellite missions are proposed with sophisticated objectives such as remote-sensing and observation of astronomical objects. In these advanced missions, some nano-satellites must meet strict attitude requirements for obtaining scientific data or images. For LEO nano-satellite, a magnetic attitude disturbance dominates over other environmental disturbances as a result of small moment of inertia, and this effect should be cancelled for a precise attitude control. This research focuses on how to cancel the magnetic disturbance in orbit. This paper presents a unique method to estimate and compensate the residual magnetic moment, which interacts with the geomagnetic field and causes the magnetic disturbance. An extended Kalman filter is used to estimate the magnetic disturbance. For more practical considerations of the magnetic disturbance compensation, this method has been examined in the PRISM (Pico-satellite for Remote-sensing and Innovative Space Missions). This method will be also used for a nano-astrometry satellite mission. This paper concludes that use of the magnetic disturbance estimation and compensation are useful for nano-satellites missions which require a high accurate attitude control.

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow

PubMed Central

Zhang, Weilong; Guo, Bingxuan; Liao, Xuan; Li, Wenzhuo

2018-01-01

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images. PMID:29659526

Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.

PubMed

Zhang, Weilong; Guo, Bingxuan; Li, Ming; Liao, Xuan; Li, Wenzhuo

2018-04-16

Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

Swarming Unmanned Aerial Vehicles (UAVS): Extending Marine Aviation Ground Task Force Communications Using UAVS

DTIC Science & Technology

2015-03-02

balloons , large UAVs, and satellite communications are all employed to mitigate LOS and OTH communication on the battlefield. The Marine Corps’ fleets...Phang, N. S. (2006). Tethered operation of autonomous aerial vehicles to provide extended fields of view for autonomous ground vehicles (Master’s

An Empirical Comparison between Two Recursive Filters for Attitude and Rate Estimation of Spinning Spacecraft

NASA Technical Reports Server (NTRS)

Harman, Richard R.

2006-01-01

The advantages of inducing a constant spin rate on a spacecraft are well known. A variety of science missions have used this technique as a relatively low cost method for conducting science. Starting in the late 1970s, NASA focused on building spacecraft using 3-axis control as opposed to the single-axis control mentioned above. Considerable effort was expended toward sensor and control system development, as well as the development of ground systems to independently process the data. As a result, spinning spacecraft development and their resulting ground system development stagnated. In the 1990s, shrinking budgets made spinning spacecraft an attractive option for science. The attitude requirements for recent spinning spacecraft are more stringent and the ground systems must be enhanced in order to provide the necessary attitude estimation accuracy. Since spinning spacecraft (SC) typically have no gyroscopes for measuring attitude rate, any new estimator would need to rely on the spacecraft dynamics equations. One estimation technique that utilized the SC dynamics and has been used successfully in 3-axis gyro-less spacecraft ground systems is the pseudo-linear Kalman filter algorithm. Consequently, a pseudo-linear Kalman filter has been developed which directly estimates the spacecraft attitude quaternion and rate for a spinning SC. Recently, a filter using Markley variables was developed specifically for spinning spacecraft. The pseudo-linear Kalman filter has the advantage of being easier to implement but estimates the quaternion which, due to the relatively high spinning rate, changes rapidly for a spinning spacecraft. The Markley variable filter is more complicated to implement but, being based on the SC angular momentum, estimates parameters which vary slowly. This paper presents a comparison of the performance of these two filters. Monte-Carlo simulation runs will be presented which demonstrate the advantages and disadvantages of both filters.

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) and its operations from an unmanned aerial vehicle (UAV) during the AROMAT campaign

NASA Astrophysics Data System (ADS)

Merlaud, Alexis; Tack, Frederik; Constantin, Daniel; Georgescu, Lucian; Maes, Jeroen; Fayt, Caroline; Mingireanu, Florin; Schuettemeyer, Dirk; Meier, Andreas Carlos; Schönardt, Anja; Ruhtz, Thomas; Bellegante, Livio; Nicolae, Doina; Den Hoed, Mirjam; Allaart, Marc; Van Roozendael, Michel

2018-01-01

The Small Whiskbroom Imager for atmospheric compositioN monitorinG (SWING) is a compact remote sensing instrument dedicated to mapping trace gases from an unmanned aerial vehicle (UAV). SWING is based on a compact visible spectrometer and a scanning mirror to collect scattered sunlight. Its weight, size, and power consumption are respectively 920 g, 27 cm × 12 cm × 8 cm, and 6 W. SWING was developed in parallel with a 2.5 m flying-wing UAV. This unmanned aircraft is electrically powered, has a typical airspeed of 100 km h-1, and can operate at a maximum altitude of 3 km. We present SWING-UAV experiments performed in Romania on 11 September 2014 during the Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaign, which was dedicated to test newly developed instruments in the context of air quality satellite validation. The UAV was operated up to 700 m above ground, in the vicinity of the large power plant of Turceni (44.67° N, 23.41° E; 116 m a. s. l. ). These SWING-UAV flights were coincident with another airborne experiment using the Airborne imaging differential optical absorption spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP), and with ground-based DOAS, lidar, and balloon-borne in situ observations. The spectra recorded during the SWING-UAV flights are analysed with the DOAS technique. This analysis reveals NO2 differential slant column densities (DSCDs) up to 13±0.6×1016 molec cm-2. These NO2 DSCDs are converted to vertical column densities (VCDs) by estimating air mass factors. The resulting NO2 VCDs are up to 4.7±0.4×1016 molec cm-2. The water vapour DSCD measurements, up to 8±0.15×1022 molec cm-2, are used to estimate a volume mixing ratio of water vapour in the boundary layer of 0.013±0.002 mol mol-1. These geophysical quantities are validated with the coincident measurements.

NASA Earth Science Research and Applications Using UAVs

NASA Technical Reports Server (NTRS)

Guillory, Anthony R.

2003-01-01

The NASA Earth Science Enterprise sponsored the UAV Science Demonstration Project, which funded two projects: the Altus Cumulus Electrification Study (ACES) and the UAV Coffee Harvest Optimization experiment. These projects were intended to begin a process of integrating UAVs into the mainstream of NASA s airborne Earth Science Research and Applications programs. The Earth Science Enterprise is moving forward given the positive science results of these demonstration projects to incorporate more platforms with additional scientific utility into the program and to look toward a horizon where the current piloted aircraft may not be able to carry out the science objectives of a mission. Longer duration, extended range, slower aircraft speed, etc. all have scientific advantages in many of the disciplines within Earth Science. The challenge we now face are identifying those capabilities that exist and exploiting them while identifying the gaps. This challenge has two facets: the engineering aspects of redesigning or modifying sensors and a paradigm shift by the scientists.

Application of GIS-based models for delineating the UAV flight region to support Search and Rescue activities

NASA Astrophysics Data System (ADS)

Jurecka, Miroslawa; Niedzielski, Tomasz

2017-04-01

The objective of the approach presented in this paper is to demonstrate a potential of using the combination of two GIS-based models - mobility model and ring model - for delineating a region above which an Unmanned Aerial Vehicle (UAV) should fly to support the Search and Rescue (SAR) activities. The procedure is based on two concepts, both describing a possible distance/path that lost person could travel from the initial planning point (being either the point last seen, or point last known). The first approach (the ring model) takes into account the crow's flight distance traveled by a lost person and its probability distribution. The second concept (the mobility model) is based on the estimated travel speed and the associated features of the geographical environment of the search area. In contrast to the ring model covering global (hence more general) SAR perspective, the mobility model represents regional viewpoint by taking into consideration local impedance. Both models working together can serve well as a starting point for the UAV flight planning to strengthen the SAR procedures. We present the method of combining the two above-mentioned models in order to delineate UAVs flight region and increase the Probability of Success for future SAR missions. The procedure is a part of a larger Search and Rescue (SAR) system which is being developed at the University of Wrocław, Poland (research project no. IP2014 032773 financed by the Ministry of Science and Higher Education of Poland). The mobility and ring models have been applied to the Polish territory, and they act in concert to provide the UAV operator with the optimal search region. This is attained in real time so that the UAV-based SAR mission can be initiated quickly.

An Ecological Approach to the Design of UAV Ground Control Station (GCS) Status Displays

NASA Technical Reports Server (NTRS)

Dowell, Susan; Morphew, Ephimia; Shively, Jay

2003-01-01

Use of UAVs in military and commercial applications will continue to increase. However, there has been limited research devoted to UAV GCS design. The current study employed an ecological approach to interfac e design. Ecological Interface Design (EID) can be characterized as r epresenting the properties of a system, such that an operator is enco uraged to use skill-based behavior when problem solving. When more ef fortful cognitive processes become necessary due to unfamiliar situations, the application of EID philosophy supports the application of kn owledge-based behavior. With advances toward multiple UAV command and control, operators need GCS interfaces designed to support understan ding of complex systems. We hypothesized that use of EID principles f or the display of UAV status information would result in better opera tor performance and situational awareness, while decreasing workload. Pilots flew a series of missions with three UAV GCS displays of statu s information (Alphanumeric, Ecological, and Hybrid display format). Measures of task performance, Situational Awareness, and workload dem onstrated the benefits of using an ecological approach to designing U AV GCS displays. The application of ecological principles to the design of UAV GCSs is a promising area for improving UAV operations.

Preliminary Study on Earthquake Surface Rupture Extraction from Uav Images

NASA Astrophysics Data System (ADS)

Yuan, X.; Wang, X.; Ding, X.; Wu, X.; Dou, A.; Wang, S.

2018-04-01

Because of the advantages of low-cost, lightweight and photography under the cloud, UAVs have been widely used in the field of seismic geomorphology research in recent years. Earthquake surface rupture is a typical seismic tectonic geomorphology that reflects the dynamic and kinematic characteristics of crustal movement. The quick identification of earthquake surface rupture is of great significance for understanding the mechanism of earthquake occurrence, disasters distribution and scale. Using integrated differential UAV platform, series images were acquired with accuracy POS around the former urban area (Qushan town) of Beichuan County as the area stricken seriously by the 2008 Wenchuan Ms8.0 earthquake. Based on the multi-view 3D reconstruction technique, the high resolution DSM and DOM are obtained from differential UAV images. Through the shade-relief map and aspect map derived from DSM, the earthquake surface rupture is extracted and analyzed. The results show that the surface rupture can still be identified by using the UAV images although the time of earthquake elapse is longer, whose middle segment is characterized by vertical movement caused by compression deformation from fault planes.

Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics

DTIC Science & Technology

2016-09-15

Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined

Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform

PubMed Central

Bai, Guanbing; Liu, Jinghong; Song, Yueming; Zuo, Yujia

2017-01-01

To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σB=1.63×10−4 (°), σL=1.35×10−4 (°), σH=15.8 (m), σsum=27.6 (m), where σB represents the longitude error, σL represents the latitude error, σH represents the altitude error, and σsum represents the error radius. PMID:28067814

UAV-LiDAR accuracy and comparison to Structure from Motion photogrammetry

NASA Astrophysics Data System (ADS)

Kucharczyk, M.; Hugenholtz, C.; Zou, X.; Nesbit, P. R.; Barchyn, T.

2016-12-01

We compare the spatial accuracy of a UAV-LiDAR system with Structure from Motion (SfM) photogrammetry. UAV-based LiDAR remote sensing potentially offers advantages over SfM photogrammetry in vegetated terrain, particularly with respect to canopy penetration and related measurements of ground surface elevation and vegetation height; however, little quantitative evidence has been presented to date. To address this, we performed a case study at a field site in Alberta, Canada with six different land cover types: short grass, tall grass, short shrubs, tall shrubs, deciduous trees, and coniferous trees. Both UAV datasets were acquired on the same day. The SfM dataset was derived from images acquired by a senseFly eBee fixed-wing UAV equipped with a 16.1 megapixel RGB camera. The UAV-LiDAR system is a proprietary design that consists of a single-rotor helicopter (2-m rotor diameter) equipped with a Riegl VUX-1UAV laser scanner, KVH 1750 inertial measurement unit, and dual NovAtel GNSS receivers. We measured vegetation height from at least 30 samples in each land cover type and acquired check point measurements to determine horizontal and vertical accuracy. Vegetation height was measured manually for grasses and shrubs with a level staff, and with a total station for trees. Coordinates of horizontal and vertical check points were surveyed with real-time kinematic (RTK) GNSS. We followed standard methods for computing horizontal and vertical accuracies based on the 2015 guidelines from the American Society of Photogrammetry and Remote Sensing. Results will be presented at the AGU Fall Meeting.

Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform.

PubMed

Bai, Guanbing; Liu, Jinghong; Song, Yueming; Zuo, Yujia

2017-01-06

To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σ B = 1.63 × 10 - 4 ( ° ) , σ L = 1.35 × 10 - 4 ( ° ) , σ H = 15.8 ( m ) , σ s u m = 27.6 ( m ) , where σ B represents the longitude error, σ L represents the latitude error, σ H represents the altitude error, and σ s u m represents the error radius.

A novel unscented predictive filter for relative position and attitude estimation of satellite formation

NASA Astrophysics Data System (ADS)

Cao, Lu; Chen, Xiaoqian; Misra, Arun K.

2015-07-01

This paper presents a novel sigma-point unscented predictive filter (UPF) for relative position and attitude estimation of satellite formation taking into account the influence of J2. A coupled relative translational dynamics model is formulated to represent orbital motion of arbitrary feature points on the deputy spacecraft, and the relative attitude motion is formulated by considering a rotational dynamics for a satellite without gyros. Based on the proposed coupled dynamic model, the UPF is developed based on unscented transformation technique, extending the capability of a traditional predictive filter (PF). The algorithm flow of the UPF is described first. Then it is demonstrated that the estimation accuracy of the model error and system state for UPF is higher than that of the traditional PF. In addition, the unscented Kalman filter (UKF) is also employed in order to compare the performance of the proposed UPF with that of the UKF. Several different scenarios are simulated to validate the effectiveness of the coupled dynamics model and the performance of the proposed UPF. Through comparisons, the proposed UPF is shown to yield highly accurate estimation of relative position and attitude during satellite formation flying.

Quality Analysis on 3d Buidling Models Reconstructed from Uav Imagery

NASA Astrophysics Data System (ADS)

Jarzabek-Rychard, M.; Karpina, M.

2016-06-01

Recent developments in UAV technology and structure from motion techniques have effected that UAVs are becoming standard platforms for 3D data collection. Because of their flexibility and ability to reach inaccessible urban parts, drones appear as optimal solution for urban applications. Building reconstruction from the data collected with UAV has the important potential to reduce labour cost for fast update of already reconstructed 3D cities. However, especially for updating of existing scenes derived from different sensors (e.g. airborne laser scanning), a proper quality assessment is necessary. The objective of this paper is thus to evaluate the potential of UAV imagery as an information source for automatic 3D building modeling at LOD2. The investigation process is conducted threefold: (1) comparing generated SfM point cloud to ALS data; (2) computing internal consistency measures of the reconstruction process; (3) analysing the deviation of Check Points identified on building roofs and measured with a tacheometer. In order to gain deep insight in the modeling performance, various quality indicators are computed and analysed. The assessment performed according to the ground truth shows that the building models acquired with UAV-photogrammetry have the accuracy of less than 18 cm for the plannimetric position and about 15 cm for the height component.

UAV Deployment Exercise for Mapping Purposes: Evaluation of Emergency Response Applications

PubMed Central

Boccardo, Piero; Chiabrando, Filiberto; Dutto, Furio; Giulio Tonolo, Fabio; Lingua, Andrea

2015-01-01

Exploiting the decrease of costs related to UAV technology, the humanitarian community started piloting the use of similar systems in humanitarian crises several years ago in different application fields, i.e., disaster mapping and information gathering, community capacity building, logistics and even transportation of goods. Part of the author’s group, composed of researchers in the field of applied geomatics, has been piloting the use of UAVs since 2006, with a specific focus on disaster management application. In the framework of such activities, a UAV deployment exercise was jointly organized with the Regional Civil Protection authority, mainly aimed at assessing the operational procedures to deploy UAVs for mapping purposes and the usability of the acquired data in an emergency response context. In the paper the technical features of the UAV platforms will be described, comparing the main advantages/disadvantages of fixed-wing versus rotor platforms. The main phases of the adopted operational procedure will be discussed and assessed especially in terms of time required to carry out each step, highlighting potential bottlenecks and in view of the national regulation framework, which is rapidly evolving. Different methodologies for the processing of the acquired data will be described and discussed, evaluating the fitness for emergency response applications. PMID:26147728

UAV Deployment Exercise for Mapping Purposes: Evaluation of Emergency Response Applications.

PubMed

Boccardo, Piero; Chiabrando, Filiberto; Dutto, Furio; Tonolo, Fabio Giulio; Lingua, Andrea

2015-07-02

Exploiting the decrease of costs related to UAV technology, the humanitarian community started piloting the use of similar systems in humanitarian crises several years ago in different application fields, i.e., disaster mapping and information gathering, community capacity building, logistics and even transportation of goods. Part of the author's group, composed of researchers in the field of applied geomatics, has been piloting the use of UAVs since 2006, with a specific focus on disaster management application. In the framework of such activities, a UAV deployment exercise was jointly organized with the Regional Civil Protection authority, mainly aimed at assessing the operational procedures to deploy UAVs for mapping purposes and the usability of the acquired data in an emergency response context. In the paper the technical features of the UAV platforms will be described, comparing the main advantages/disadvantages of fixed-wing versus rotor platforms. The main phases of the adopted operational procedure will be discussed and assessed especially in terms of time required to carry out each step, highlighting potential bottlenecks and in view of the national regulation framework, which is rapidly evolving. Different methodologies for the processing of the acquired data will be described and discussed, evaluating the fitness for emergency response applications.

Image-based tracking and sensor resource management for UAVs in an urban environment

NASA Astrophysics Data System (ADS)

Samant, Ashwin; Chang, K. C.

2010-04-01

Coordination and deployment of multiple unmanned air vehicles (UAVs) requires a lot of human resources in order to carry out a successful mission. The complexity of such a surveillance mission is significantly increased in the case of an urban environment where targets can easily escape from the UAV's field of view (FOV) due to intervening building and line-of-sight obstruction. In the proposed methodology, we focus on the control and coordination of multiple UAVs having gimbaled video sensor onboard for tracking multiple targets in an urban environment. We developed optimal path planning algorithms with emphasis on dynamic target prioritizations and persistent target updates. The command center is responsible for target prioritization and autonomous control of multiple UAVs, enabling a single operator to monitor and control a team of UAVs from a remote location. The results are obtained using extensive 3D simulations in Google Earth using Tangent plus Lyapunov vector field guidance for target tracking.

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments

PubMed Central

Vanegas, Fernando; Gonzalez, Felipe

2016-01-01

Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP), so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV), to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios. PMID:27171096

Enabling UAV Navigation with Sensor and Environmental Uncertainty in Cluttered and GPS-Denied Environments.

PubMed

Vanegas, Fernando; Gonzalez, Felipe

2016-05-10

Unmanned Aerial Vehicles (UAV) can navigate with low risk in obstacle-free environments using ground control stations that plan a series of GPS waypoints as a path to follow. This GPS waypoint navigation does however become dangerous in environments where the GPS signal is faulty or is only present in some places and when the airspace is filled with obstacles. UAV navigation then becomes challenging because the UAV uses other sensors, which in turn generate uncertainty about its localisation and motion systems, especially if the UAV is a low cost platform. Additional uncertainty affects the mission when the UAV goal location is only partially known and can only be discovered by exploring and detecting a target. This navigation problem is established in this research as a Partially-Observable Markov Decision Process (POMDP), so as to produce a policy that maps a set of motion commands to belief states and observations. The policy is calculated and updated on-line while flying with a newly-developed system for UAV Uncertainty-Based Navigation (UBNAV), to navigate in cluttered and GPS-denied environments using observations and executing motion commands instead of waypoints. Experimental results in both simulation and real flight tests show that the UAV finds a path on-line to a region where it can explore and detect a target without colliding with obstacles. UBNAV provides a new method and an enabling technology for scientists to implement and test UAV navigation missions with uncertainty where targets must be detected using on-line POMDP in real flight scenarios.

Uav Photogrammetry: a Practical Solution for Challenging Mapping Projects

NASA Astrophysics Data System (ADS)

Saadatseresht, M.; Hashempour, A. H.; Hasanlou, M.

2015-12-01

We have observed huge attentions to application of unmanned aerial vehicle (UAV) in aerial mapping since a decade ago. Though, it has several advantages for handling time/cost/quality issues, there are a dozen of challenges in working with UAVs. In this paper, we; as the Robotic Photogrammetry Research Group (RPRG), will firstly review these challenges then show its advantages in three special practical projects. For each project, we will share our experiences through description of the UAV specifications, flight settings and processing steps. At the end, we will illustrate final result of each project and show how this technology could make unbelievable benefits to clients including 3D city realistic model in decimetre level, ultra high quality map production in several centimetre level, and accessing to a high risk and rough relief area for mapping aims.

Autonomous mission management for UAVs using soar intelligent agents

NASA Astrophysics Data System (ADS)

Gunetti, Paolo; Thompson, Haydn; Dodd, Tony

2013-05-01

State-of-the-art unmanned aerial vehicles (UAVs) are typically able to autonomously execute a pre-planned mission. However, UAVs usually fly in a very dynamic environment which requires dynamic changes to the flight plan; this mission management activity is usually tasked to human supervision. Within this article, a software system that autonomously accomplishes the mission management task for a UAV will be proposed. The system is based on a set of theoretical concepts which allow the description of a flight plan and implemented using a combination of Soar intelligent agents and traditional control techniques. The system is capable of automatically generating and then executing an entire flight plan after being assigned a set of objectives. This article thoroughly describes all system components and then presents the results of tests that were executed using a realistic simulation environment.

Low cost infrared and near infrared sensors for UAVs

NASA Astrophysics Data System (ADS)

Aden, S. T.; Bialas, J. P.; Champion, Z.; Levin, E.; McCarty, J. L.

2014-11-01

Thermal remote sensing has a wide range of applications, though the extent of its use is inhibited by cost. Robotic and computer components are now widely available to consumers on a scale that makes thermal data a readily accessible resource. In this project, thermal imagery collected via a lightweight remote sensing Unmanned Aerial Vehicle (UAV) was used to create a surface temperature map for the purpose of providing wildland firefighting crews with a cost-effective and time-saving resource. The UAV system proved to be flexible, allowing for customized sensor packages to be designed that could include visible or infrared cameras, GPS, temperature sensors, and rangefinders, in addition to many data management options. Altogether, such a UAV system could be used to rapidly collect thermal and aerial data, with a geographic accuracy of less than one meter.

Wavelength-Adaptive Dehazing Using Histogram Merging-Based Classification for UAV Images

PubMed Central

Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

2015-01-01

Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results. PMID:25808767

Augmented Reality Tool for the Situational Awareness Improvement of UAV Operators.

PubMed

Ruano, Susana; Cuevas, Carlos; Gallego, Guillermo; García, Narciso

2017-02-06

Unmanned Aerial Vehicles (UAVs) are being extensively used nowadays. Therefore, pilots of traditional aerial platforms should adapt their skills to operate them from a Ground Control Station (GCS). Common GCSs provide information in separate screens: one presents the video stream while the other displays information about the mission plan and information coming from other sensors. To avoid the burden of fusing information displayed in the two screens, an Augmented Reality (AR) tool is proposed in this paper. The AR system has two functionalities for Medium-Altitude Long-Endurance (MALE) UAVs: route orientation and target identification. Route orientation allows the operator to identify the upcoming waypoints and the path that the UAV is going to follow. Target identification allows a fast target localization, even in the presence of occlusions. The AR tool is implemented following the North Atlantic Treaty Organization (NATO) standards so that it can be used in different GCSs. The experiments show how the AR tool improves significantly the situational awareness of the UAV operators.

Wavelength-adaptive dehazing using histogram merging-based classification for UAV images.

PubMed

Yoon, Inhye; Jeong, Seokhwa; Jeong, Jaeheon; Seo, Doochun; Paik, Joonki

2015-03-19

Since incoming light to an unmanned aerial vehicle (UAV) platform can be scattered by haze and dust in the atmosphere, the acquired image loses the original color and brightness of the subject. Enhancement of hazy images is an important task in improving the visibility of various UAV images. This paper presents a spatially-adaptive dehazing algorithm that merges color histograms with consideration of the wavelength-dependent atmospheric turbidity. Based on the wavelength-adaptive hazy image acquisition model, the proposed dehazing algorithm consists of three steps: (i) image segmentation based on geometric classes; (ii) generation of the context-adaptive transmission map; and (iii) intensity transformation for enhancing a hazy UAV image. The major contribution of the research is a novel hazy UAV image degradation model by considering the wavelength of light sources. In addition, the proposed transmission map provides a theoretical basis to differentiate visually important regions from others based on the turbidity and merged classification results.

INITIAL ASSESSMENT OF SURFACE PRESSURE CHARACTERISTICS OF TWO ROTARY WING UAV DESIGNS

NASA Technical Reports Server (NTRS)

Jones, Henry E.; Wong, Oliver D.; Watkins, A. Neal; Noonan, Kevin W.; Reis, Deane G.; Malovrh, Brendon D.; Ingram, Joanne L.

2006-01-01

This paper presents results of an experimental investigation of two rotary-wing UAV designs. The primary goal of the investigation was to provide a set of interactional aerodynamic data for an emerging class of rotorcraft. The present paper provides an overview of the test and an introduction to the test articles, and instrumentation. Sample data in the form of fixed system pressure coefficient response to changes in configuration attitude and flight condition for both rotor off and on conditions are presented. The presence of the rotor is seen to greatly affect the magnitude of the response. Pressure coefficients were measured using both conventional pressure taps and via pressure sensitive paint. Comparisons between the two methods are presented and demonstrate that the pressure sensitive paint is a promising method; however, further work on the technique is required.

Semiautonomous Avionics-and-Sensors System for a UAV

NASA Technical Reports Server (NTRS)

Shams, Qamar

2006-01-01

Unmanned Aerial Vehicles (UAVs) autonomous or remotely controlled pilotless aircraft have been recently thrust into the spotlight for military applications, for homeland security, and as test beds for research. In addition to these functions, there are many space applications in which lightweight, inexpensive, small UAVS can be used e.g., to determine the chemical composition and other qualities of the atmospheres of remote planets. Moreover, on Earth, such UAVs can be used to obtain information about weather in various regions; in particular, they can be used to analyze wide-band acoustic signals to aid in determining the complex dynamics of movement of hurricanes. The Advanced Sensors and Electronics group at Langley Research Center has developed an inexpensive, small, integrated avionics-and-sensors system to be installed in a UAV that serves two purposes. The first purpose is to provide flight data to an AI (Artificial Intelligence) controller as part of an autonomous flight-control system. The second purpose is to store data from a subsystem of distributed MEMS (microelectromechanical systems) sensors. Examples of these MEMS sensors include humidity, temperature, and acoustic sensors, plus chemical sensors for detecting various vapors and other gases in the environment. The critical sensors used for flight control are a differential- pressure sensor that is part of an apparatus for determining airspeed, an absolute-pressure sensor for determining altitude, three orthogonal accelerometers for determining tilt and acceleration, and three orthogonal angular-rate detectors (gyroscopes). By using these eight sensors, it is possible to determine the orientation, height, speed, and rates of roll, pitch, and yaw of the UAV. This avionics-and-sensors system is shown in the figure. During the last few years, there has been rapid growth and advancement in the technological disciplines of MEMS, of onboard artificial-intelligence systems, and of smaller, faster, and

High-Precision Attitude Estimation Method of Star Sensors and Gyro Based on Complementary Filter and Unscented Kalman Filter

NASA Astrophysics Data System (ADS)

Guo, C.; Tong, X.; Liu, S.; Liu, S.; Lu, X.; Chen, P.; Jin, Y.; Xie, H.

2017-07-01

Determining the attitude of satellite at the time of imaging then establishing the mathematical relationship between image points and ground points is essential in high-resolution remote sensing image mapping. Star tracker is insensitive to the high frequency attitude variation due to the measure noise and satellite jitter, but the low frequency attitude motion can be determined with high accuracy. Gyro, as a short-term reference to the satellite's attitude, is sensitive to high frequency attitude change, but due to the existence of gyro drift and integral error, the attitude determination error increases with time. Based on the opposite noise frequency characteristics of two kinds of attitude sensors, this paper proposes an on-orbit attitude estimation method of star sensors and gyro based on Complementary Filter (CF) and Unscented Kalman Filter (UKF). In this study, the principle and implementation of the proposed method are described. First, gyro attitude quaternions are acquired based on the attitude kinematics equation. An attitude information fusion method is then introduced, which applies high-pass filtering and low-pass filtering to the gyro and star tracker, respectively. Second, the attitude fusion data based on CF are introduced as the observed values of UKF system in the process of measurement updating. The accuracy and effectiveness of the method are validated based on the simulated sensors attitude data. The obtained results indicate that the proposed method can suppress the gyro drift and measure noise of attitude sensors, improving the accuracy of the attitude determination significantly, comparing with the simulated on-orbit attitude and the attitude estimation results of the UKF defined by the same simulation parameters.

Unscented predictive variable structure filter for satellite attitude estimation with model errors when using low precision sensors

NASA Astrophysics Data System (ADS)

Cao, Lu; Li, Hengnian

2016-10-01

For the satellite attitude estimation problem, the serious model errors always exist and hider the estimation performance of the Attitude Determination and Control System (ACDS), especially for a small satellite with low precision sensors. To deal with this problem, a new algorithm for the attitude estimation, referred to as the unscented predictive variable structure filter (UPVSF) is presented. This strategy is proposed based on the variable structure control concept and unscented transform (UT) sampling method. It can be implemented in real time with an ability to estimate the model errors on-line, in order to improve the state estimation precision. In addition, the model errors in this filter are not restricted only to the Gaussian noises; therefore, it has the advantages to deal with the various kinds of model errors or noises. It is anticipated that the UT sampling strategy can further enhance the robustness and accuracy of the novel UPVSF. Numerical simulations show that the proposed UPVSF is more effective and robustness in dealing with the model errors and low precision sensors compared with the traditional unscented Kalman filter (UKF).

Evaluating the effectiveness of low cost UAV generated topography for geomorphic change detection

NASA Astrophysics Data System (ADS)

Cook, K. L.

2014-12-01

With the recent explosion in the use and availability of unmanned aerial vehicle platforms and development of easy to use structure from motion software, UAV based photogrammetry is increasingly being adopted to produce high resolution topography for the study of surface processes. UAV systems can vary substantially in price and complexity, but the tradeoffs between these and the quality of the resulting data are not well constrained. We look at one end of this spectrum and evaluate the effectiveness of a simple low cost UAV setup for obtaining high resolution topography in a challenging field setting. Our study site is the Daan River gorge in western Taiwan, a rapidly eroding bedrock gorge that we have monitored with terrestrial Lidar since 2009. The site presents challenges for the generation and analysis of high resolution topography, including vertical gorge walls, vegetation, wide variation in surface roughness, and a complicated 3D morphology. In order to evaluate the accuracy of the UAV-derived topography, we compare it with terrestrial Lidar data collected during the same survey period. Our UAV setup combines a DJI Phantom 2 quadcopter with a 16 megapixel Canon Powershot camera for a total platform cost of less than $850. The quadcopter is flown manually, and the camera is programmed to take a photograph every 5 seconds, yielding 200-250 pictures per flight. We measured ground control points and targets for both the Lidar scans and the aerial surveys using a Leica RTK GPS with 1-2 cm accuracy. UAV derived point clouds were obtained using Agisoft Photoscan software. We conducted both Lidar and UAV surveys before and after a summer typhoon season, allowing us to evaluate the reliability of the UAV survey to detect geomorphic changes in the range of one to several meters. We find that this simple UAV setup can yield point clouds with an average accuracy on the order of 10 cm compared to the Lidar point clouds. Well-distributed and accurately located ground

Kalman Filter Estimation of Spinning Spacecraft Attitude using Markley Variables

NASA Technical Reports Server (NTRS)

Sedlak, Joseph E.; Harman, Richard

2004-01-01

There are several different ways to represent spacecraft attitude and its time rate of change. For spinning or momentum-biased spacecraft, one particular representation has been put forward as a superior parameterization for numerical integration. Markley has demonstrated that these new variables have fewer rapidly varying elements for spinning spacecraft than other commonly used representations and provide advantages when integrating the equations of motion. The current work demonstrates how a Kalman filter can be devised to estimate the attitude using these new variables. The seven Markley variables are subject to one constraint condition, making the error covariance matrix singular. The filter design presented here explicitly accounts for this constraint by using a six-component error state in the filter update step. The reduced dimension error state is unconstrained and its covariance matrix is nonsingular.

Energy-Efficient Systems Eliminate Icing Danger for UAVs

NASA Technical Reports Server (NTRS)

2010-01-01

Ames Research Center engineer Leonard Haslim invented an anti-icing t echnology called an electroexpulsive separation system, which uses m echanical force to shatter potentially dangerous ice buildup on an ai rcraft surface. Temecula, California-based Ice Management Systems (no w known as IMS-ESS) licensed the technology from Ames and has discov ered a niche market for the lightweight, energy-efficient technology: unmanned aerial vehicles (UAVs). IMS-ESS systems now prevent damagi ng ice accumulation on military UAVs, allowing the vehicles to carry out crucial missions year round.

Design and implementation of a remote UAV-based mobile health monitoring system

NASA Astrophysics Data System (ADS)

Li, Songwei; Wan, Yan; Fu, Shengli; Liu, Mushuang; Wu, H. Felix

2017-04-01

Unmanned aerial vehicles (UAVs) play increasing roles in structure health monitoring. With growing mobility in modern Internet-of-Things (IoT) applications, the health monitoring of mobile structures becomes an emerging application. In this paper, we develop a UAV-carried vision-based monitoring system that allows a UAV to continuously track and monitor a mobile infrastructure and transmit back the monitoring information in real- time from a remote location. The monitoring system uses a simple UAV-mounted camera and requires only a single feature located on the mobile infrastructure for target detection and tracking. The computation-effective vision-based tracking solution based on a single feature is an improvement over existing vision-based lead-follower tracking systems that either have poor tracking performance due to the use of a single feature, or have improved tracking performance at a cost of the usage of multiple features. In addition, a UAV-carried aerial networking infrastructure using directional antennas is used to enable robust real-time transmission of monitoring video streams over a long distance. Automatic heading control is used to self-align headings of directional antennas to enable robust communication in mobility. Compared to existing omni-communication systems, the directional communication solution significantly increases the operation range of remote monitoring systems. In this paper, we develop the integrated modeling framework of camera and mobile platforms, design the tracking algorithm, develop a testbed of UAVs and mobile platforms, and evaluate system performance through both simulation studies and field tests.

UAV based mapping of variation in grassland yield for forage production in Arctic environments

NASA Astrophysics Data System (ADS)

Davids, C.; Karlsen, S. R.; Jørgensen, M.; Ancin Murguzur, F. J.

2017-12-01

Grassland cultivation for animal feed is the key agricultural activity in northern Norway. Even though the growing season has increased by at least a week in the last 30 years, grassland yields appear to have declined, probably due to more challenging winter conditions and changing agronomy practices. The ability for local and regional crop productivity forecasting would assist farmers with management decisions and would provide local and national authorities with a better overview over productivity and potential problems due to e.g. winter damage. Remote sensing technology has long been used to estimate and map the variability of various biophysical parameters, but calibration is important. In order to establish the relationship between spectral reflectance and grass yield in northern European environments we combine Sentinel-2 time series, UAV-based multispectral measurements, and ground-based spectroradiometry, with biomass analyses and observations of species composition. In this presentation we will focus on the results from the UAV data acquisition. We used a multirotor UAV with different sensors (a multispectral Rikola camera, and NDVI and RGB cameras) to image a number of cultivated grasslands of different age and productivity in northern Norway in June/July 2016 and 2017. Following UAV data acquisition, 10 to 20 in situ measurements were made per field using a FieldSpec3 (350-2500 nm). In addition, samples were taken to determine biomass and grass species composition. The imaging and sampling was done immediately prior to harvesting. The Rikola camera, when used as a stand-alone camera mounted on a UAV, can collect 15 bands with a spectral width of 10-15 nm in the range between 500-890 nm. In the initial analysis of the 2016 data we investigated how well different vegetation indices correlated with biomass and showed that vegetation indices that include red edge bands perform better than widely used indices such as NDVI. We will extend the analysis with

Common Approach to Geoprocessing of Uav Data across Application Domains

NASA Astrophysics Data System (ADS)

Percivall, G. S.; Reichardt, M.; Taylor, T.

2015-08-01

UAVs are a disruptive technology bringing new geographic data and information to many application domains. UASs are similar to other geographic imagery systems so existing frameworks are applicable. But the diversity of UAVs as platforms along with the diversity of available sensors are presenting challenges in the processing and creation of geospatial products. Efficient processing and dissemination of the data is achieved using software and systems that implement open standards. The challenges identified point to the need for use of existing standards and extending standards. Results from the use of the OGC Sensor Web Enablement set of standards are presented. Next steps in the progress of UAVs and UASs may follow the path of open data, open source and open standards.

Concept for Classifying Facade Elements Based on Material, Geometry and Thermal Radiation Using Multimodal Uav Remote Sensing

NASA Astrophysics Data System (ADS)

Ilehag, R.; Schenk, A.; Hinz, S.

2017-08-01

This paper presents a concept for classification of facade elements, based on the material and the geometry of the elements in addition to the thermal radiation of the facade with the usage of a multimodal Unmanned Aerial Vehicle (UAV) system. Once the concept is finalized and functional, the workflow can be used for energy demand estimations for buildings by exploiting existing methods for estimation of heat transfer coefficient and the transmitted heat loss. The multimodal system consists of a thermal, a hyperspectral and an optical sensor, which can be operational with a UAV. While dealing with sensors that operate in different spectra and have different technical specifications, such as the radiometric and the geometric resolution, the challenges that are faced are presented. Addressed are the different approaches of data fusion, such as image registration, generation of 3D models by performing image matching and the means for classification based on either the geometry of the object or the pixel values. As a first step towards realizing the concept, the result from a geometric calibration with a designed multimodal calibration pattern is presented.

Automated multiple target detection and tracking in UAV videos

NASA Astrophysics Data System (ADS)

Mao, Hongwei; Yang, Chenhui; Abousleman, Glen P.; Si, Jennie

2010-04-01

In this paper, a novel system is presented to detect and track multiple targets in Unmanned Air Vehicles (UAV) video sequences. Since the output of the system is based on target motion, we first segment foreground moving areas from the background in each video frame using background subtraction. To stabilize the video, a multi-point-descriptor-based image registration method is performed where a projective model is employed to describe the global transformation between frames. For each detected foreground blob, an object model is used to describe its appearance and motion information. Rather than immediately classifying the detected objects as targets, we track them for a certain period of time and only those with qualified motion patterns are labeled as targets. In the subsequent tracking process, a Kalman filter is assigned to each tracked target to dynamically estimate its position in each frame. Blobs detected at a later time are used as observations to update the state of the tracked targets to which they are associated. The proposed overlap-rate-based data association method considers the splitting and merging of the observations, and therefore is able to maintain tracks more consistently. Experimental results demonstrate that the system performs well on real-world UAV video sequences. Moreover, careful consideration given to each component in the system has made the proposed system feasible for real-time applications.

Secure Utilization of Beacons and UAVs in Emergency Response Systems for Building Fire Hazard.

PubMed

Seo, Seung-Hyun; Choi, Jung-In; Song, Jinseok

2017-09-25

An intelligent emergency system for hazard monitoring and building evacuation is a very important application area in Internet of Things (IoT) technology. Through the use of smart sensors, such a system can provide more vital and reliable information to first-responders and also reduce the incidents of false alarms. Several smart monitoring and warning systems do already exist, though they exhibit key weaknesses such as a limited monitoring coverage and security, which have not yet been sufficiently addressed. In this paper, we propose a monitoring and emergency response method for buildings by utilizing beacons and Unmanned Aerial Vehicles (UAVs) on an IoT security platform. In order to demonstrate the practicability of our method, we also implement a proof of concept prototype, which we call the UAV-EMOR (UAV-assisted Emergency Monitoring and Response) system. Our UAV-EMOR system provides the following novel features: (1) secure communications between UAVs, smart sensors, the control server and a smartphone app for security managers; (2) enhanced coordination between smart sensors and indoor/outdoor UAVs to expand real-time monitoring coverage; and (3) beacon-aided rescue and building evacuation.

Secure Utilization of Beacons and UAVs in Emergency Response Systems for Building Fire Hazard

PubMed Central

Seo, Seung-Hyun; Choi, Jung-In; Song, Jinseok

2017-01-01

An intelligent emergency system for hazard monitoring and building evacuation is a very important application area in Internet of Things (IoT) technology. Through the use of smart sensors, such a system can provide more vital and reliable information to first-responders and also reduce the incidents of false alarms. Several smart monitoring and warning systems do already exist, though they exhibit key weaknesses such as a limited monitoring coverage and security, which have not yet been sufficiently addressed. In this paper, we propose a monitoring and emergency response method for buildings by utilizing beacons and Unmanned Aerial Vehicles (UAVs) on an IoT security platform. In order to demonstrate the practicability of our method, we also implement a proof of concept prototype, which we call the UAV-EMOR (UAV-assisted Emergency Monitoring and Response) system. Our UAV-EMOR system provides the following novel features: (1) secure communications between UAVs, smart sensors, the control server and a smartphone app for security managers; (2) enhanced coordination between smart sensors and indoor/outdoor UAVs to expand real-time monitoring coverage; and (3) beacon-aided rescue and building evacuation. PMID:28946659

Photovoltaic electric power applied to Unmanned Aerial Vehicles (UAV)

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

Geis, J.; Arnold, J.H.

1994-09-01

Photovoltaic electric-powered flight is receiving a great deal of attention in the context of the United States` Unmanned Aerial Vehicle (UAV) program. This paper addresses some of the enabling technical areas and their potential solutions. Of particular interest are the long-duration, high-altitude class of UAV`s whose mission it is to achieve altitudes between 60,000 and 100,000 feet, and to remain at those altitudes for prolonged periods performing various mapping and surveillance activities. Addressed herein are studies which reveal the need for extremely light-weight and efficient solar cells, high-efficiency electric motor-driven propeller modules, and power management and distribution control elements. Sincemore » the potential payloads vary dramatically in their power consumption and duty cycles, a typical load profile has been selected to provide commonality for the propulsion power comparisons. Since missions vary widely with respect to ground coverage requirements, from repeated orbiting over a localized target to long-distance routes over irregular terrain, the authors have also averaged the power requirements for on-board guidance and control power, as well as ground control and communication link utilization. In the context of the national technology reinvestment program, wherever possible they modeled components and materials which have been qualified for space and defense applications, yet are compatible with civilian UAV activities. These include, but are not limited to, solar cell developments, electric storage technology for diurnal operation, local and ground communications, power management and distribution, and control servo design. And finally, the results of tests conducted by Wright Laboratory on ultralight, highly efficient MOCVD GaAs solar cells purchased from EPI Materials Ltd. (EML) of the UK are presented. These cells were also used for modeling the flight characteristics of UAV aircraft.« less

Emergency response to landslide using GNSS measurements and UAV

NASA Astrophysics Data System (ADS)

Nikolakopoulos, Konstantinos G.; Koukouvelas, Ioannis K.

2017-10-01

Landslide monitoring can be performed using many different methods: Classical geotechnical measurements like inclinometer, topographical survey measurements with total stations or GNSS sensors and photogrammetric techniques using airphotos or high resolution satellite images. However all these methods are expensive or difficult to be developed immediately after the landslide triggering. In contrast airborne technology and especially the use of Unmanned Aerial Vehicles (UAVs) make response to landslide disaster easier as UAVs can be launched quickly in dangerous terrains and send data about the sliding areas to responders on the ground either as RGB images or as videos. In addition, the emergency response to landslide is critical for the further monitoring. For proper displacement identification all the above mentioned monitoring methods need a high resolution and a very accurate representation of the relief. The ideal solution for the accurate and quick mapping of a landslide is the combined use of UAV's photogrammetry and GNSS measurements. UAVs have started their development as expensive toys but they currently became a very valuable tool in large scale mapping of sliding areas. The purpose of this work is to demonstrate an effective solution for the initial landslide mapping immediately after the occurrence of the phenomenon and the possibility of the periodical assessment of the landslide. Three different landslide cases from Greece are presented in the current study. All three landslides have different characteristics: occurred in different geomorphologic environments, triggered by different causes and had different geologic bedrock. In all three cases we performed detailed GNSS measurements of the landslide area, we generated orthophotos as well as Digital Surface Models (DSMs) at an accuracy of less than +/-10 cm. Slide direction and velocity, mass balances as well as protection and mitigation measurements can be derived from the application of the UAVs

A UAV System for Observing Volcanoes and Natural Hazards

NASA Astrophysics Data System (ADS)

Saggiani, G.; Persiani, F.; Ceruti, A.; Tortora, P.; Troiani, E.; Giuletti, F.; Amici, S.; Buongiorno, M.; Distefano, G.; Bentini, G.; Bianconi, M.; Cerutti, A.; Nubile, A.; Sugliani, S.; Chiarini, M.; Pennestri, G.; Petrini, S.; Pieri, D.

2007-12-01

Fixed or rotary wing manned aircraft are currently the most commonly used platforms for airborne reconnaissance in response to natural hazards, such as volcanic eruptions, oil spills, wild fires, earthquakes. Such flights are very often undertaken in hazardous flying conditions (e.g., turbulence, downdrafts, reduced visibility, close proximity to dangerous terrain) and can be expensive. To mitigate these two fundamental issues-- safety and cost--we are exploring the use of small (less than 100kg), relatively inexpensive, but effective, unmanned aerial vehicles (UAVs) for this purpose. As an operational test, in 2004 we flew a small autonomous UAV in the airspace above and around Stromboli Volcano. Based in part on this experience, we are adapting the RAVEN UAV system for such natural hazard surveillance missions. RAVEN has a 50km range, with a 3.5m wingspan, main fuselage length of 4.60m, and maximum weight of 56kg. It has autonomous flight capability and a ground control Station for the mission planning and control. It will carry a variety of imaging devices, including a visible camera, and an IR camera. It will also carry an experimental Fourier micro-interferometer based on MOEMS technology, (developed by IMM Institute of CNR), to detect atmospheric trace gases. Such flexible, capable, and easy-to-deploy UAV systems may significantly shorten the time necessary to characterize the nature and scale of the natural hazard threats if used from the outset of, and systematically during, natural hazard events. When appropriately utilized, such UAVs can provide a powerful new hazard mitigation and documentation tool for civil protection hazard responders. This research was carried out under the auspices of the Italian government, and, in part, under contract to NASA at the Jet Propulsion Laboratory.

Automated UAV-based video exploitation using service oriented architecture framework

NASA Astrophysics Data System (ADS)

Se, Stephen; Nadeau, Christian; Wood, Scott

2011-05-01

Airborne surveillance and reconnaissance are essential for successful military missions. Such capabilities are critical for troop protection, situational awareness, mission planning, damage assessment, and others. Unmanned Aerial Vehicles (UAVs) gather huge amounts of video data but it is extremely labour-intensive for operators to analyze hours and hours of received data. At MDA, we have developed a suite of tools that can process the UAV video data automatically, including mosaicking, change detection and 3D reconstruction, which have been integrated within a standard GIS framework. In addition, the mosaicking and 3D reconstruction tools have also been integrated in a Service Oriented Architecture (SOA) framework. The Visualization and Exploitation Workstation (VIEW) integrates 2D and 3D visualization, processing, and analysis capabilities developed for UAV video exploitation. Visualization capabilities are supported through a thick-client Graphical User Interface (GUI), which allows visualization of 2D imagery, video, and 3D models. The GUI interacts with the VIEW server, which provides video mosaicking and 3D reconstruction exploitation services through the SOA framework. The SOA framework allows multiple users to perform video exploitation by running a GUI client on the operator's computer and invoking the video exploitation functionalities residing on the server. This allows the exploitation services to be upgraded easily and allows the intensive video processing to run on powerful workstations. MDA provides UAV services to the Canadian and Australian forces in Afghanistan with the Heron, a Medium Altitude Long Endurance (MALE) UAV system. On-going flight operations service provides important intelligence, surveillance, and reconnaissance information to commanders and front-line soldiers.

Estimating distribution of hidden objects with drones: from tennis balls to manatees.

PubMed

Martin, Julien; Edwards, Holly H; Burgess, Matthew A; Percival, H Franklin; Fagan, Daniel E; Gardner, Beth E; Ortega-Ortiz, Joel G; Ifju, Peter G; Evers, Brandon S; Rambo, Thomas J

2012-01-01

Unmanned aerial vehicles (UAV), or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection). UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348). The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants.

Estimating Distribution of Hidden Objects with Drones: From Tennis Balls to Manatees

PubMed Central

Martin, Julien; Edwards, Holly H.; Burgess, Matthew A.; Percival, H. Franklin; Fagan, Daniel E.; Gardner, Beth E.; Ortega-Ortiz, Joel G.; Ifju, Peter G.; Evers, Brandon S.; Rambo, Thomas J.

2012-01-01

Unmanned aerial vehicles (UAV), or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection). UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348). The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants. PMID:22761712

Development of a UAV-based Global Ozone Lidar Demonstrator (GOLD)

NASA Astrophysics Data System (ADS)

Browell, E. V.; Deyoung, R. J.; Hair, J. W.; Ismail, S.; McGee, T.; Hardesty, R. M.; Brewer, W. A.; McDermid, I. S.

2006-12-01

Global ozone measurements are needed across the troposphere with high vertical resolution to enable comprehensive studies of continental and intercontinental atmospheric chemistry and dynamics, which are affected by diverse natural and human-induced processes. The development of a unattended aerial vehicle (UAV) based Global Ozone Lidar Demonstrator (GOLD) is an important step in enabling a space-based ozone and aerosol lidar and for conducting unique UAV-based large-scale atmospheric investigations. The GOLD system will incorporate the most advanced technology developed under the NASA Laser Risk Reduction Program (LRRP) and the Small Business Innovative Research (SBIR) program to produce a compact, autonomously operating ozone and aerosol Differential Absorption Lidar (DIAL) system for a UAV platform. This system will leverage advanced Nd:YAG and optical parametric oscillator (OPO) laser technologies being developed by ITT Industries under the LRRP and the autonomously operating ozone DIAL system being developed by Science and Engineering Services Inc. (SESI) under an SBIR Phase-3 contract. Laser components from ITT will be integrated into the SESI DIAL system, and the resulting GOLD system will be flight tested on a NASA UAV. The development of the GOLD system was initiated as part of the NASA Instrument Incubator Program in December 2005, and great progress has been made towards completing major GOLD subsystems. ITT has begun construction of the high-power Nd:YAG pump laser and the ultraviolet OPO for generating the ozone DIAL wavelengths of 290 and 300 nm and the aerosol visible wavelength at 532 nm. SESI is completing the Phase-3 SBIR contract for the delivery and demonstration of the ozone DIAL receiver and data system, and NOAA is completing detector evaluations for use in the GOLD system. Welch Mechanical is examining system designs for integrating GOLD into the external pod that will be hung under the new IKANA (Predator-B) UAV that NASA Dryden is

The Practical Application of Uav-Based Photogrammetry Under Economic Aspects

NASA Astrophysics Data System (ADS)

Sauerbier, M.; Siegrist, E.; Eisenbeiss, H.; Demir, N.

2011-09-01

Nowadays, small size UAVs (Unmanned Aerial Vehicles) have reached a level of practical reliability and functionality that enables this technology to enter the geomatics market as an additional platform for spatial data acquisition. Though one could imagine a wide variety of interesting sensors to be mounted on such a device, here we will focus on photogrammetric applications using digital cameras. In praxis, UAV-based photogrammetry will only be accepted if it a) provides the required accuracy and an additional value and b) if it is competitive in terms of economic application compared to other measurement technologies. While a) was already proven by the scientific community and results were published comprehensively during the last decade, b) still has to be verified under real conditions. For this purpose, a test data set representing a realistic scenario provided by ETH Zurich was used to investigate cost effectiveness and to identify weak points in the processing chain that require further development. Our investigations are limited to UAVs carrying digital consumer cameras, for larger UAVs equipped with medium format cameras the situation has to be considered as significantly different. Image data was acquired during flights using a microdrones MD4-1000 quadrocopter equipped with an Olympus PE-1 digital compact camera. From these images, a subset of 5 images was selected for processing in order to register the effort of time required for the whole production chain of photogrammetric products. We see the potential of mini UAV-based photogrammetry mainly in smaller areas, up to a size of ca. 100 hectares. Larger areas can be efficiently covered by small airplanes with few images, reducing processing effort drastically. In case of smaller areas of a few hectares only, it depends more on the products required. UAVs can be an enhancement or alternative to GNSS measurements, terrestrial laser scanning and ground based photogrammetry. We selected the above mentioned

Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR

PubMed Central

Bartholomeus, Harm M.; Kooistra, Lammert

2017-01-01

In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX®-1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Models (DTMs), Digital Surface Models (DSMs) and finally Canopy Height Models (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 cm higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 cm. We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB). PMID:29039755

Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR.

PubMed

Brede, Benjamin; Lau, Alvaro; Bartholomeus, Harm M; Kooistra, Lammert

2017-10-17

In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX ® -1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Model (DTMs), Digital Surface Model (DSMs) and finally Canopy Height Model (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 c m higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 c m . We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).

Multi-Criteria GIS Analyses with the Use of Uavs for the Needs of Spatial Planning

NASA Astrophysics Data System (ADS)

Zawieska, D.; Markiewicz, J.; Turek, A.; Bakuła, K.; Kowalczyk, M.; Kurczyński, Z.; Ostrowski, W.; Podlasiak, P.

2016-06-01

Utilization of Unmanned Aerial Systems (UAVs) in agriculture, forestry, or other environmental contexts has recently become common. However, in the case of spatial planning, the role of UAVs still seems to be underestimated. At present, sections of municipal development use UAVs mainly for promotional purposes (films, folders, brochures, etc.). The use of UAVs for spatial management provides results, first of all, in the form of savings in human resources and time; however, more frequently, it is also connected with financial savings (given the decreasing cost of UAVs and photogrammetric software). The performed research presented here relates to the possibilities of using UAVs to update planning documents, and, in particular, to update the study of conditions and directions of spatial management and preparation of local plans for physical management. Based on acquired photographs with a resolution of 3 cm, a cloud of points is generated, as well as 3D models and the true orthophotomap. These data allow multi-criteria spatial analyses. Additionally, directions of development and changes in physical management are analysed for the given area.

UAV telemetry communications using ZigBee protocol

NASA Astrophysics Data System (ADS)

Nasution, T. H.; Siregar, I.; Yasir, M.

2017-10-01

Wireless communication has been widely used in various fields or disciplines such as agriculture, health, engineering, military, and aerospace so as to support the work in that field. The communication technology is typically used for controlling devices and data monitoring. One development of wireless communication is the widely used telemetry system used to reach areas that cannot be reached by humans using UAV (Unmanned Aerial Vehicle) or unmanned aircraft. In this paper we discuss the design of telemetry system in UAV using ZigBee protocol. From the test obtained the system can work well with visualization displays without pause is 20 data per second with a maximum data length of 120 characters.

A proposed UAV for indoor patient care.

PubMed

Todd, Catherine; Watfa, Mohamed; El Mouden, Yassine; Sahir, Sana; Ali, Afrah; Niavarani, Ali; Lutfi, Aoun; Copiaco, Abigail; Agarwal, Vaibhavi; Afsari, Kiyan; Johnathon, Chris; Okafor, Onyeka; Ayad, Marina

2015-09-10

Indoor flight, obstacle avoidance and client-server communication of an Unmanned Aerial Vehicle (UAV) raises several unique research challenges. This paper examines current methods and associated technologies adapted within the literature toward autonomous UAV flight, for consideration in a proposed system for indoor healthcare administration with a quadcopter. We introduce Healthbuddy, a unique research initiative towards overcoming challenges associated with indoor navigation, collision detection and avoidance, stability, wireless drone-server communications and automated decision support for patient care in a GPS-denied environment. To address the identified research deficits, a drone-based solution is presented. The solution is preliminary as we develop and refine the suggested algorithms and hardware system to achieve the research objectives.

Augmented Reality Tool for the Situational Awareness Improvement of UAV Operators

PubMed Central

Ruano, Susana; Cuevas, Carlos; Gallego, Guillermo; García, Narciso

2017-01-01

Unmanned Aerial Vehicles (UAVs) are being extensively used nowadays. Therefore, pilots of traditional aerial platforms should adapt their skills to operate them from a Ground Control Station (GCS). Common GCSs provide information in separate screens: one presents the video stream while the other displays information about the mission plan and information coming from other sensors. To avoid the burden of fusing information displayed in the two screens, an Augmented Reality (AR) tool is proposed in this paper. The AR system has two functionalities for Medium-Altitude Long-Endurance (MALE) UAVs: route orientation and target identification. Route orientation allows the operator to identify the upcoming waypoints and the path that the UAV is going to follow. Target identification allows a fast target localization, even in the presence of occlusions. The AR tool is implemented following the North Atlantic Treaty Organization (NATO) standards so that it can be used in different GCSs. The experiments show how the AR tool improves significantly the situational awareness of the UAV operators. PMID:28178189

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs.

PubMed

Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E; Hernandez, Carmen; Dalmau, Oscar

2017-06-16

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow.

Tracking with a Cooperatively Controlled Swarm of GMTI Equipped UAVS

DTIC Science & Technology

2008-12-02

with Ground Optimal Placement of GMTI UAVs for ground target tracking Abhijit Sinha°, Thia. Kirubarajana and Yaakov Bar-Shalom6 " Electrical and...Storrs, CT 06269, USA Abstract—With the recent advent of moderate-cost unmanned (or uninhabited) aerial vehicles (UAV) and their success in...the sensor platforms are mobile one has to decide the optimal placement of sensors. With the recent advent of af- fordable unmanned aerial vehicles

Establishment of Models and Data Tracking for Small UAV Reliability

DTIC Science & Technology

2004-06-01

The development of solar powered UAVs is also being supported and funded by NASA. The idea, development, and construction was initiated by the...Aerovironment company, which has been involved in the construction of solar -powered aircraft for 20 years. Solar Challenger, HALSOL, Talon, Pathfinder...Centurion, and Helios with a wingspan of 247 feet, were among the solar -powered UAVs during those efforts.28 New technologies like regenerative fuel

Electric Power System for High Altitude UAV Technology Survey

NASA Technical Reports Server (NTRS)

1997-01-01

Electric powertrain technologies with application to high altitude Unmanned Aerial Vehicles (UAV) are assessed. One hundred twenty five solar electric UAV configurations and missions were simulated. Synergistic design opportunities were investigated with the premise that specific benefits may be realized, for example, if a single component can serve multiple functions, such as a battery being used for energy storage as well as for a structural component of the aircraft. For each UAV mission simulation, the airframe structure, powertrain configuration (type of solar cells, energy storage options) and performance baseline (1997 or 2001) were specified. It has been found that the use of the high efficiency (multijunction) solar cells or the use of the synergistic amorphous silicon solar cell configuration yields aircraft that can accomplish the majority of the missions of interest for any latitude between 0 deg and 55 deg, hence, a single versatile aircraft can be constructed and implemented to accomplish these missions.

Portable Imagery Quality Assessment Test Field for Uav Sensors

NASA Astrophysics Data System (ADS)

Dąbrowski, R.; Jenerowicz, A.

2015-08-01

Nowadays the imagery data acquired from UAV sensors are the main source of all data used in various remote sensing applications, photogrammetry projects and in imagery intelligence (IMINT) as well as in other tasks as decision support. Therefore quality assessment of such imagery is an important task. The research team from Military University of Technology, Faculty of Civil Engineering and Geodesy, Geodesy Institute, Department of Remote Sensing and Photogrammetry has designed and prepared special test field- The Portable Imagery Quality Assessment Test Field (PIQuAT) that provides quality assessment in field conditions of images obtained with sensors mounted on UAVs. The PIQuAT consists of 6 individual segments, when combined allow for determine radiometric, spectral and spatial resolution of images acquired from UAVs. All segments of the PIQuAT can be used together in various configurations or independently. All elements of The Portable Imagery Quality Assessment Test Field were tested in laboratory conditions in terms of their radiometry and spectral reflectance characteristics.

Evaluation of composite materials providing improved acoustic transmission loss for UAVs

NASA Astrophysics Data System (ADS)

Callicoat, Jeffrey R.

With the proliferation of Unmanned Aerial Vehicles (UAVs) in civilian airspace in the near future, community noise will be a major issue of concern. Numerous studies have shown a direct link between community noise pollution (i.e., road traffic noise and airport noise) and serious health problems. There exists, therefore, a pressing need to create quiet UAVs, and this drives the need for noise-attenuating materials and structures suitable for UAV airframe fabrication. By shrouding predominant noise sources such as the engine, exhaust, and even the propeller (in the case of a ducted fan) with the airframe structure, the airframe can serve as a noise transmission barrier and substantially reduce UAV noise profiles. The present research effort is an experimental investigation of light-weight fiber-reinforced composite materials to provide high acoustic transmission loss (TL) for use in fabricating UAV airframes. A transmission loss tube acoustic test system was designed, fabricated, and validated, and extensive testing was done on numerous composite layups of interest for UAV fabrication. Composites under study included carbon fiber, fiberglass, and Kevlar fabrics as skin materials along with vinyl foam, Nomex honeycomb, and balsawood as core materials. Results from testing small 3"x3" samples in the TL tube led to the selection of four composite sandwich panels of interest for further study. Larger 36"x36" test samples of these selected layups were then fabricated and tested using a 2-room methodology. Whereas the TL tube yielded results in the stiffness-controlled region of acoustic behavior, the 2-room tests produced results in the mass-controlled region for these materials, enabling relative performance comparisons over both acoustic regimes. Recognizing that a good material for airframe fabrication should possess not only high TL, but also low weight and high stiffness, load-deflection tests were conducted and overall material performance was compared in terms of

Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera

PubMed Central

Qu, Yufu; Huang, Jianyu; Zhang, Xuan

2018-01-01

In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles’ camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth–map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable. PMID:29342908

Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera.

PubMed

Qu, Yufu; Huang, Jianyu; Zhang, Xuan

2018-01-14

In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles' camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth-map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

Study on the aerodynamic behavior of a UAV with an applied seeder for agricultural practices

NASA Astrophysics Data System (ADS)

Felismina, Raimundo; Silva, Miguel; Mateus, Artur; Malça, Cândida

2017-06-01

It is irrefutable that the use of Unmanned Airborne Vehicle Systems (UAVs) in agricultural tasks and on the analysis of health and vegetative conditions represents a powerful tool in modern agriculture. To contribute to the growth of the agriculture economic sector a seeder to be coupled to any type of UAV was previously developed and designed by the authors. This seeder allows for the deposition of seeds with positional accuracy, i.e., seeds are accurately deposited at pre-established distances between plants [1]. This work aims at analyzing the aerodynamic behavior of UAV/Seeder assembly to determine the suitable inclination - among 0°, 15° and 30° - for its takeoff and for its motion during the seeding operation and, in turn, to define the suitable flight plan that increases the batteries autonomy. For this the ANSYS® FLUENT computational tool was used to simulate a wind tunnel which has as principle the Navier-Stokes differential equations, that designates the fluid flow around the UAV/Seeder assembly. The aerodynamic results demonstrated that for take-off the UAV inclination of 30° is the aerodynamically most favorable position due to the lower aerodynamic drag during the climb. Concerning flying motion during the seeding procedure the UAV inclination of 0° is that which leads to lower UAV/Seeder frontal area and drag coefficient.

UAV-Based Estimation of Carbon Exports from Heterogeneous Soil Landscapes—A Case Study from the CarboZALF Experimental Area

PubMed Central

Wehrhan, Marc; Rauneker, Philipp; Sommer, Michael

2016-01-01

The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b899. The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part. PMID:26907284

UAV-Based Estimation of Carbon Exports from Heterogeneous Soil Landscapes--A Case Study from the CarboZALF Experimental Area.

PubMed

Wehrhan, Marc; Rauneker, Philipp; Sommer, Michael

2016-02-19

The advantages of remote sensing using Unmanned Aerial Vehicles (UAVs) are a high spatial resolution of images, temporal flexibility and narrow-band spectral data from different wavelengths domains. This enables the detection of spatio-temporal dynamics of environmental variables, like plant-related carbon dynamics in agricultural landscapes. In this paper, we quantify spatial patterns of fresh phytomass and related carbon (C) export using imagery captured by a 12-band multispectral camera mounted on the fixed wing UAV Carolo P360. The study was performed in 2014 at the experimental area CarboZALF-D in NE Germany. From radiometrically corrected and calibrated images of lucerne (Medicago sativa), the performance of four commonly used vegetation indices (VIs) was tested using band combinations of six near-infrared bands. The highest correlation between ground-based measurements of fresh phytomass of lucerne and VIs was obtained for the Enhanced Vegetation Index (EVI) using near-infrared band b899. The resulting map was transformed into dry phytomass and finally upscaled to total C export by harvest. The observed spatial variability at field- and plot-scale could be attributed to small-scale soil heterogeneity in part.

Network Analysis on Attitudes

PubMed Central

Borsboom, Denny; van Harreveld, Frenk; van der Maas, Han L. J.

2017-01-01

In this article, we provide a brief tutorial on the estimation, analysis, and simulation on attitude networks using the programming language R. We first discuss what a network is and subsequently show how one can estimate a regularized network on typical attitude data. For this, we use open-access data on the attitudes toward Barack Obama during the 2012 American presidential election. Second, we show how one can calculate standard network measures such as community structure, centrality, and connectivity on this estimated attitude network. Third, we show how one can simulate from an estimated attitude network to derive predictions from attitude networks. By this, we highlight that network theory provides a framework for both testing and developing formalized hypotheses on attitudes and related core social psychological constructs. PMID:28919944

Using Visual Odometry to Estimate Position and Attitude

NASA Technical Reports Server (NTRS)

Maimone, Mark; Cheng, Yang; Matthies, Larry; Schoppers, Marcel; Olson, Clark

2007-01-01

A computer program in the guidance system of a mobile robot generates estimates of the position and attitude of the robot, using features of the terrain on which the robot is moving, by processing digitized images acquired by a stereoscopic pair of electronic cameras mounted rigidly on the robot. Developed for use in localizing the Mars Exploration Rover (MER) vehicles on Martian terrain, the program can also be used for similar purposes on terrestrial robots moving in sufficiently visually textured environments: examples include low-flying robotic aircraft and wheeled robots moving on rocky terrain or inside buildings. In simplified terms, the program automatically detects visual features and tracks them across stereoscopic pairs of images acquired by the cameras. The 3D locations of the tracked features are then robustly processed into an estimate of overall vehicle motion. Testing has shown that by use of this software, the error in the estimate of the position of the robot can be limited to no more than 2 percent of the distance traveled, provided that the terrain is sufficiently rich in features. This software has proven extremely useful on the MER vehicles during driving on sandy and highly sloped terrains on Mars.

Estimating Attitude, Trajectory, and Gyro Biases in an Extended Kalman Filter using Earth Magnetic Field Data from the Rossi X-Ray Timing Explorer

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack

1997-01-01

Traditionally satellite attitude and trajectory have been estimated with completely separate systems, using different measurement data. The estimation of both trajectory and attitude for low earth orbit satellites has been successfully demonstrated in ground software using magnetometer and gyroscope data. Since the earth's magnetic field is a function of time and position, and since time is known quite precisely, the differences between the computed and measured magnetic field components, as measured by the magnetometers throughout the entire spacecraft orbit, are a function of both the spacecraft trajectory and attitude errors. Therefore, these errors can be used to estimate both trajectory and attitude. This work further tests the single augmented Extended Kalman Filter (EKF) which simultaneously and autonomously estimates spacecraft trajectory and attitude with data from the Rossi X-Ray Timing Explorer (RXTE) magnetometer and gyro-measured body rates. In addition, gyro biases are added to the state and the filter's ability to estimate them is presented.

Computationally efficient algorithms for real-time attitude estimation

NASA Technical Reports Server (NTRS)

Pringle, Steven R.

1993-01-01

For many practical spacecraft applications, algorithms for determining spacecraft attitude must combine inputs from diverse sensors and provide redundancy in the event of sensor failure. A Kalman filter is suitable for this task, however, it may impose a computational burden which may be avoided by sub optimal methods. A suboptimal estimator is presented which was implemented successfully on the Delta Star spacecraft which performed a 9 month SDI flight experiment in 1989. This design sought to minimize algorithm complexity to accommodate the limitations of an 8K guidance computer. The algorithm used is interpreted in the framework of Kalman filtering and a derivation is given for the computation.

Accuracy evaluation of 3D lidar data from small UAV

NASA Astrophysics Data System (ADS)

Tulldahl, H. M.; Bissmarck, Fredrik; Larsson, Hâkan; Grönwall, Christina; Tolt, Gustav

2015-10-01

A UAV (Unmanned Aerial Vehicle) with an integrated lidar can be an efficient system for collection of high-resolution and accurate three-dimensional (3D) data. In this paper we evaluate the accuracy of a system consisting of a lidar sensor on a small UAV. High geometric accuracy in the produced point cloud is a fundamental qualification for detection and recognition of objects in a single-flight dataset as well as for change detection using two or several data collections over the same scene. Our work presented here has two purposes: first to relate the point cloud accuracy to data processing parameters and second, to examine the influence on accuracy from the UAV platform parameters. In our work, the accuracy is numerically quantified as local surface smoothness on planar surfaces, and as distance and relative height accuracy using data from a terrestrial laser scanner as reference. The UAV lidar system used is the Velodyne HDL-32E lidar on a multirotor UAV with a total weight of 7 kg. For processing of data into a geographically referenced point cloud, positioning and orientation of the lidar sensor is based on inertial navigation system (INS) data combined with lidar data. The combination of INS and lidar data is achieved in a dynamic calibration process that minimizes the navigation errors in six degrees of freedom, namely the errors of the absolute position (x, y, z) and the orientation (pitch, roll, yaw) measured by GPS/INS. Our results show that low-cost and light-weight MEMS based (microelectromechanical systems) INS equipment with a dynamic calibration process can obtain significantly improved accuracy compared to processing based solely on INS data.

Coupled orbit-attitude dynamics and relative state estimation of spacecraft near small Solar System bodies

NASA Astrophysics Data System (ADS)

Misra, Gaurav; Izadi, Maziar; Sanyal, Amit; Scheeres, Daniel

2016-04-01

The effects of dynamical coupling between the rotational (attitude) and translational (orbital) motion of spacecraft near small Solar System bodies is investigated. This coupling arises due to the weak gravity of these bodies, as well as solar radiation pressure. The traditional approach assumes a point-mass spacecraft model to describe the translational motion of the spacecraft, while the attitude motion is considered to be completely decoupled from the translational motion. The model used here to describe the rigid-body spacecraft dynamics includes the non-uniform rotating gravity field of the small body up to second degree and order along with the attitude dependent terms, solar tide, and solar radiation pressure. This model shows that the second degree and order gravity terms due to the small body affect the dynamics of the spacecraft to the same extent as the orbit-attitude coupling due to the primary gravity (zeroth order) term. Variational integrators are used to simulate the dynamics of both the rigid spacecraft and the point mass. The small bodies considered here are modeled after Near-Earth Objects (NEO) 101955 Bennu, and 25143 Itokawa, and are assumed to be triaxial ellipsoids with uniform density. Differences in the numerically obtained trajectories of a rigid spacecraft and a point mass are then compared, to illustrate the impact of the orbit-attitude coupling on spacecraft dynamics in proximity of small bodies. Possible implications on the performance of model-based spacecraft control and on the station-keeping budget, if the orbit-attitude coupling is not accounted for in the model of the dynamics, are also discussed. An almost globally asymptotically stable motion estimation scheme based solely on visual/optical feedback that estimates the relative motion of the asteroid with respect to the spacecraft is also obtained. This estimation scheme does not require a model of the dynamics of the asteroid, which makes it perfectly suited for asteroids whose

Development and Testing of a Two-UAV Communication Relay System

PubMed Central

Li, Boyang; Jiang, Yifan; Sun, Jingxuan; Cai, Lingfeng; Wen, Chih-Yung

2016-01-01

In the development of beyond-line-of-sight (BLOS) Unmanned Aerial Vehicle (UAV) systems, communication between the UAVs and the ground control station (GCS) is of critical importance. The commonly used economical wireless modules are restricted by the short communication range and are easily blocked by obstacles. The use of a communication relay system provides a practical way to solve these problems, improving the performance of UAV communication in BLOS and cross-obstacle operations. In this study, a communication relay system, in which a quadrotor was used to relay radio communication for another quadrotor was developed and tested. First, the UAVs used as the airborne platform were constructed, and the hardware for the communication relay system was selected and built up. Second, a set of software programs and protocol for autonomous mission control, communication relay control, and ground control were developed. Finally, the system was fully integrated into the airborne platform and tested both indoor and in-flight. The Received Signal Strength Indication (RSSI) and noise value in two typical application scenarios were recorded. The test results demonstrated the ability of this system to extend the communication range and build communication over obstacles. This system also shows the feasibility to coordinate multiple UAVs’ communication with the same relay structure. PMID:27754369

ESTADIUS: A High Motion "One Arcsec" Daytime Attitude Estimation System for Stratospheric Applications

NASA Astrophysics Data System (ADS)

Montel, J.; Andre, Y.; Mirc, F.; Etcheto, P.; Evrard, J.; Bray, N.; Saccoccio, M.; Tomasini, L.; Perot, E.

2015-09-01

ESTADIUS is an autonomous, accurate and daytime attitude estimation system, for stratospheric balloons that require a high level of attitude measurement and stability. The system has been developed by CNES. ESTADIUS is based on star sensor an pyrometer data fusion within an extended Kalman filter. The star sensor is composed of a 16 MPixels visible-CCD camera and a large aperture camera lens (focal length of 135mm, aperture f/1.8, 10ºx15º field of view or FOV) which provides very accurate stars measurements due to very low pixel angular size. This also allows detecting stars against a bright sky background. The pyrometer is a 0.01º/h performance class Fiber Optic Gyroscope (FOG). The system is adapted to work down to an altitude of ~25km, even under high cinematic conditions. Key elements of ESTADIUS are: daytime conditions use (as well as night time), autonomy (automatic recognition of constellations), high angular rate robustness (a few deg/s thanks to the high performance of attitude propagation), stray-light robustness (thanks to a high performance baffle), high accuracy (<1", 1σ). Four stratospheric qualification flights were very successfully performed in 2010/2011 and 2013/2014 in Kiruna (Sweden) and Timmins (Canada). ESTADIUS will allow long stratospheric flights with a unique attitude estimation system avoiding the restriction of night/day conditions at launch. The first operational flight of ESTADIUS will be in 2015 for the PILOT scientific missions (led by IRAP and CNES in France). Further balloon missions such as CIDRE will use the system ESTADIUS is probably the first autonomous, large FOV, daytime stellar attitude measurement system. This paper details the technical features and in-flight results.

Light UAV Support Ship (ASW) (LUSSA)

DTIC Science & Technology

2011-08-01

35 9.5 TriSWACH Model Test Data...7 Figure 8: TriSWACH Model ...Innovation in Ship Design (CISD) used the Northrop Grumman Bat UAV (formally known as the Swift Engineering Killer Bee KB4) to model launch, recovery, and

a Sensor Aided H.264/AVC Video Encoder for Aerial Video Sequences with in the Loop Metadata Correction

NASA Astrophysics Data System (ADS)

Cicala, L.; Angelino, C. V.; Ruatta, G.; Baccaglini, E.; Raimondo, N.

2015-08-01

Unmanned Aerial Vehicles (UAVs) are often employed to collect high resolution images in order to perform image mosaicking and/or 3D reconstruction. Images are usually stored on board and then processed with on-ground desktop software. In such a way the computational load, and hence the power consumption, is moved on ground, leaving on board only the task of storing data. Such an approach is important in the case of small multi-rotorcraft UAVs because of their low endurance due to the short battery life. Images can be stored on board with either still image or video data compression. Still image system are preferred when low frame rates are involved, because video coding systems are based on motion estimation and compensation algorithms which fail when the motion vectors are significantly long and when the overlapping between subsequent frames is very small. In this scenario, UAVs attitude and position metadata from the Inertial Navigation System (INS) can be employed to estimate global motion parameters without video analysis. A low complexity image analysis can be still performed in order to refine the motion field estimated using only the metadata. In this work, we propose to use this refinement step in order to improve the position and attitude estimation produced by the navigation system in order to maximize the encoder performance. Experiments are performed on both simulated and real world video sequences.

Impact of Prior Flight Experience on Learning Predator UAV Operator Skills

DTIC Science & Technology

2002-02-01

UAVs are becoming a mainstay of intelligence , surveillance, and reconnaissance (ISR) information gathering, with the capability of supplying, in...indicators of UAV pilot skill, namely frequency and type of videogame playing, and experience with remote-controlled hobby aircraft. Experience with...indicator, artificial horizon, heading rate indicator, and engine revolutions per minute. The right monitor displays other useful information, such as a

The Use of Drones in Spain: Towards a Platform for Controlling UAVs in Urban Environments.

PubMed

Chamoso, Pablo; González-Briones, Alfonso; Rivas, Alberto; Bueno De Mata, Federico; Corchado, Juan Manuel

2018-05-03

Rapid advances in technology make it necessary to prepare our society in every aspect. Some of the most significant technological developments of the last decade are the UAVs (Unnamed Aerial Vehicles) or drones. UAVs provide a wide range of new possibilities and have become a tool that we now use on a daily basis. However, if their use is not controlled, it could entail several risks, which make it necessary to legislate and monitor UAV flights to ensure, inter alia, the security and privacy of all citizens. As a result of this problem, several laws have been passed which seek to regulate their use; however, no proposals have been made with regards to the control of airspace from a technological point of view. This is exactly what we propose in this article: a platform with different modes designed to control UAVs and monitor their status. The features of the proposed platform provide multiple advantages that make the use of UAVs more secure, such as prohibiting UAVs’ access to restricted areas or avoiding collisions between vehicles. The platform has been successfully tested in Salamanca, Spain.

A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs

PubMed Central

Calvario, Gabriela; Sierra, Basilio; Alarcón, Teresa E.; Hernandez, Carmen; Dalmau, Oscar

2017-01-01

The use of Unmanned Aerial Vehicles (UAVs) based on remote sensing has generated low cost monitoring, since the data can be acquired quickly and easily. This paper reports the experience related to agave crop analysis with a low cost UAV. The data were processed by traditional photogrammetric flow and data extraction techniques were applied to extract new layers and separate the agave plants from weeds and other elements of the environment. Our proposal combines elements of photogrammetry, computer vision, data mining, geomatics and computer science. This fusion leads to very interesting results in agave control. This paper aims to demonstrate the potential of UAV monitoring in agave crops and the importance of information processing with reliable data flow. PMID:28621740