Frequency Diverse Tracking/Guidance Millimeter Radar Adapted to Target Acquisition,

DTIC Science & Technology

1980-06-01

resolution offered by electro- optical and infrared systems and the adverse environment (fog, battle- field smokes) penetrability which is characteristic of...Reflectors (&1 > 2). 63 ALEXANDER whereAis the transmitted wavelength. It shall also be assumed for this analysis that 2*a4 ’ ( optical region), and that the...and J. L. Brown, "A Preliminary Assessment of Target Classification using Noncoherent Radar Waveforms," US Army Missile Command, Technical Report T-79

Translation compensation and micro-Doppler extraction for precession ballistic targets with a wideband terahertz radar

NASA Astrophysics Data System (ADS)

Yang, Qi; Deng, Bin; Wang, Hongqiang; Zhang, Ye; Qin, Yuliang

2018-01-01

Imaging, classification, and recognition techniques of ballistic targets in midcourse have always been the focus of research in the radar field for military applications. However, the high velocity translation of ballistic targets will subject range profile and Doppler to translation, slope, and fold, which are especially severe in the terahertz region. Therefore, a two-step translation compensation method based on envelope alignment is presented. The rough compensation is based on the traditional envelope alignment algorithm in inverse synthetic aperture radar imaging, and the fine compensation is supported by distance fitting. Then, a wideband imaging radar system with a carrier frequency of 0.32 THz is introduced, and an experiment on a precession missile model is carried out. After translation compensation with the method proposed in this paper, the range profile and the micro-Doppler distributions unaffected by translation are obtained, providing an important foundation for the high-resolution imaging and micro-Doppler extraction of the terahertz radar.

A time-frequency classifier for human gait recognition

NASA Astrophysics Data System (ADS)

Mobasseri, Bijan G.; Amin, Moeness G.

2009-05-01

Radar has established itself as an effective all-weather, day or night sensor. Radar signals can penetrate walls and provide information on moving targets. Recently, radar has been used as an effective biometric sensor for classification of gait. The return from a coherent radar system contains a frequency offset in the carrier frequency, known as the Doppler Effect. The movements of arms and legs give rise to micro Doppler which can be clearly detailed in the time-frequency domain using traditional or modern time-frequency signal representation. In this paper we propose a gait classifier based on subspace learning using principal components analysis(PCA). The training set consists of feature vectors defined as either time or frequency snapshots taken from the spectrogram of radar backscatter. We show that gait signature is captured effectively in feature vectors. Feature vectors are then used in training a minimum distance classifier based on Mahalanobis distance metric. Results show that gait classification with high accuracy and short observation window is achievable using the proposed classifier.

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

NASA Astrophysics Data System (ADS)

Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

2018-03-01

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

Fly eye radar or micro-radar sensor technology

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo; Asmolova, Olga

2014-05-01

To compensate for its eye's inability to point its eye at a target, the fly's eye consists of multiple angularly spaced sensors giving the fly the wide-area visual coverage it needs to detect and avoid the threats around him. Based on a similar concept a revolutionary new micro-radar sensor technology is proposed for detecting and tracking ground and/or airborne low profile low altitude targets in harsh urban environments. Distributed along a border or around a protected object (military facility and buildings, camp, stadium) small size, low power unattended radar sensors can be used for target detection and tracking, threat warning, pre-shot sniper protection and provides effective support for homeland security. In addition it can provide 3D recognition and targets classification due to its use of five orders more pulses than any scanning radar to each space point, by using few points of view, diversity signals and intelligent processing. The application of an array of directional antennas eliminates the need for a mechanical scanning antenna or phase processor. It radically decreases radar size and increases bearing accuracy several folds. The proposed micro-radar sensors can be easy connected to one or several operators by point-to-point invisible protected communication. The directional antennas have higher gain, can be multi-frequency and connected to a multi-functional network. Fly eye micro-radars are inexpensive, can be expendable and will reduce cost of defense.

On Adaptive Cell-Averaging CFAR (Constant False-Alarm Rate) Radar Signal Detection

DTIC Science & Technology

1987-10-01

SIICILE COPY 4 F FInI Tedwill Rlmrt to October 197 00 C\\JT ON ADAPTIVE CELL-AVERA81NG CFAR I RADAR SIGNAL DETECTION Syracuse University Mourud krket...NY 13441-5700 ELEMENT NO. NO. NO ACCESSION NO. 11. TITLE (Include Security Classification) 61102F 2’ 05 J8 PD - ON ADAPTIVE CELL-AVERAGING CFAR RADAR... CFAR ). One approach to adaptive detection in nonstationary noise and clutter background is to compare the processed target signal to an adaptive

High resolution through-the-wall radar image based on beamspace eigenstructure subspace methods

NASA Astrophysics Data System (ADS)

Yoon, Yeo-Sun; Amin, Moeness G.

2008-04-01

Through-the-wall imaging (TWI) is a challenging problem, even if the wall parameters and characteristics are known to the system operator. Proper target classification and correct imaging interpretation require the application of high resolution techniques using limited array size. In inverse synthetic aperture radar (ISAR), signal subspace methods such as Multiple Signal Classification (MUSIC) are used to obtain high resolution imaging. In this paper, we adopt signal subspace methods and apply them to the 2-D spectrum obtained from the delay-andsum beamforming image. This is in contrast to ISAR, where raw data, in frequency and angle, is directly used to form the estimate of the covariance matrix and array response vector. Using beams rather than raw data has two main advantages, namely, it improves the signal-to-noise ratio (SNR) and can correctly image typical indoor extended targets, such as tables and cabinets, as well as point targets. The paper presents both simulated and experimental results using synthesized and real data. It compares the performance of beam-space MUSIC and Capon beamformer. The experimental data is collected at the test facility in the Radar Imaging Laboratory, Villanova University.

Polsar Land Cover Classification Based on Hidden Polarimetric Features in Rotation Domain and Svm Classifier

NASA Astrophysics Data System (ADS)

Tao, C.-S.; Chen, S.-W.; Li, Y.-Z.; Xiao, S.-P.

2017-09-01

Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR) data utilization. Rollinvariant polarimetric features such as H / Ani / α / Span are commonly adopted in PolSAR land cover classification. However, target orientation diversity effect makes PolSAR images understanding and interpretation difficult. Only using the roll-invariant polarimetric features may introduce ambiguity in the interpretation of targets' scattering mechanisms and limit the followed classification accuracy. To address this problem, this work firstly focuses on hidden polarimetric feature mining in the rotation domain along the radar line of sight using the recently reported uniform polarimetric matrix rotation theory and the visualization and characterization tool of polarimetric coherence pattern. The former rotates the acquired polarimetric matrix along the radar line of sight and fully describes the rotation characteristics of each entry of the matrix. Sets of new polarimetric features are derived to describe the hidden scattering information of the target in the rotation domain. The latter extends the traditional polarimetric coherence at a given rotation angle to the rotation domain for complete interpretation. A visualization and characterization tool is established to derive new polarimetric features for hidden information exploration. Then, a classification scheme is developed combing both the selected new hidden polarimetric features in rotation domain and the commonly used roll-invariant polarimetric features with a support vector machine (SVM) classifier. Comparison experiments based on AIRSAR and multi-temporal UAVSAR data demonstrate that compared with the conventional classification scheme which only uses the roll-invariant polarimetric features, the proposed classification scheme achieves both higher classification accuracy and better robustness. For AIRSAR data, the overall classification accuracy with the proposed classification scheme is 94.91 %, while that with the conventional classification scheme is 93.70 %. Moreover, for multi-temporal UAVSAR data, the averaged overall classification accuracy with the proposed classification scheme is up to 97.08 %, which is much higher than the 87.79 % from the conventional classification scheme. Furthermore, for multitemporal PolSAR data, the proposed classification scheme can achieve better robustness. The comparison studies also clearly demonstrate that mining and utilization of hidden polarimetric features and information in the rotation domain can gain the added benefits for PolSAR land cover classification and provide a new vision for PolSAR image interpretation and application.

Correlating Flight Behavior and Radar Measurements for Species Based Classification of Bird Radar Echoes for Wind Energy Site Assessment

NASA Astrophysics Data System (ADS)

Werth, S. P.; Frasier, S. J.

2015-12-01

Wind energy is one of the fastest-growing segments of the world energy market, offering a clean and abundant source of electricity. However, wind energy facilities can have detrimental effects on wildlife, especially birds and bats. Monitoring systems based on marine navigation radar are often used to quantify migration near potential wind sites, but the ability to reliably distinguish between bats and different varieties of birds has not been practically achieved. This classification capability would enable wind site selection that protects more vulnerable species, such as bats and raptors. Flight behavior, such as wing beat frequency, changes in speed, or changes in orientation, are known to vary by species [1]. The ability to extract these properties from radar data could ultimately enable a species based classification scheme. In this work, we analyze the relationship between radar measurements and bird flight behavior in echoes from avifauna. During the 2014 fall migration season, the UMass dual polarized weather radar was used to collect low elevation observations of migrating birds as they traversed through a fixed antenna beam. The radar was run during the night time, in clear-air conditions. Data was coherently integrated, and detections of biological targets exceeding an SNR threshold were extracted. Detections without some dominant frequency content (i.e. clear periodicity, potentially the wing beat frequency) were removed from the sample in order to isolate observations suspected to contain a single species or bird. For the remaining detections, measurements including the polarimetric products and the Doppler spectrum were extracted at each time step over the duration of the observation. The periodic and time changing nature of some of these different measurements was found to have a strong correlation with flight behavior (i.e. flapping vs. gliding behavior). Assumptions about flight behavior and orientation were corroborated through scattering simulations of birds in flight. The presence of a strong correlation between certain radar measurements and flight behavior would suggest the potential for a broad, species based avian classification algorithm. Such a classification scheme could ultimately help select and monitor wind sites in order to minimize harm to at-risk bird and bat species.

Autonomous target recognition using remotely sensed surface vibration measurements

NASA Astrophysics Data System (ADS)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Online clustering algorithms for radar emitter classification.

PubMed

Liu, Jun; Lee, Jim P Y; Senior; Li, Lingjie; Luo, Zhi-Quan; Wong, K Max

2005-08-01

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters from received radar pulse samples. The main challenges of this task are the high dimensionality of radar pulse samples, small sample group size, and closely located radar pulse clusters. In this paper, two new online clustering algorithms are developed for radar emitter classification: One is model-based using the Minimum Description Length (MDL) criterion and the other is based on competitive learning. Computational complexity is analyzed for each algorithm and then compared. Simulation results show the superior performance of the model-based algorithm over competitive learning in terms of better classification accuracy, flexibility, and stability.

Planetary radar targets 1999 AP10, 2000 TO64, 2000 UJ1, and 2000 XK44: Four S-complex near-Earth asteroids.

NASA Astrophysics Data System (ADS)

Hicks, M.; Lawrence, K.

2009-12-01

We report taxonomic classifications of four near-Earth asteroids (1999 AP10, 2000 TO64, 2000 UJ1, and 2000 XK44) scheduled for radar observation by the JPL radar group at the Arecibo facility in Oct-Nov 2009, using long-slit CCD spectroscopy acquired at the Palomar 5-m telescope on 2009 Nov 09 UT. Table 1 lists the observation circumstances. Normalized reflectance spectra are shown in Figures 1-4 [1]Photonic Breast Tomography and Tumor Aggressiveness Assessment

DTIC Science & Technology

2011-07-01

incorporates, in optical domain, the vector subspace classification method, Multiple Signal Classification ( MUSIC ). MUSIC was developed by Devaney...and co-workers for finding the location of scattering targets whose size is smaller than the wavelength of acoustic waves or electromagnetic waves...general area of array processing for acoustic and radar time-reversal imaging [12]. The eigenvalue equation of TR matrix is solved, and the signal and

Target recognition based on the moment functions of radar signatures

NASA Astrophysics Data System (ADS)

Kim, Kyung-Tae; Kim, Hyo-Tae

2002-03-01

In this paper, we present the results of target recognition research based on the moment functions of various radar signatures, such as time-frequency signatures, range profiles, and scattering centers. The proposed approach utilizes geometrical moments or central moments of the obtained radar signatures. In particular, we derived exact and closed form expressions of the geometrical moments of the adaptive Gaussian representation (AGR), which is one of the adaptive joint time-frequency techniques, and also computed the central moments of range profiles and one-dimensional (1-D) scattering centers on a target, which are obtained by various super-resolution techniques. The obtained moment functions are further processed to provide small dimensional and redundancy-free feature vectors, and classified via a neural network approach or a Bayes classifier. The performances of the proposed technique are demonstrated using a simulated radar cross section (RCS) data set, or a measured RCS data set of various scaled aircraft models, obtained at the Pohang University of Science and Technology (POSTECH) compact range facility. Results show that the techniques in this paper can not only provide reliable classification accuracy, but also save computational resources.

Ballistic missile precession frequency extraction based on the Viterbi & Kalman algorithm

NASA Astrophysics Data System (ADS)

Wu, Longlong; Xie, Yongjie; Xu, Daping; Ren, Li

2015-12-01

Radar Micro-Doppler signatures are of great potential for target detection, classification and recognition. In the mid-course phase, warheads flying outside the atmosphere are usually accompanied by precession. Precession may induce additional frequency modulations on the returned radar signal, which can be regarded as a unique signature and provide additional information that is complementary to existing target recognition methods. The main purpose of this paper is to establish a more actual precession model of conical ballistic missile warhead and extract the precession parameters by utilizing Viterbi & Kalman algorithm, which improving the precession frequency estimation accuracy evidently , especially in low SNR.

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.

Improved Reconstruction of Radio Holographic Signal for Forward Scatter Radar Imaging

PubMed Central

Hu, Cheng; Liu, Changjiang; Wang, Rui; Zeng, Tao

2016-01-01

Forward scatter radar (FSR), as a specially configured bistatic radar, is provided with the capabilities of target recognition and classification by the Shadow Inverse Synthetic Aperture Radar (SISAR) imaging technology. This paper mainly discusses the reconstruction of radio holographic signal (RHS), which is an important procedure in the signal processing of FSR SISAR imaging. Based on the analysis of signal characteristics, the method for RHS reconstruction is improved in two parts: the segmental Hilbert transformation and the reconstruction of mainlobe RHS. In addition, a quantitative analysis of the method’s applicability is presented by distinguishing between the near field and far field in forward scattering. Simulation results validated the method’s advantages in improving the accuracy of RHS reconstruction and imaging. PMID:27164114

SAR target recognition and posture estimation using spatial pyramid pooling within CNN

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-01-01

Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

Three-dimensional laser radar modeling

NASA Astrophysics Data System (ADS)

Steinvall, Ove K.; Carlsson, Tomas

2001-09-01

Laser radars have the unique capability to give intensity and full 3-D images of an object. Doppler lidars can give velocity and vibration characteristics of an objects. These systems have many civilian and military applications such as terrain modelling, depth sounding, object detection and classification as well as object positioning. In order to derive the signal waveform from the object one has to account for the laser pulse time characteristics, media effects such as the atmospheric attenuation and turbulence effects or scattering properties, the target shape and reflection (BRDF), speckle noise together with the receiver and background noise. Finally the type of waveform processing (peak detection, leading edge etc.) is needed to model the sensor output to be compared with observations. We have developed a computer model which models performance of a 3-D laser radar. We will give examples of signal waveforms generated from model different targets calculated by integrating the laser beam profile in space and time over the target including reflection characteristics during different speckle and turbulence conditions. The result will be of help when designing and using new laser radar systems. The importance of different type of signal processing of the waveform in order to fulfil performance goals will be shown.

Intelligent Classification in Huge Heterogeneous Data Sets

DTIC Science & Technology

2015-06-01

Competencies DoD Department of Defense GMTI Ground Moving Target Indicator ISR Intelligence, Surveillance and Reconnaissance NCD Noncoherent Change...Detection OCR Optical Character Recognition PCA Principal Component Analysis SAR Synthetic Aperture Radar SVD Singular Value Decomponsition USPS United States Postal Service 8 Approved for Public Release; Distribution Unlimited.

A radar-enabled collaborative sensor network integrating COTS technology for surveillance and tracking.

PubMed

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R; Demirer, R Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios.

Quantification of Reflection Patterns in Ground-Penetrating Radar Data

NASA Astrophysics Data System (ADS)

Moysey, S.; Knight, R. J.; Jol, H. M.; Allen-King, R. M.; Gaylord, D. R.

2005-12-01

Radar facies analysis provides a way of interpreting the large-scale structure of the subsurface from ground-penetrating radar (GPR) data. Radar facies are often distinguished from each other by the presence of patterns, such as flat-lying, dipping, or chaotic reflections, in different regions of a radar image. When these patterns can be associated with radar facies in a repeated and predictable manner we refer to them as `radar textures'. While it is often possible to qualitatively differentiate between radar textures visually, pattern recognition tools, like neural networks, require a quantitative measure to discriminate between them. We investigate whether currently available tools, such as instantaneous attributes or metrics adapted from standard texture analysis techniques, can be used to improve the classification of radar facies. To this end, we use a neural network to perform cross-validation tests that assess the efficacy of different textural measures for classifying radar facies in GPR data collected from the William River delta, Saskatchewan, Canada. We found that the highest classification accuracies (>93%) were obtained for measures of texture that preserve information about the spatial arrangement of reflections in the radar image, e.g., spatial covariance. Lower accuracy (87%) was obtained for classifications based directly on windows of amplitude data extracted from the radar image. Measures that did not account for the spatial arrangement of reflections in the image, e.g., instantaneous attributes and amplitude variance, yielded classification accuracies of less than 65%. Optimal classifications were obtained for textural measures that extracted sufficient information from the radar data to discriminate between radar facies but were insensitive to other facies specific characteristics. For example, the rotationally invariant Fourier-Mellin transform delivered better classification results than the spatial covariance because dip angle of the reflections, but not dip direction, was an important discriminator between radar facies at the William River delta. To extend the use of radar texture beyond the identification of radar facies to sedimentary facies we are investigating how sedimentary features are encoded in GPR data at Borden, Ontario, Canada. At this site, we have collected extensive sedimentary and hydrologic data over the area imaged by GPR. Analysis of this data coupled with synthetic modeling of the radar signal has allowed us to develop insight into the generation of radar texture in complex geologic environments.

Detection and tracking of human targets in indoor and urban environments using through-the-wall radar sensors

NASA Astrophysics Data System (ADS)

Radzicki, Vincent R.; Boutte, David; Taylor, Paul; Lee, Hua

2017-05-01

Radar based detection of human targets behind walls or in dense urban environments is an important technical challenge with many practical applications in security, defense, and disaster recovery. Radar reflections from a human can be orders of magnitude weaker than those from objects encountered in urban settings such as walls, cars, or possibly rubble after a disaster. Furthermore, these objects can act as secondary reflectors and produce multipath returns from a person. To mitigate these issues, processing of radar return data needs to be optimized for recognizing human motion features such as walking, running, or breathing. This paper presents a theoretical analysis on the modulation effects human motion has on the radar waveform and how high levels of multipath can distort these motion effects. From this analysis, an algorithm is designed and optimized for tracking human motion in heavily clutter environments. The tracking results will be used as the fundamental detection/classification tool to discriminate human targets from others by identifying human motion traits such as predictable walking patterns and periodicity in breathing rates. The theoretical formulations will be tested against simulation and measured data collected using a low power, portable see-through-the-wall radar system that could be practically deployed in real-world scenarios. Lastly, the performance of the algorithm is evaluated in a series of experiments where both a single person and multiple people are moving in an indoor, cluttered environment.

The problem of regime summaries of the data from radar observations. [for cloud system identification

NASA Technical Reports Server (NTRS)

Divinskaya, B. S.; Salman, Y. M.

1975-01-01

Peculiarities of the radar information about clouds are examined in comparison with visual data. An objective radar classification is presented and the relation of it to the meteorological classification is shown. The advisability of storage and summarization of the primary radar data for regime purposes is substantiated.

Random Forest Application for NEXRAD Radar Data Quality Control

NASA Astrophysics Data System (ADS)

Keem, M.; Seo, B. C.; Krajewski, W. F.

2017-12-01

Identification and elimination of non-meteorological radar echoes (e.g., returns from ground, wind turbines, and biological targets) are the basic data quality control steps before radar data use in quantitative applications (e.g., precipitation estimation). Although WSR-88Ds' recent upgrade to dual-polarization has enhanced this quality control and echo classification, there are still challenges to detect some non-meteorological echoes that show precipitation-like characteristics (e.g., wind turbine or anomalous propagation clutter embedded in rain). With this in mind, a new quality control method using Random Forest is proposed in this study. This classification algorithm is known to produce reliable results with less uncertainty. The method introduces randomness into sampling and feature selections and integrates consequent multiple decision trees. The multidimensional structure of the trees can characterize the statistical interactions of involved multiple features in complex situations. The authors explore the performance of Random Forest method for NEXRAD radar data quality control. Training datasets are selected using several clear cases of precipitation and non-precipitation (but with some non-meteorological echoes). The model is structured using available candidate features (from the NEXRAD data) such as horizontal reflectivity, differential reflectivity, differential phase shift, copolar correlation coefficient, and their horizontal textures (e.g., local standard deviation). The influence of each feature on classification results are quantified by variable importance measures that are automatically estimated by the Random Forest algorithm. Therefore, the number and types of features in the final forest can be examined based on the classification accuracy. The authors demonstrate the capability of the proposed approach using several cases ranging from distinct to complex rain/no-rain events and compare the performance with the existing algorithms (e.g., MRMS). They also discuss operational feasibility based on the observed strength and weakness of the method.

Polarimetric SAR Models for Oil Fields Monitoring in China Seas

NASA Astrophysics Data System (ADS)

Buono, A.; Nunziata, F.; Li, X.; Wei, Y.; Ding, X.

2014-11-01

In this study, physical-based models for polarimetric Synthetic Aperture Radar (SAR) oil fields monitoring are proposed. They all share a physical rationale relying on the different scattering mechanisms that characterize a free sea surface, an oil slick-covered sea surface, and a metallic target. In fact, sea surface scattering is well modeled by a Bragg-like behaviour, while a strong departure from Bragg scattering is in place when dealing with oil slicks and targets. Furthermore, the proposed polarimetric models aim at addressing simultaneously target and oil slick detection, providing useful extra information with respect to single-pol SAR data in order to approach oil discrimination and classification. Experiments undertaken over East and South China Sea from actual C-band RadarSAT-2 full-pol SAR data witness the soundness of the proposed rationale.

Polarimetric SAR Models for Oil Fields Monitoring in China Seas

NASA Astrophysics Data System (ADS)

Buono, A.; Nunziata, F.; Li, X.; Wei, Y.; Ding, X.

2014-11-01

In this study, physical-based models for polarimetric Synthetic Aperture Radar (SAR) oil fields monitoring are proposed. They all share a physical rationale relying on the different scattering mechanisms that characterize a free sea surface, an oil slick-covered sea surface, and a metallic target. In fact, sea surface scattering is well modeled by a Bragg-like behaviour, while a strong departure from Bragg scattering is in place when dealing with oil slicks and targets. Furthermore, the proposed polarimetric models aim at addressing simultaneously target and oil slick detection, providing useful extra information with respect to single-pol SAR data in order to approach oil discrimination and classification.Experiments undertaken over East and South China Sea from actual C-band RadarSAT-2 full-pol SAR data witness the soundness of the proposed rationale.

A Radar-Enabled Collaborative Sensor Network Integrating COTS Technology for Surveillance and Tracking

PubMed Central

Kozma, Robert; Wang, Lan; Iftekharuddin, Khan; McCracken, Ernest; Khan, Muhammad; Islam, Khandakar; Bhurtel, Sushil R.; Demirer, R. Murat

2012-01-01

The feasibility of using Commercial Off-The-Shelf (COTS) sensor nodes is studied in a distributed network, aiming at dynamic surveillance and tracking of ground targets. Data acquisition by low-cost (<$50 US) miniature low-power radar through a wireless mote is described. We demonstrate the detection, ranging and velocity estimation, classification and tracking capabilities of the mini-radar, and compare results to simulations and manual measurements. Furthermore, we supplement the radar output with other sensor modalities, such as acoustic and vibration sensors. This method provides innovative solutions for detecting, identifying, and tracking vehicles and dismounts over a wide area in noisy conditions. This study presents a step towards distributed intelligent decision support and demonstrates effectiveness of small cheap sensors, which can complement advanced technologies in certain real-life scenarios. PMID:22438713

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

SAR Image Simulation of Ship Targets Based on Multi-Path Scattering

NASA Astrophysics Data System (ADS)

Guo, Y.; Wang, H.; Ma, H.; Li, K.; Xia, Z.; Hao, Y.; Guo, H.; Shi, H.; Liao, X.; Yue, H.

2018-04-01

Synthetic Aperture Radar (SAR) plays an important role in the classification and recognition of ship targets because of its all-weather working ability and fine resolution. In SAR images, besides the sea clutter, the influence of the sea surface on the radar echo is also known as the so-called multipath effect. These multipath effects will generate some extra "pseudo images", which may cause the distortion of the target image and affect the estimation of the characteristic parameters. In this paper,the multipath effect of rough sea surface and its influence on the estimation of ship characteristic parameters are studied. The imaging of the first and the secondary reflection of sea surface is presented . The artifacts not only overlap with the image of the target itself, but may also appear in the sea near the target area. It is difficult to distinguish them, and this artifact has an effect on the length and width of the ship.

Feature-based RNN target recognition

NASA Astrophysics Data System (ADS)

Bakircioglu, Hakan; Gelenbe, Erol

1998-09-01

Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

Terrain feature recognition for synthetic aperture radar (SAR) imagery employing spatial attributes of targets

NASA Astrophysics Data System (ADS)

Iisaka, Joji; Sakurai-Amano, Takako

1994-08-01

This paper describes an integrated approach to terrain feature detection and several methods to estimate spatial information from SAR (synthetic aperture radar) imagery. Spatial information of image features as well as spatial association are key elements in terrain feature detection. After applying a small feature preserving despeckling operation, spatial information such as edginess, texture (smoothness), region-likeliness and line-likeness of objects, target sizes, and target shapes were estimated. Then a trapezoid shape fuzzy membership function was assigned to each spatial feature attribute. Fuzzy classification logic was employed to detect terrain features. Terrain features such as urban areas, mountain ridges, lakes and other water bodies as well as vegetated areas were successfully identified from a sub-image of a JERS-1 SAR image. In the course of shape analysis, a quantitative method was developed to classify spatial patterns by expanding a spatial pattern through the use of a series of pattern primitives.

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Jung, B.; Gillespie, K.; Hemmat, M.; Aslam, A.; Brunfeldt, D.; Dobson, M. C.

1983-01-01

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

A target recognition method for maritime surveillance radars based on hybrid ensemble selection

NASA Astrophysics Data System (ADS)

Fan, Xueman; Hu, Shengliang; He, Jingbo

2017-11-01

In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

Assessing the performance of a covert automatic target recognition algorithm

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2005-05-01

Passive radar systems exploit illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. Doing so allows them to operate covertly and inexpensively. Our research seeks to enhance passive radar systems by adding automatic target recognition (ATR) capabilities. In previous papers we proposed conducting ATR by comparing the radar cross section (RCS) of aircraft detected by a passive radar system to the precomputed RCS of aircraft in the target class. To effectively model the low-frequency setting, the comparison is made via a Rician likelihood model. Monte Carlo simulations indicate that the approach is viable. This paper builds on that work by developing a method for quickly assessing the potential performance of the ATR algorithm without using exhaustive Monte Carlo trials. This method exploits the relation between the probability of error in a binary hypothesis test under the Bayesian framework to the Chernoff information. Since the data are well-modeled as Rician, we begin by deriving a closed-form approximation for the Chernoff information between two Rician densities. This leads to an approximation for the probability of error in the classification algorithm that is a function of the number of available measurements. We conclude with an application that would be particularly cumbersome to accomplish via Monte Carlo trials, but that can be quickly addressed using the Chernoff information approach. This application evaluates the length of time that an aircraft must be tracked before the probability of error in the ATR algorithm drops below a desired threshold.

A robust algorithm for automated target recognition using precomputed radar cross sections

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2004-09-01

Passive radar is an emerging technology that offers a number of unique benefits, including covert operation. Many such systems are already capable of detecting and tracking aircraft. The goal of this work is to develop a robust algorithm for adding automated target recognition (ATR) capabilities to existing passive radar systems. In previous papers, we proposed conducting ATR by comparing the precomputed RCS of known targets to that of detected targets. To make the precomputed RCS as accurate as possible, a coordinated flight model is used to estimate aircraft orientation. Once the aircraft's position and orientation are known, it is possible to determine the incident and observed angles on the aircraft, relative to the transmitter and receiver. This makes it possible to extract the appropriate radar cross section (RCS) from our simulated database. This RCS is then scaled to account for propagation losses and the receiver's antenna gain. A Rician likelihood model compares these expected signals from different targets to the received target profile. We have previously employed Monte Carlo runs to gauge the probability of error in the ATR algorithm; however, generation of a statistically significant set of Monte Carlo runs is computationally intensive. As an alternative to Monte Carlo runs, we derive the relative entropy (also known as Kullback-Liebler distance) between two Rician distributions. Since the probability of Type II error in our hypothesis testing problem can be expressed as a function of the relative entropy via Stein's Lemma, this provides us with a computationally efficient method for determining an upper bound on our algorithm's performance. It also provides great insight into the types of classification errors we can expect from our algorithm. This paper compares the numerically approximated probability of Type II error with the results obtained from a set of Monte Carlo runs.

Integrated Range-Doppler Map and Extended Target Classification with Adaptive Waveform for Cognitive Radar

DTIC Science & Technology

2014-12-01

location for multiple targets of unknown types assuming unity noise energy ( 10ψ = percent and FAP = 0.1...2E )),D FAP Q Q P NR −= − (51) where 2sE NR /x hE E σ= where sE specifically means return (echo) energy using the wideband waveform. It can...probabilities ( FAP ). Considering Fig. 22, the performance of the eigenwaveform is superior to rectangular and wideband waveforms (given a fixed FAP

Developing an Automated Machine Learning Marine Oil Spill Detection System with Synthetic Aperture Radar

NASA Astrophysics Data System (ADS)

Pinales, J. C.; Graber, H. C.; Hargrove, J. T.; Caruso, M. J.

2016-02-01

Previous studies have demonstrated the ability to detect and classify marine hydrocarbon films with spaceborne synthetic aperture radar (SAR) imagery. The dampening effects of hydrocarbon discharges on small surface capillary-gravity waves renders the ocean surface "radar dark" compared with the standard wind-borne ocean surfaces. Given the scope and impact of events like the Deepwater Horizon oil spill, the need for improved, automated and expedient monitoring of hydrocarbon-related marine anomalies has become a pressing and complex issue for governments and the extraction industry. The research presented here describes the development, training, and utilization of an algorithm that detects marine oil spills in an automated, semi-supervised manner, utilizing X-, C-, or L-band SAR data as the primary input. Ancillary datasets include related radar-borne variables (incidence angle, etc.), environmental data (wind speed, etc.) and textural descriptors. Shapefiles produced by an experienced human-analyst served as targets (validation) during the training portion of the investigation. Training and testing datasets were chosen for development and assessment of algorithm effectiveness as well as optimal conditions for oil detection in SAR data. The algorithm detects oil spills by following a 3-step methodology: object detection, feature extraction, and classification. Previous oil spill detection and classification methodologies such as machine learning algorithms, artificial neural networks (ANN), and multivariate classification methods like partial least squares-discriminant analysis (PLS-DA) are evaluated and compared. Statistical, transform, and model-based image texture techniques, commonly used for object mapping directly or as inputs for more complex methodologies, are explored to determine optimal textures for an oil spill detection system. The influence of the ancillary variables is explored, with a particular focus on the role of strong vs. weak wind forcing.

Use of multi-frequency, multi-polarization, multi-angle airborne radars for class discrimination in a southern temperature forest

NASA Technical Reports Server (NTRS)

Mehta, N. C.

1984-01-01

The utility of radar scatterometers for discrimination and characterization of natural vegetation was investigated. Backscatter measurements were acquired with airborne multi-frequency, multi-polarization, multi-angle radar scatterometers over a test site in a southern temperate forest. Separability between ground cover classes was studied using a two-class separability measure. Very good separability is achieved between most classes. Longer wavelength is useful in separating trees from non-tree classes, while shorter wavelength and cross polarization are helpful for discrimination among tree classes. Using the maximum likelihood classifier, 50% overall classification accuracy is achieved using a single, short-wavelength scatterometer channel. Addition of multiple incidence angles and another radar band improves classification accuracy by 20% and 50%, respectively, over the single channel accuracy. Incorporation of a third radar band seems redundant for vegetation classification. Vertical transmit polarization is critically important for all classes.

Comparative of signal processing techniques for micro-Doppler signature extraction with automotive radar systems

NASA Astrophysics Data System (ADS)

Rodriguez-Hervas, Berta; Maile, Michael; Flores, Benjamin C.

2014-05-01

In recent years, the automotive industry has experienced an evolution toward more powerful driver assistance systems that provide enhanced vehicle safety. These systems typically operate in the optical and microwave regions of the electromagnetic spectrum and have demonstrated high efficiency in collision and risk avoidance. Microwave radar systems are particularly relevant due to their operational robustness under adverse weather or illumination conditions. Our objective is to study different signal processing techniques suitable for extraction of accurate micro-Doppler signatures of slow moving objects in dense urban environments. Selection of the appropriate signal processing technique is crucial for the extraction of accurate micro-Doppler signatures that will lead to better results in a radar classifier system. For this purpose, we perform simulations of typical radar detection responses in common driving situations and conduct the analysis with several signal processing algorithms, including short time Fourier Transform, continuous wavelet or Kernel based analysis methods. We take into account factors such as the relative movement between the host vehicle and the target, and the non-stationary nature of the target's movement. A comparison of results reveals that short time Fourier Transform would be the best approach for detection and tracking purposes, while the continuous wavelet would be the best suited for classification purposes.

Imaging laser radar for high-speed monitoring of the environment

NASA Astrophysics Data System (ADS)

Froehlich, Christoph; Mettenleiter, M.; Haertl, F.

1998-01-01

In order to establish mobile robot operations and to realize survey and inspection tasks, robust and precise measurements of the geometry of the 3D environment is the basis sensor technology. For visual inspection, surface classification, and documentation purposes, however, additional information concerning reflectance of measured objects is necessary. High-speed acquisition of both geometric and visual information is achieved by means of an active laser radar, supporting consistent range and reflectance images. The laser radar developed at Zoller + Froehlich (ZF) is an optical-wavelength system measuring the range between sensor and target surface as well as the reflectance of the target surface, which corresponds to the magnitude of the back scattered laser energy. In contrast to other range sensing devices, the ZF system is designed for high-speed and high- performance operation in real indoor and outdoor environments, emitting a minimum of near-IR laser energy. It integrates a single-point laser measurement system and a mechanical deflection system for 3D environmental measurements. This paper reports details of the laser radar which is designed to cover requirements with medium range applications. It outlines the performance requirements and introduces the two-frequency phase-shift measurement principle. The hardware design of the single-point laser measurement system, including the main modulates, such as the laser head, the high frequency unit and the signal processing unit are discussed in detail. The paper focuses on performance data of the laser radar, including noise, drift over time, precision, and accuracy with measurements. It discusses the influences of ambient light, surface material of the target, and ambient temperature for range accuracy and range precision. Furthermore, experimental results from inspection of tunnels, buildings, monuments and industrial environments are presented. The paper concludes by summarizing results and gives a short outlook to future work.

Development and Testing of a Multiple Frequency Continuous Wave Radar for Target Detection and Classification

DTIC Science & Technology

2007-03-01

1 2’ VIH " 1 ’ 󈧏) (34) where is the modified Bessel function of zero order. Here is the conditional variance and is the conditional probability...10, the probability of detection is the area under the signal-plus-noise curve above the detection threshold co M vF (V 2+ A2)]10 ( vAPd= fnp~ju,( vIH

Holographic neural networks versus conventional neural networks: a comparative evaluation for the classification of landmine targets in ground-penetrating radar images

NASA Astrophysics Data System (ADS)

Mudigonda, Naga R.; Kacelenga, Ray; Edwards, Mark

2004-09-01

This paper evaluates the performance of a holographic neural network in comparison with a conventional feedforward backpropagation neural network for the classification of landmine targets in ground penetrating radar images. The data used in the study was acquired from four different test sites using the landmine detection system developed by General Dynamics Canada Ltd., in collaboration with the Defense Research and Development Canada, Suffield. A set of seven features extracted for each detected alarm is used as stimulus inputs for the networks. The recall responses of the networks are then evaluated against the ground truth to declare true or false detections. The area computed under the receiver operating characteristic curve is used for comparative purposes. With a large dataset comprising of data from multiple sites, both the holographic and conventional networks showed comparable trends in recall accuracies with area values of 0.88 and 0.87, respectively. By using independent validation datasets, the holographic network"s generalization performance was observed to be better (mean area = 0.86) as compared to the conventional network (mean area = 0.82). Despite the widely publicized theoretical advantages of the holographic technology, use of more than the required number of cortical memory elements resulted in an over-fitting phenomenon of the holographic network.

Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns.

PubMed

Kauppi, Jukka-Pekka; Martikainen, Kalle; Ruotsalainen, Ulla

2010-12-01

The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals. Currently, there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms. Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex, dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems. To assist recognition of complex radar emissions in modern intercept receivers, we have developed a novel method to recognize dynamically varying pulse repetition interval (PRI) modulation patterns emitted by MFRs. We use robust feature extraction and classifier design techniques to assist recognition in unpredictable real-world signal environments. We classify received pulse trains hierarchically which allows unambiguous detection of the subpatterns using a sliding window. Accuracy, robustness and reliability of the technique are demonstrated with extensive simulations using both static and dynamically varying PRI modulation patterns. Copyright © 2010 Elsevier Ltd. All rights reserved.

Improving crop classification through attention to the timing of airborne radar acquisitions

NASA Technical Reports Server (NTRS)

Brisco, B.; Ulaby, F. T.; Protz, R.

1984-01-01

Radar remote sensors may provide valuable input to crop classification procedures because of (1) their independence of weather conditions and solar illumination, and (2) their ability to respond to differences in crop type. Manual classification of multidate synthetic aperture radar (SAR) imagery resulted in an overall accuracy of 83 percent for corn, forest, grain, and 'other' cover types. Forests and corn fields were identified with accuracies approaching or exceeding 90 percent. Grain fields and 'other' fields were often confused with each other, resulting in classification accuracies of 51 and 66 percent, respectively. The 83 percent correct classification represents a 10 percent improvement when compared to similar SAR data for the same area collected at alternate time periods in 1978. These results demonstrate that improvements in crop classification accuracy can be achieved with SAR data by synchronizing data collection times with crop growth stages in order to maximize differences in the geometric and dielectric properties of the cover types of interest.

Active acoustic classification via transient resonance scattering

NASA Astrophysics Data System (ADS)

Gaunaurd, Guillermo C.

1992-12-01

The echoes reflected by a sound ping emerging from active sonar when it interacts with a target in its path can be remotely sensed by a receiver. The presented approach capitalizes on an air inverse scattering method that exploits the presence of certain resonance features in these echoes returned by targets to classify them. Classifying underwater objects is important to naval programs such as mine countermeasures (MC) and anti-submarine warfare (ASW) to preclude wasting of ordnance on false targets. Although the classification of complex shapes is still a formidable task, considerable progress has been made in classifying simple shapes such as spheroidal or cylindrical shells. The briefly overviewed methodology has emphasized the extraction, isolation, and labeling of resonance features hidden within the echo, but little has been said about how these could be used to classify a target. A couple of simple examples illustrate exactly how these resonances can be linked to the physical characteristics of the target, allowing for its unambiguous characterization. The procedure, although illustrated with active acoustics (i.e., sonar), can be extended to any active return from any sensor, including radar.

Pedestrian recognition using automotive radar sensors

NASA Astrophysics Data System (ADS)

Bartsch, A.; Fitzek, F.; Rasshofer, R. H.

2012-09-01

The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

Surface Water Detection Using Fused Synthetic Aperture Radar, Airborne LiDAR and Optical Imagery

NASA Astrophysics Data System (ADS)

Braun, A.; Irwin, K.; Beaulne, D.; Fotopoulos, G.; Lougheed, S. C.

2016-12-01

Each remote sensing technique has its unique set of strengths and weaknesses, but by combining techniques the classification accuracy can be increased. The goal of this project is to underline the strengths and weaknesses of Synthetic Aperture Radar (SAR), LiDAR and optical imagery data and highlight the opportunities where integration of the three data types can increase the accuracy of identifying water in a principally natural landscape. The study area is located at the Queen's University Biological Station, Ontario, Canada. TerraSAR-X (TSX) data was acquired between April and July 2016, consisting of four single polarization (HH) staring spotlight mode backscatter intensity images. Grey-level thresholding is used to extract surface water bodies, before identifying and masking zones of radar shadow and layover by using LiDAR elevation models to estimate the canopy height and applying simple geometry algorithms. The airborne LiDAR survey was conducted in June 2014, resulting in a discrete return dataset with a density of 1 point/m2. Radiometric calibration to correct for range and incidence angle is applied, before classifying the points as water or land based on corrected intensity, elevation, roughness, and intensity density. Panchromatic and multispectral (4-band) imagery from Quickbird was collected in September 2005 at spatial resolutions of 0.6m and 2.5m respectively. Pixel-based classification is applied to identify and distinguish water bodies from land. A classification system which inputs SAR-, LiDAR- and optically-derived water presence models in raster formats is developed to exploit the strengths and weaknesses of each technique. The total percentage of water detected in the sample area for SAR backscatter, LiDAR intensity, and optical imagery was 27%, 19% and 18% respectively. The output matrix of the classification system indicates that in over 72% of the study area all three methods agree on the classification. Analysis was specifically targeted towards areas where the methods disagree, highlighting how each technique should be properly weighted over these areas to increase the classification accuracy of water. The conclusions and techniques developed in this study are applicable to other areas where similar environmental conditions and data availability exist.

Integrated Strike Avionics Study. Volume 1

DTIC Science & Technology

1980-10-01

MMW Systems Targeting Studies Perf. Meas. o C02 Laser Radar Ses. St. Army Obstacle Detect Prog. Concept Demo Mobile System 20 ’ - I...Fabrication and Test o FLIR Field of View & Classification Study (FLIR FACS) Definition m Development & Test 4. Aplicability of Current Programs to...FY80 81 8283 84 85 o LANTIRN 1 n Imaoinn Sensor Autoprocessor • o Forward Looking Active Class a 4. Aplicability of Current Program Required The need

A new FOD recognition algorithm based on multi-source information fusion and experiment analysis

NASA Astrophysics Data System (ADS)

Li, Yu; Xiao, Gang

2011-08-01

Foreign Object Debris (FOD) is a kind of substance, debris or article alien to an aircraft or system, which would potentially cause huge damage when it appears on the airport runway. Due to the airport's complex circumstance, quick and precise detection of FOD target on the runway is one of the important protections for airplane's safety. A multi-sensor system including millimeter-wave radar and Infrared image sensors is introduced and a developed new FOD detection and recognition algorithm based on inherent feature of FOD is proposed in this paper. Firstly, the FOD's location and coordinate can be accurately obtained by millimeter-wave radar, and then according to the coordinate IR camera will take target images and background images. Secondly, in IR image the runway's edges which are straight lines can be extracted by using Hough transformation method. The potential target region, that is, runway region, can be segmented from the whole image. Thirdly, background subtraction is utilized to localize the FOD target in runway region. Finally, in the detailed small images of FOD target, a new characteristic is discussed and used in target classification. The experiment results show that this algorithm can effectively reduce the computational complexity, satisfy the real-time requirement and possess of high detection and recognition probability.

Characteristics of Forests in Western Sayani Mountains, Siberia from SAR Data

NASA Technical Reports Server (NTRS)

Ranson, K. Jon; Sun, Guoqing; Kharuk, V. I.; Kovacs, Katalin

1998-01-01

This paper investigated the possibility of using spaceborne radar data to map forest types and logging in the mountainous Western Sayani area in Siberia. L and C band HH, HV, and VV polarized images from the Shuttle Imaging Radar-C instrument were used in the study. Techniques to reduce topographic effects in the radar images were investigated. These included radiometric correction using illumination angle inferred from a digital elevation model, and reducing apparent effects of topography through band ratios. Forest classification was performed after terrain correction utilizing typical supervised techniques and principal component analyses. An ancillary data set of local elevations was also used to improve the forest classification. Map accuracy for each technique was estimated for training sites based on Russian forestry maps, satellite imagery and field measurements. The results indicate that it is necessary to correct for topography when attempting to classify forests in mountainous terrain. Radiometric correction based on a DEM (Digital Elevation Model) improved classification results but required reducing the SAR (Synthetic Aperture Radar) resolution to match the DEM. Using ratios of SAR channels that include cross-polarization improved classification and

Objective Classification of Radar Profile Types, and Their Relationship to Lightning Occurrence

NASA Technical Reports Server (NTRS)

Boccippio, Dennis

2003-01-01

A cluster analysis technique is used to identify 16 "archetypal" vertical radar profile types from a large, globally representative sample of profiles from the TRMM Precipitation Radar. These include nine convective types (7 of these deep convective) and seven stratiform types (5 of these clearly glaciated). Radar profile classification provides an alternative to conventional deep convective storm metrics, such as 30 dBZ echo height, maximum reflectivity or VIL. As expected, the global frequency of occurrence of deep convective profile types matches satellite-observed total lightning production, including to very small scall local features. Each location's "mix" of profile types provides an objective description of the local convective spectrum, and in turn, is a first step in objectively classifying convective regimes. These classifiers are tested as inputs to a neural network which attempts to predict lightning occurrence based on radar-only storm observations, and performance is compared with networks using traditional radar metrics as inputs.

Per-point and per-field contextual classification of multipolarization and multiple incidence angle aircraft L-band radar data

NASA Technical Reports Server (NTRS)

Hoffer, Roger M.; Hussin, Yousif Ali

1989-01-01

Multipolarized aircraft L-band radar data are classified using two different image classification algorithms: (1) a per-point classifier, and (2) a contextual, or per-field, classifier. Due to the distinct variations in radar backscatter as a function of incidence angle, the data are stratified into three incidence-angle groupings, and training and test data are defined for each stratum. A low-pass digital mean filter with varied window size (i.e., 3x3, 5x5, and 7x7 pixels) is applied to the data prior to the classification. A predominately forested area in northern Florida was the study site. The results obtained by using these image classifiers are then presented and discussed.

Progress in coherent laser radar

NASA Technical Reports Server (NTRS)

Vaughan, J. M.

1986-01-01

Considerable progress with coherent laser radar has been made over the last few years, most notably perhaps in the available range of high performance devices and components and the confidence with which systems may now be taken into the field for prolonged periods of operation. Some of this increasing maturity was evident at the 3rd Topical Meeting on Coherent Laser Radar: Technology and Applications. Topics included in discussions were: mesoscale wind fields, nocturnal valley drainage and clear air down bursts; airborne Doppler lidar studies and comparison of ground and airborne wind measurement; wind measurement over the sea for comparison with satellite borne microwave sensors; transport of wake vortices at airfield; coherent DIAL methods; a newly assembled Nd-YAG coherent lidar system; backscatter profiles in the atmosphere and wavelength dependence over the 9 to 11 micrometer region; beam propagation; rock and soil classification with an airborne 4-laser system; technology of a global wind profiling system; target calibration; ranging and imaging with coherent pulsed and CW system; signal fluctuations and speckle. Some of these activities are briefly reviewed.

3D Target Localization of Modified 3D MUSIC for a Triple-Channel K-Band Radar.

PubMed

Li, Ying-Chun; Choi, Byunggil; Chong, Jong-Wha; Oh, Daegun

2018-05-20

In this paper, a modified 3D multiple signal classification (MUSIC) algorithm is proposed for joint estimation of range, azimuth, and elevation angles of K-band radar with a small 2 × 2 horn antenna array. Three channels of the 2 × 2 horn antenna array are utilized as receiving channels, and the other one is a transmitting antenna. The proposed modified 3D MUSIC is designed to make use of a stacked autocorrelation matrix, whose element matrices are related to each other in the spatial domain. An augmented 2D steering vector based on the stacked autocorrelation matrix is proposed for the modified 3D MUSIC, instead of the conventional 3D steering vector. The effectiveness of the proposed modified 3D MUSIC is verified through implementation with a K-band frequency-modulated continuous-wave (FMCW) radar with the 2 × 2 horn antenna array through a variety of experiments in a chamber.

Signal analysis by means of time-frequency (Wigner-type) distributions -- Applications to sonar and radar echoes

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

Gaunaurd, G.; Strifors, H.C.

1996-09-01

Time series data have been traditionally analyzed in either the time or the frequency domains. For signals with a time-varying frequency content, the combined time-frequency (TF) representations, based on the Cohen class of (generalized) Wigner distributions (WD`s) offer a powerful analysis tool. Using them, it is possible to: (1) trace the time-evolution of the resonance features usually present in a standard sonar cross section (SCS), or in a radar cross section (RCS) and (2) extract target information that may be difficult to even notice in an ordinary SCS or RCS. After a brief review of the fundamental properties of themore » WD, the authors discuss ways to reduce or suppress the cross term interference that appears in the WD of multicomponent systems. These points are illustrated with a variety of three-dimensional (3-D) plots of Wigner and pseudo-Wigner distributions (PWD), in which the strength of the distribution is depicted as the height of a Wigner surface with height scales measured by various color shades or pseudocolors. The authors also review studies they have made of the echoes returned by conducting or dielectric targets in the atmosphere, when they are illuminated by broadband radar pings. A TF domain analysis of these impulse radar returns demonstrates their superior informative content. These plots allow the identification of targets in an easier and clearer fashion than by the conventional RCS of narrowband systems. The authors show computed and measured plots of WD and PWD of various types of aircraft to illustrate the classification advantages of the approach at any aspect angle. They also show analogous results for metallic objects buried underground, in dielectric media, at various depths.« less

Active laser radar (lidar) for measurement of corresponding height and reflectance images

NASA Astrophysics Data System (ADS)

Froehlich, Christoph; Mettenleiter, M.; Haertl, F.

1997-08-01

For the survey and inspection of environmental objects, a non-tactile, robust and precise imaging of height and depth is the basis sensor technology. For visual inspection,surface classification, and documentation purposes, however, additional information concerning reflectance of measured objects is necessary. High-speed acquisition of both geometric and visual information is achieved by means of an active laser radar, supporting consistent 3D height and 2D reflectance images. The laser radar is an optical-wavelength system, and is comparable to devices built by ERIM, Odetics, and Perceptron, measuring the range between sensor and target surfaces as well as the reflectance of the target surface, which corresponds to the magnitude of the back scattered laser energy. In contrast to these range sensing devices, the laser radar under consideration is designed for high speed and precise operation in both indoor and outdoor environments, emitting a minimum of near-IR laser energy. It integrates a laser range measurement system and a mechanical deflection system for 3D environmental measurements. This paper reports on design details of the laser radar for surface inspection tasks. It outlines the performance requirements and introduces the measurement principle. The hardware design, including the main modules, such as the laser head, the high frequency unit, the laser beam deflection system, and the digital signal processing unit are discussed.the signal processing unit consists of dedicated signal processors for real-time sensor data preprocessing as well as a sensor computer for high-level image analysis and feature extraction. The paper focuses on performance data of the system, including noise, drift over time, precision, and accuracy with measurements. It discuses the influences of ambient light, surface material of the target, and ambient temperature for range accuracy and range precision. Furthermore, experimental results from inspection of buildings, monuments and industrial environments are presented. The paper concludes by summarizing results achieved in industrial environments and gives a short outlook to future work.

Segmentation, classification, and pose estimation of military vehicles in low resolution laser radar images

NASA Astrophysics Data System (ADS)

Neulist, Joerg; Armbruster, Walter

2005-05-01

Model-based object recognition in range imagery typically involves matching the image data to the expected model data for each feasible model and pose hypothesis. Since the matching procedure is computationally expensive, the key to efficient object recognition is the reduction of the set of feasible hypotheses. This is particularly important for military vehicles, which may consist of several large moving parts such as the hull, turret, and gun of a tank, and hence require an eight or higher dimensional pose space to be searched. The presented paper outlines techniques for reducing the set of feasible hypotheses based on an estimation of target dimensions and orientation. Furthermore, the presence of a turret and a main gun and their orientations are determined. The vehicle parts dimensions as well as their error estimates restrict the number of model hypotheses whereas the position and orientation estimates and their error bounds reduce the number of pose hypotheses needing to be verified. The techniques are applied to several hundred laser radar images of eight different military vehicles with various part classifications and orientations. On-target resolution in azimuth, elevation and range is about 30 cm. The range images contain up to 20% dropouts due to atmospheric absorption. Additionally some target retro-reflectors produce outliers due to signal crosstalk. The presented algorithms are extremely robust with respect to these and other error sources. The hypothesis space for hull orientation is reduced to about 5 degrees as is the error for turret rotation and gun elevation, provided the main gun is visible.

A simulation study of the effects of land cover and crop type on sensing soil moisture with an orbital C-band radar

NASA Technical Reports Server (NTRS)

Dobson, M. C.; Ulaby, F. T.; Moezzi, S.; Roth, E.

1983-01-01

Simulated C-band radar imagery for a 124-km by 108-km test site in eastern Kansas is used to classify soil moisture. Simulated radar resolutions are 100 m by 100 m, 1 km by 1 km, and 3 km by 3 km, and each is processed using more than 23 independent samples. Moisture classification errors are examined as a function of land-cover distribution, field-size distribution, and local topographic relief for the full test site and also for subregions of cropland, urban areas, woodland, and pasture/rangeland. Results show that a radar resolution of 100 m by 100 m yields the most robust classification accuracies.

Extended target recognition in cognitive radar networks.

PubMed

Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

2010-01-01

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

Salient Feature Identification and Analysis using Kernel-Based Classification Techniques for Synthetic Aperture Radar Automatic Target Recognition

DTIC Science & Technology

2014-03-27

and machine learning for a range of research including such topics as medical imaging [10] and handwriting recognition [11]. The type of feature...1989. [11] C. Bahlmann, B. Haasdonk, and H. Burkhardt, “Online handwriting recognition with support vector machines-a kernel approach,” in Eighth...International Workshop on Frontiers in Handwriting Recognition, pp. 49–54, IEEE, 2002. [12] C. Cortes and V. Vapnik, “Support-vector networks,” Machine

Advancement of High Resolution Radar Polarimetry in Target Verses Clutter Detection, Discrimination, Classification: A. Basic Theory and Modeling of Polarimetric Clutter Phenomenology.

DTIC Science & Technology

1988-07-15

the interim period, polarimetLic measurement data collected at other DOD/NATO/Industrial R/D/M facilities will be used. These basic studies will be...the polarization sphere and its spread can he related either to the coherency factor or the depolarization factor plus descriptive parameters of the...careful study of the concluding sections outlining the overall scenario of solved and unsolved problems. Here, we also refer to the recent report (Dec

A Dual-Wavelength Radar Technique to Detect Hydrometeor Phases

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert

2016-01-01

This study is aimed at investigating the feasibility of a Ku- and Ka-band space/air-borne dual wavelength radar algorithm to discriminate various phase states of precipitating hydrometeors. A phase-state classification algorithm has been developed from the radar measurements of snow, mixed-phase and rain obtained from stratiform storms. The algorithm, presented in the form of the look-up table that links the Ku-band radar reflectivities and dual-frequency ratio (DFR) to the phase states of hydrometeors, is checked by applying it to the measurements of the Jet Propulsion Laboratory, California Institute of Technology, Airborne Precipitation Radar Second Generation (APR-2). In creating the statistically-based phase look-up table, the attenuation corrected (or true) radar reflectivity factors are employed, leading to better accuracy in determining the hydrometeor phase. In practice, however, the true radar reflectivities are not always available before the phase states of the hydrometeors are determined. Therefore, it is desirable to make use of the measured radar reflectivities in classifying the phase states. To do this, a phase-identification procedure is proposed that uses only measured radar reflectivities. The procedure is then tested using APR-2 airborne radar data. Analysis of the classification results in stratiform rain indicates that the regions of snow, mixed-phase and rain derived from the phase-identification algorithm coincide reasonably well with those determined from the measured radar reflectivities and linear depolarization ratio (LDR).

Identification of hydrometeor mixtures in polarimetric radar measurements and their linear de-mixing

NASA Astrophysics Data System (ADS)

Besic, Nikola; Ventura, Jordi Figueras i.; Grazioli, Jacopo; Gabella, Marco; Germann, Urs; Berne, Alexis

2017-04-01

The issue of hydrometeor mixtures affects radar sampling volumes without a clear dominant hydrometeor type. Containing a number of different hydrometeor types which significantly contribute to the polarimetric variables, these volumes are likely to occur in the vicinity of the melting layer and mainly, at large distance from a given radar. Motivated by potential benefits for both quantitative and qualitative applications of dual-pol radar, we propose a method for the identification of hydrometeor mixtures and their subsequent linear de-mixing. This method is intrinsically related to our recently proposed semi-supervised approach for hydrometeor classification. The mentioned classification approach [1] performs labeling of radar sampling volumes by using as a criterion the Euclidean distance with respect to five-dimensional centroids, depicting nine hydrometeor classes. The positions of the centroids in the space formed by four radar moments and one external parameter (phase indicator), are derived through a technique of k-medoids clustering, applied on a selected representative set of radar observations, and coupled with statistical testing which introduces the assumed microphysical properties of the different hydrometeor types. Aside from a hydrometeor type label, each radar sampling volume is characterized by an entropy estimate, indicating the uncertainty of the classification. Here, we revisit the concept of entropy presented in [1], in order to emphasize its presumed potential for the identification of hydrometeor mixtures. The calculation of entropy is based on the estimate of the probability (pi ) that the observation corresponds to the hydrometeor type i (i = 1,ṡṡṡ9) . The probability is derived from the Euclidean distance (di ) of the observation to the centroid characterizing the hydrometeor type i . The parametrization of the d → p transform is conducted in a controlled environment, using synthetic polarimetric radar datasets. It ensures balanced entropy values: low for pure volumes, and high for different possible combinations of mixed hydrometeors. The parametrized entropy is further on applied to real polarimetric C and X band radar datasets, where we demonstrate the potential of linear de-mixing using a simplex formed by a set of pre-defined centroids in the five-dimensional space. As main outcome, the proposed approach allows to provide plausible proportions of the different hydrometeors contained in a given radar sampling volume. [1] Besic, N., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmos. Meas. Tech., 9, 4425-4445, doi:10.5194/amt-9-4425-2016, 2016.

Use of Pattern Classification Algorithms to Interpret Passive and Active Data Streams from a Walking-Speed Robotic Sensor Platform

NASA Astrophysics Data System (ADS)

Dieckman, Eric Allen

In order to perform useful tasks for us, robots must have the ability to notice, recognize, and respond to objects and events in their environment. This requires the acquisition and synthesis of information from a variety of sensors. Here we investigate the performance of a number of sensor modalities in an unstructured outdoor environment, including the Microsoft Kinect, thermal infrared camera, and coffee can radar. Special attention is given to acoustic echolocation measurements of approaching vehicles, where an acoustic parametric array propagates an audible signal to the oncoming target and the Kinect microphone array records the reflected backscattered signal. Although useful information about the target is hidden inside the noisy time domain measurements, the Dynamic Wavelet Fingerprint process (DWFP) is used to create a time-frequency representation of the data. A small-dimensional feature vector is created for each measurement using an intelligent feature selection process for use in statistical pattern classification routines. Using our experimentally measured data from real vehicles at 50 m, this process is able to correctly classify vehicles into one of five classes with 94% accuracy. Fully three-dimensional simulations allow us to study the nonlinear beam propagation and interaction with real-world targets to improve classification results.

Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach

NASA Astrophysics Data System (ADS)

Besic, Nikola; Ventura, Jordi Figueras i.; Grazioli, Jacopo; Gabella, Marco; Germann, Urs; Berne, Alexis

2016-09-01

Polarimetric radar-based hydrometeor classification is the procedure of identifying different types of hydrometeors by exploiting polarimetric radar observations. The main drawback of the existing supervised classification methods, mostly based on fuzzy logic, is a significant dependency on a presumed electromagnetic behaviour of different hydrometeor types. Namely, the results of the classification largely rely upon the quality of scattering simulations. When it comes to the unsupervised approach, it lacks the constraints related to the hydrometeor microphysics. The idea of the proposed method is to compensate for these drawbacks by combining the two approaches in a way that microphysical hypotheses can, to a degree, adjust the content of the classes obtained statistically from the observations. This is done by means of an iterative approach, performed offline, which, in a statistical framework, examines clustered representative polarimetric observations by comparing them to the presumed polarimetric properties of each hydrometeor class. Aside from comparing, a routine alters the content of clusters by encouraging further statistical clustering in case of non-identification. By merging all identified clusters, the multi-dimensional polarimetric signatures of various hydrometeor types are obtained for each of the studied representative datasets, i.e. for each radar system of interest. These are depicted by sets of centroids which are then employed in operational labelling of different hydrometeors. The method has been applied on three C-band datasets, each acquired by different operational radar from the MeteoSwiss Rad4Alp network, as well as on two X-band datasets acquired by two research mobile radars. The results are discussed through a comparative analysis which includes a corresponding supervised and unsupervised approach, emphasising the operational potential of the proposed method.

Effect of radar frequency on the detection of shaped (low RCS) targets

NASA Astrophysics Data System (ADS)

Moraitis, D.; Alland, S.

The use of shaping to reduce the radar cross-section (RCS) of aircraft and missiles can result in the RCS varying significantly with radar operating frequency. This RCS sensitivity to frequency should be considered when selecting radar frequency and should be accounted for when evaluating radar performance. A detection range increase for shaped (low RCS) targets of a factor of two or greater can be realized for lower frequency radar (e.g., UHF-Band or L-Band) when compared to higher frequency radar (C-Band or X-Band). For low flying (sea skimming) targets, the RCS variation with frequency for shaped (low RCS) targets neutralizes the advantage that higher radar frequencies realize in multipath propagation resulting in approximately the same detection range across the radar bands from UHF to X-Band.

Sparse representation based SAR vehicle recognition along with aspect angle.

PubMed

Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang

2014-01-01

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Optimal Non-Invasive Fault Classification Model for Packaged Ceramic Tile Quality Monitoring Using MMW Imaging

NASA Astrophysics Data System (ADS)

Agarwal, Smriti; Singh, Dharmendra

2016-04-01

Millimeter wave (MMW) frequency has emerged as an efficient tool for different stand-off imaging applications. In this paper, we have dealt with a novel MMW imaging application, i.e., non-invasive packaged goods quality estimation for industrial quality monitoring applications. An active MMW imaging radar operating at 60 GHz has been ingeniously designed for concealed fault estimation. Ceramic tiles covered with commonly used packaging cardboard were used as concealed targets for undercover fault classification. A comparison of computer vision-based state-of-the-art feature extraction techniques, viz, discrete Fourier transform (DFT), wavelet transform (WT), principal component analysis (PCA), gray level co-occurrence texture (GLCM), and histogram of oriented gradient (HOG) has been done with respect to their efficient and differentiable feature vector generation capability for undercover target fault classification. An extensive number of experiments were performed with different ceramic tile fault configurations, viz., vertical crack, horizontal crack, random crack, diagonal crack along with the non-faulty tiles. Further, an independent algorithm validation was done demonstrating classification accuracy: 80, 86.67, 73.33, and 93.33 % for DFT, WT, PCA, GLCM, and HOG feature-based artificial neural network (ANN) classifier models, respectively. Classification results show good capability for HOG feature extraction technique towards non-destructive quality inspection with appreciably low false alarm as compared to other techniques. Thereby, a robust and optimal image feature-based neural network classification model has been proposed for non-invasive, automatic fault monitoring for a financially and commercially competent industrial growth.

Validation of the Electromagnetic Code FACETS for Numerical Simulation of Radar Target Images

DTIC Science & Technology

2009-12-01

Validation of the electromagnetic code FACETS for numerical simulation of radar target images S. Wong...Validation of the electromagnetic code FACETS for numerical simulation of radar target images S. Wong DRDC Ottawa...for simulating radar images of a target is obtained, through direct simulation-to-measurement comparisons. A 3-dimensional computer-aided design

Target scattering characteristics for OAM-based radar

NASA Astrophysics Data System (ADS)

Liu, Kang; Gao, Yue; Li, Xiang; Cheng, Yongqiang

2018-02-01

The target scattering characteristics are crucial for radar systems. However, there is very little study conducted for the recently developed orbital angular momentum (OAM) based radar system. To illustrate the role of OAM-based radar cross section (ORCS), conventional radar equation is modified by taking characteristics of the OAM waves into account. Subsequently, the ORCS is defined in analogy to classical radar cross section (RCS). The unique features of the incident OAM-carrying field are analyzed. The scattered field is derived, and the analytical expressions of ORCSs for metal plate and cylinder targets are obtained. Furthermore, the ORCS and RCS are compared to illustrate the influences of OAM mode number, target size and signal frequency on the ORCS. Analytical studies demonstrate that the mirror-reflection phenomenon disappears and peak values of ORCS are in the non-specular direction. Finally, the ORCS features are summarized to show its advantages in radar target detection. This work can provide theoretical guidance to the design of OAM-based radar as well as the target detection and identification applications.

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

Deng, Min; Kollias, Pavlos; Feng, Zhe

The motivation for this research is to develop a precipitation classification and rain rate estimation method using cloud radar-only measurements for Atmospheric Radiation Measurement (ARM) long-term cloud observation analysis, which are crucial and unique for studying cloud lifecycle and precipitation features under different weather and climate regimes. Based on simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two precipitation radars (NCAR S-PolKa and Texas A&M University SMART-R), and surface precipitation during the DYNAMO/AMIE field campaign, a new cloud radar-only based precipitation classification and rain rate estimation method has been developed and evaluated. The resulting precipitation classification ismore » equivalent to those collocated SMART-R and S-PolKa observations. Both cloud and precipitation radars detected about 5% precipitation occurrence during this period. The convective (stratiform) precipitation fraction is about 18% (82%). The 2-day collocated disdrometer observations show an increased number concentration of large raindrops in convective rain compared to dominant concentration of small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also show two distinct structures for convective and stratiform rain. These indicate that the method produces physically consistent results for two types of rain. The cloud radar-only rainfall estimation is developed based on the gradient of accumulative radar reflectivity below 1 km, near-surface Ze, and collocated surface rainfall (R) measurement. The parameterization is compared with the Z-R exponential relation. The relative difference between estimated and surface measured rainfall rate shows that the two-parameter relation can improve rainfall estimation.« less

Radar activities of the DFVLR Institute for Radio Frequency Technology

NASA Technical Reports Server (NTRS)

Keydel, W.

1983-01-01

Aerospace research and the respective applications microwave tasks with respect to remote sensing, position finding and communication are discussed. The radar activities are directed at point targets, area targets and volume targets; they center around signature research for earth and ocean remote sensing, target recognition, reconnaissance and camouflage and imaging and area observation radar techniques (SAR and SLAR). The radar activities cover a frequency range from 1 GHz up to 94 GHz. The radar program is oriented to four possible application levels: ground, air, shuttle orbits and satellite orbits. Ground based studies and measurements, airborne scatterometers and imaging radars, a space shuttle radar, the MRSE, and follow on experiments are considered.

Development and Application of integrated monitoring platform for the Doppler Weather SA-BAND Radar

NASA Astrophysics Data System (ADS)

Zhang, Q.; Sun, J.; Zhao, C. C.; Chen, H. Y.

2017-10-01

The doppler weather SA-band radar is an important part of modern meteorological observation methods, monitoring the running status of radar and the data transmission is important.This paper introduced the composition of radar system and classification of radar data,analysed the characteristics and laws of the radar when is normal or abnormal. Using Macromedia Dreamweaver and PHP, developed the integrated monitoring platform for the doppler weather SA-band radar which could monitor the real-time radar system running status and important performance indicators such as radar power,status parameters and others on Web page,and when the status is abnormal it will trigger the audio alarm.

Continuous high PRF waveforms for challenging environments

NASA Astrophysics Data System (ADS)

Jaroszewski, Steven; Corbeil, Allan; Ryland, Robert; Sobota, David

2017-05-01

Current airborne radar systems segment the available time-on-target during each beam dwell into multiple Coherent Processing Intervals (CPIs) in order to eliminate range eclipsing, solve for unambiguous range, and increase the detection performance against larger Radar Cross Section (RCS) targets. As a consequence, these radars do not realize the full Signal-to-Noise Ratio (SNR) increase and detection performance improvement that is possible. Continuous High Pulse Repetition Frequency (HPRF) waveforms and processing enables the coherent integration of all available radar data over the full time-on-target. This can greatly increase the SNR for air targets at long range and/or with weak radar returns and significantly improve the detection performance against such targets. TSC worked with its partner KeyW to implement a Continuous HPRF waveform in their Sahara radar testbed and obtained measured radar data on both a ground vehicle target and an airborne target of opportunity. This experimental data was processed by TSC to validate the expected benefits of Continuous HPRF waveforms.

An Algorithm Based Wavelet Entropy for Shadowing Effect of Human Detection Using Ultra-Wideband Bio-Radar

PubMed Central

Liu, Miao; Zhang, Yang; Liang, Fulai; Qi, Fugui; Lv, Hao; Wang, Jianqi; Zhang, Yang

2017-01-01

Ultra-wide band (UWB) radar for short-range human target detection is widely used to find and locate survivors in some rescue missions after a disaster. The results of the application of bistatic UWB radar for detecting multi-stationary human targets have shown that human targets close to the radar antennas are very often visible, while those farther from radar antennas are detected with less reliability. In this paper, on account of the significant difference of frequency content between the echo signal of the human target and that of noise in the shadowing region, an algorithm based on wavelet entropy is proposed to detect multiple targets. Our findings indicate that the entropy value of human targets was much lower than that of noise. Compared with the method of adaptive filtering and the energy spectrum, wavelet entropy can accurately detect the person farther from the radar antennas, and it can be employed as a useful tool in detecting multiple targets by bistatic UWB radar. PMID:28973988

An Algorithm Based Wavelet Entropy for Shadowing Effect of Human Detection Using Ultra-Wideband Bio-Radar.

PubMed

Xue, Huijun; Liu, Miao; Zhang, Yang; Liang, Fulai; Qi, Fugui; Chen, Fuming; Lv, Hao; Wang, Jianqi; Zhang, Yang

2017-09-30

Ultra-wide band (UWB) radar for short-range human target detection is widely used to find and locate survivors in some rescue missions after a disaster. The results of the application of bistatic UWB radar for detecting multi-stationary human targets have shown that human targets close to the radar antennas are very often visible, while those farther from radar antennas are detected with less reliability. In this paper, on account of the significant difference of frequency content between the echo signal of the human target and that of noise in the shadowing region, an algorithm based on wavelet entropy is proposed to detect multiple targets. Our findings indicate that the entropy value of human targets was much lower than that of noise. Compared with the method of adaptive filtering and the energy spectrum, wavelet entropy can accurately detect the person farther from the radar antennas, and it can be employed as a useful tool in detecting multiple targets by bistatic UWB radar.

Maximum a posteriori classification of multifrequency, multilook, synthetic aperture radar intensity data

NASA Technical Reports Server (NTRS)

Rignot, E.; Chellappa, R.

1993-01-01

We present a maximum a posteriori (MAP) classifier for classifying multifrequency, multilook, single polarization SAR intensity data into regions or ensembles of pixels of homogeneous and similar radar backscatter characteristics. A model for the prior joint distribution of the multifrequency SAR intensity data is combined with a Markov random field for representing the interactions between region labels to obtain an expression for the posterior distribution of the region labels given the multifrequency SAR observations. The maximization of the posterior distribution yields Bayes's optimum region labeling or classification of the SAR data or its MAP estimate. The performance of the MAP classifier is evaluated by using computer-simulated multilook SAR intensity data as a function of the parameters in the classification process. Multilook SAR intensity data are shown to yield higher classification accuracies than one-look SAR complex amplitude data. The MAP classifier is extended to the case in which the radar backscatter from the remotely sensed surface varies within the SAR image because of incidence angle effects. The results obtained illustrate the practicality of the method for combining SAR intensity observations acquired at two different frequencies and for improving classification accuracy of SAR data.

A preliminary investigation of bird classification by Doppler radar

NASA Technical Reports Server (NTRS)

Martinson, L. W.

1973-01-01

A preliminary study of the application of Doppler radar to the classification of birds is reported. The desirability for improvements in bird classification stems primarily from the hazards they present to jet aircraft in flight and in the vicinity of airports. A secondary need exists in the study of bird migration. The wing body and tail motion of a bird in flight reflect signals which, when analyzed properly present a signature of wing beat pattern which is unique for each bird species. Although the results of this investigation did not validate the feasibility of classifying bird species, they do indicate that a more thorough investigation is warranted. Certain gross characteristics such as wing beat rates, multiple bird patterns, and bird maneuverability, were indicated clearly in the results. Large birds with slow wing beat rates appear to be the most optimum subject for further study with the X-band Doppler radar used in this investigation.

Performance assessment techniques for Doppler radar physiological sensors.

PubMed

Hafner, Noah; Lubecke, Victor

2009-01-01

This paper presents a technique for assessing the performance of continuous wave Doppler radar systems for physiological sensing. The technique includes an artificial target for testing physiological sensing radar systems with motion analogous to human heart movement and software algorithms leveraging the capabilities of this target to simply test radar system performance. The mechanical target provides simple to complex patterns of motion that are stable and repeatable. Details of radar system performance can be assessed and the effects of configuration changes that might not appear with a human target can be observed when using this mechanical target.

Use of Dual Polarization Radar in Validation of Satellite Precipitation Measurements: Rationale and Opportunities

NASA Technical Reports Server (NTRS)

Chandrasekar, V.; Hou, Arthur; Smith, Eric; Bringi, V. N.; Rutledge, S. A.; Gorgucci, E.; Petersen, W. A.; SkofronickJackson, Gail

2008-01-01

Dual-polarization weather radars have evolved significantly in the last three decades culminating in the operational deployment by the National Weather Service. In addition to operational applications in the weather service, dual-polarization radars have shown significant potential in contributing to the research fields of ground based remote sensing of rainfall microphysics, study of precipitation evolution and hydrometeor classification. Furthermore the dual-polarization radars have also raised the awareness of radar system aspects such as calibration. Microphysical characterization of precipitation and quantitative precipitation estimation are important applications that are critical in the validation of satellite borne precipitation measurements and also serves as a valuable tool in algorithm development. This paper presents the important role played by dual-polarization radar in validating space borne precipitation measurements. Starting from a historical evolution, the various configurations of dual-polarization radar are presented. Examples of raindrop size distribution retrievals and hydrometeor type classification are discussed. The quantitative precipitation estimation is a product of direct relevance to space borne observations. During the TRMM program substantial advancement was made with ground based polarization radars specially collecting unique observations in the tropics which are noted. The scientific accomplishments of relevance to space borne measurements of precipitation are summarized. The potential of dual-polarization radars and opportunities in the era of global precipitation measurement mission is also discussed.

Radar target classification method with high accuracy and decision speed performance using MUSIC spectrum vectors and PCA projection

NASA Astrophysics Data System (ADS)

Secmen, Mustafa

2011-10-01

This paper introduces the performance of an electromagnetic target recognition method in resonance scattering region, which includes pseudo spectrum Multiple Signal Classification (MUSIC) algorithm and principal component analysis (PCA) technique. The aim of this method is to classify an "unknown" target as one of the "known" targets in an aspect-independent manner. The suggested method initially collects the late-time portion of noise-free time-scattered signals obtained from different reference aspect angles of known targets. Afterward, these signals are used to obtain MUSIC spectrums in real frequency domain having super-resolution ability and noise resistant feature. In the final step, PCA technique is applied to these spectrums in order to reduce dimensionality and obtain only one feature vector per known target. In the decision stage, noise-free or noisy scattered signal of an unknown (test) target from an unknown aspect angle is initially obtained. Subsequently, MUSIC algorithm is processed for this test signal and resulting test vector is compared with feature vectors of known targets one by one. Finally, the highest correlation gives the type of test target. The method is applied to wire models of airplane targets, and it is shown that it can tolerate considerable noise levels although it has a few different reference aspect angles. Besides, the runtime of the method for a test target is sufficiently low, which makes the method suitable for real-time applications.

Doppler radar fall activity detection using the wavelet transform.

PubMed

Su, Bo Yu; Ho, K C; Rantz, Marilyn J; Skubic, Marjorie

2015-03-01

We propose in this paper the use of Wavelet transform (WT) to detect human falls using a ceiling mounted Doppler range control radar. The radar senses any motions from falls as well as nonfalls due to the Doppler effect. The WT is very effective in distinguishing the falls from other activities, making it a promising technique for radar fall detection in nonobtrusive inhome elder care applications. The proposed radar fall detector consists of two stages. The prescreen stage uses the coefficients of wavelet decomposition at a given scale to identify the time locations in which fall activities may have occurred. The classification stage extracts the time-frequency content from the wavelet coefficients at many scales to form a feature vector for fall versus nonfall classification. The selection of different wavelet functions is examined to achieve better performance. Experimental results using the data from the laboratory and real inhome environments validate the promising and robust performance of the proposed detector.

Capabilities of radar as they might relate to entomological studies

NASA Technical Reports Server (NTRS)

Skolnik, M. I.

1979-01-01

A tutoral background of radar capabilities and its potential for insect research is provided. The basic principles and concepts of radar were reviewed. Information on current radar equipment was examined. Specific issues related to insect research included; target cross-section, radar frequency, tracking target recognition and false alarms, clutter reduction, radar transmitter power, and ascertained atmospheric processes.

Evaluation of space SAR as a land-cover classification

NASA Technical Reports Server (NTRS)

Brisco, B.; Ulaby, F. T.; Williams, T. H. L.

1985-01-01

The multidimensional approach to the mapping of land cover, crops, and forests is reported. Dimensionality is achieved by using data from sensors such as LANDSAT to augment Seasat and Shuttle Image Radar (SIR) data, using different image features such as tone and texture, and acquiring multidate data. Seasat, Shuttle Imaging Radar (SIR-A), and LANDSAT data are used both individually and in combination to map land cover in Oklahoma. The results indicates that radar is the best single sensor (72% accuracy) and produces the best sensor combination (97.5% accuracy) for discriminating among five land cover categories. Multidate Seasat data and a single data of LANDSAT coverage are then used in a crop classification study of western Kansas. The highest accuracy for a single channel is achieved using a Seasat scene, which produces a classification accuracy of 67%. Classification accuracy increases to approximately 75% when either a multidate Seasat combination or LANDSAT data in a multisensor combination is used. The tonal and textural elements of SIR-A data are then used both alone and in combination to classify forests into five categories.

Synthetic aperture radar operator tactical target acquisition research

NASA Technical Reports Server (NTRS)

Hershberger, M. L.; Craig, D. W.

1978-01-01

A radar target acquisition research study was conducted to access the effects of two levels of 13 radar sensor, display, and mission parameters on operator tactical target acquisition. A saturated fractional-factorial screening design was employed to examine these parameters. Data analysis computed ETA squared values for main and second-order effects for the variables tested. Ranking of the research parameters in terms of importance to system design revealed four variables (radar coverage, radar resolution/multiple looks, display resolution, and display size) accounted for 50 percent of the target acquisition probability variance.

A novel neural network based image reconstruction model with scale and rotation invariance for target identification and classification for Active millimetre wave imaging

NASA Astrophysics Data System (ADS)

Agarwal, Smriti; Bisht, Amit Singh; Singh, Dharmendra; Pathak, Nagendra Prasad

2014-12-01

Millimetre wave imaging (MMW) is gaining tremendous interest among researchers, which has potential applications for security check, standoff personal screening, automotive collision-avoidance, and lot more. Current state-of-art imaging techniques viz. microwave and X-ray imaging suffers from lower resolution and harmful ionizing radiation, respectively. In contrast, MMW imaging operates at lower power and is non-ionizing, hence, medically safe. Despite these favourable attributes, MMW imaging encounters various challenges as; still it is very less explored area and lacks suitable imaging methodology for extracting complete target information. Keeping in view of these challenges, a MMW active imaging radar system at 60 GHz was designed for standoff imaging application. A C-scan (horizontal and vertical scanning) methodology was developed that provides cross-range resolution of 8.59 mm. The paper further details a suitable target identification and classification methodology. For identification of regular shape targets: mean-standard deviation based segmentation technique was formulated and further validated using a different target shape. For classification: probability density function based target material discrimination methodology was proposed and further validated on different dataset. Lastly, a novel artificial neural network based scale and rotation invariant, image reconstruction methodology has been proposed to counter the distortions in the image caused due to noise, rotation or scale variations. The designed neural network once trained with sample images, automatically takes care of these deformations and successfully reconstructs the corrected image for the test targets. Techniques developed in this paper are tested and validated using four different regular shapes viz. rectangle, square, triangle and circle.

Comparison of classification algorithms for various methods of preprocessing radar images of the MSTAR base

NASA Astrophysics Data System (ADS)

Borodinov, A. A.; Myasnikov, V. V.

2018-04-01

The present work is devoted to comparing the accuracy of the known qualification algorithms in the task of recognizing local objects on radar images for various image preprocessing methods. Preprocessing involves speckle noise filtering and normalization of the object orientation in the image by the method of image moments and by a method based on the Hough transform. In comparison, the following classification algorithms are used: Decision tree; Support vector machine, AdaBoost, Random forest. The principal component analysis is used to reduce the dimension. The research is carried out on the objects from the base of radar images MSTAR. The paper presents the results of the conducted studies.

Tangential velocity measurement using interferometric MTI radar

DOEpatents

Doerry, Armin W.; Mileshosky, Brian P.; Bickel, Douglas L.

2006-01-03

Radar systems use time delay measurements between a transmitted signal and its echo to calculate range to a target. Ranges that change with time cause a Doppler offset in phase and frequency of the echo. Consequently, the closing velocity between target and radar can be measured by measuring the Doppler offset of the echo. The closing velocity is also known as radial velocity, or line-of-sight velocity. Doppler frequency is measured in a pulse-Doppler radar as a linear phase shift over a set of radar pulses during some Coherent Processing Interval (CPI). An Interferometric Moving Target Indicator (MTI) radar can be used to measure the tangential velocity component of a moving target. Multiple baselines, along with the conventional radial velocity measurement, allow estimating the true 3-D velocity of a target.

Design of integrated ship monitoring system using SAR, RADAR, and AIS

NASA Astrophysics Data System (ADS)

Yang, Chan-Su; Kim, Tae-Ho; Hong, Danbee; Ahn, Hyung-Wook

2013-06-01

When we talk about for the ship detection, identification and its classification, we need to go for the wide area of monitoring and it may be possible only through satellite based monitoring approach which monitors and covers coastal as well as the oceanic zone. Synthetic aperture radar (SAR) has been widely used to detect targets of interest with the advantage of the operating capability in all weather and luminance free condition (Margarit and Tabasco, 2011). In EU waters, EMSA(European Maritime Safety Agency) is operating the SafeSeaNet and CleanSeaNet systems which provide the current positions of all ships and oil spill monitoring information in and around EU waters in a single picture to Member States using AIS, LRIT and SAR images. In many countries, a similar system has been developed and the key of the matter is to integrate all available data. This abstract describes the preliminary design concept for an integration system of RADAR, AIS and SAR data for vessel traffic monitoring. SAR sensors are used to acquire image data over large coverage area either through the space borne or airborne platforms in UTC. AIS reports should be also obtained on the same date as of the SAR acquisition for the purpose to perform integration test. Land-based RADAR can provide ships positions detected and tracked in near real time. In general, SAR are used to acquire image data over large coverage area, AIS reports are obtained from ship based transmitter, and RADAR can monitor continuously ships for a limited area. In this study, we developed individual ship monitoring algorithms using RADAR(FMCW and Pulse X-band), AIS and SAR(RADARSAT-2 Full-pol Mode). We conducted field experiments two times for displaying the RADAR, AIS and SAR integration over the Pyeongtaek Port, South Korea.

German Radar Observation Shuttle Experiment (ROSE)

NASA Technical Reports Server (NTRS)

Sleber, A. J.; Hartl, P.; Haydn, R.; Hildebrandt, G.; Konecny, G.; Muehlfeld, R.

1984-01-01

The success of radar sensors in several different application areas of interest depends on the knowledge of the backscatter of radar waves from the targets of interest, the variance of these interaction mechanisms with respect to changing measurement parameters, and the determination of the influence of he measuring systems on the results. The incidence-angle dependency of the radar cross section of different natural targets is derived. Problems involved by the combination of data gained with different sensors, e.g., MSS-, TM-, SPOTand SAR-images are analyzed. Radar cross-section values gained with ground-based radar spectrometers and spaceborne radar imaging, and non-imaging scatterometers and spaceborne radar images from the same areal target are correlated. The penetration of L-band radar waves into vegetated and nonvegetated surfaces is analyzed.

Investigation of hydrometeor classification uncertainties through the POLARRIS polarimetric radar simulator

NASA Astrophysics Data System (ADS)

Dolan, B.; Rutledge, S. A.; Barnum, J. I.; Matsui, T.; Tao, W. K.; Iguchi, T.

2017-12-01

POLarimetric Radar Retrieval and Instrument Simulator (POLARRIS) is a framework that has been developed to simulate radar observations from cloud resolving model (CRM) output and subject model data and observations to the same retrievals, analysis and visualization. This framework not only enables validation of bulk microphysical model simulated properties, but also offers an opportunity to study the uncertainties associated with retrievals such as hydrometeor classification (HID). For the CSU HID, membership beta functions (MBFs) are built using a set of simulations with realistic microphysical assumptions about axis ratio, density, canting angles, size distributions for each of ten hydrometeor species. These assumptions are tested using POLARRIS to understand their influence on the resulting simulated polarimetric data and final HID classification. Several of these parameters (density, size distributions) are set by the model microphysics, and therefore the specific assumptions of axis ratio and canting angle are carefully studied. Through these sensitivity studies, we hope to be able to provide uncertainties in retrieved polarimetric variables and HID as applied to CRM output. HID retrievals assign a classification to each point by determining the highest score, thereby identifying the dominant hydrometeor type within a volume. However, in nature, there is rarely just one a single hydrometeor type at a particular point. Models allow for mixing ratios of different hydrometeors within a grid point. We use the mixing ratios from CRM output in concert with the HID scores and classifications to understand how the HID algorithm can provide information about mixtures within a volume, as well as calculate a confidence in the classifications. We leverage the POLARRIS framework to additionally probe radar wavelength differences toward the possibility of a multi-wavelength HID which could utilize the strengths of different wavelengths to improve HID classifications. With these uncertainties and algorithm improvements, cases of convection are studied in a continental (Oklahoma) and maritime (Darwin, Australia) regime. Observations from C-band polarimetric data in both locations are compared to CRM simulations from NU-WRF using the POLARRIS framework.

Classification of surface types using SIR-C/X-SAR, Mount Everest Area, Tibet

USGS Publications Warehouse

Albright, Thomas P.; Painter, Thomas H.; Roberts, Dar A.; Shi, Jiancheng; Dozier, Jeff; Fielding, Eric

1998-01-01

Imaging radar is a promising tool for mapping snow and ice cover in alpine regions. It combines a high-resolution, day or night, all-weather imaging capability with sensitivity to hydrologic and climatic snow and ice parameters. We use the spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR) to map snow and glacial ice on the rugged north slope of Mount Everest. From interferometrically derived digital elevation data, we compute the terrain calibration factor and cosine of the local illumination angle. We then process and terrain-correct radar data sets acquired on April 16, 1994. In addition to the spectral data, we include surface slope to improve discrimination among several surface types. These data sets are then used in a decision tree to generate an image classification. This method is successful in identifying and mapping scree/talus, dry snow, dry snow-covered glacier, wet snow-covered glacier, and rock-covered glacier, as corroborated by comparison with existing surface cover maps and other ancillary information. Application of the classification scheme to data acquired on October 7 of the same year yields accurate results for most surface types but underreports the extent of dry snow cover.

Remote sensing of Earth terrain

NASA Technical Reports Server (NTRS)

Kong, Jin AU; Shin, Robert T.; Nghiem, Son V.; Yueh, Herng-Aung; Han, Hsiu C.; Lim, Harold H.; Arnold, David V.

1990-01-01

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

Enhancing Europa surface characterization with ice penetrating radar: A Comparative study in Antarctica

NASA Astrophysics Data System (ADS)

Curra, C.; Arnold, E.; Karwoski, B.; Grima, C.; Schroeder, D. M.; Young, D. A.; Blankenship, D. D.

2013-12-01

The shape and composition of the surface of Europa result from multiple processes, most of them involving direct and indirect interactions between the liquid and solid phases of its outer water layer. The surface ice composition is likely to reflect the material exchanged with the sub-glacial ocean and potentially holds signatures of organic compounds that could demonstrate the ability of the icy moon to sustain life. Therefore, the most likely targets for in-situ landing missions are primarily located in complex terrains disrupted by exchange mechanisms with the ocean/lenses of sub-glacial liquid water. Any landing site selection process to ensure a safe delivery of a future lander, will then have to confidently characterize its surface roughness. We evaluate the capability of an ice-penetrating radar to characterize the roughness using a statistical method applied to the surface echoes. Our approach is to compare radar-derived data with nadir-imagery and laser altimetry simultaneously acquired on an airborne platform over Marie Byrd Land, West Antarctica, during the 2012-13 GIMBLE survey. The radar is the High-Capability Radar Sounder 2 (HiCARS 2, 60 MHz) system operated by the University of Texas Institute for Geophysics (UTIG), with specifications similar to the Ice Penetrating Radar (IPR) of the Europa Clipper project. Surface textures as seen by simultaneously collected nadir imagery are manually classified, allowing individual contrast stretching for better identification. We identified crevasse fields, blue ice patches, and families of wind-blown patterns. Homogeneity/heterogeneity of the textures has also been an important classification criterion. The various textures are geolocated and compared to the evolution and amplitude of laser-derived and radar-derived roughness. Similarities and discrepancies between these three datasets are illustrated and analyzed to qualitatively constrain radar sensitivity to the surface textures. The result allows for a first insight and discussion into how to interpret statistically-inverted radar data from an icy planetary surface.

Target-adaptive polarimetric synthetic aperture radar target discrimination using maximum average correlation height filters.

PubMed

Sadjadi, Firooz A; Mahalanobis, Abhijit

2006-05-01

We report the development of a technique for adaptive selection of polarization ellipse tilt and ellipticity angles such that the target separation from clutter is maximized. From the radar scattering matrix [S] and its complex components, in phase and quadrature phase, the elements of the Mueller matrix are obtained. Then, by means of polarization synthesis, the radar cross section of the radar scatters are obtained at different transmitting and receiving polarization states. By designing a maximum average correlation height filter, we derive a target versus clutter distance measure as a function of four transmit and receive polarization state angles. The results of applying this method on real synthetic aperture radar imagery indicate a set of four transmit and receive angles that lead to maximum target versus clutter discrimination. These optimum angles are different for different targets. Hence, by adaptive control of the state of polarization of polarimetric radar, one can noticeably improve the discrimination of targets from clutter.

Through-the-Wall Localization of a Moving Target by Two Independent Ultra Wideband (UWB) Radar Systems

PubMed Central

Kocur, Dušan; Švecová, Mária; Rovňáková, Jana

2013-01-01

In the case of through-the-wall localization of moving targets by ultra wideband (UWB) radars, there are applications in which handheld sensors equipped only with one transmitting and two receiving antennas are applied. Sometimes, the radar using such a small antenna array is not able to localize the target with the required accuracy. With a view to improve through-the-wall target localization, cooperative positioning based on a fusion of data retrieved from two independent radar systems can be used. In this paper, the novel method of the cooperative localization referred to as joining intersections of the ellipses is introduced. This method is based on a geometrical interpretation of target localization where the target position is estimated using a properly created cluster of the ellipse intersections representing potential positions of the target. The performance of the proposed method is compared with the direct calculation method and two alternative methods of cooperative localization using data obtained by measurements with the M-sequence UWB radars. The direct calculation method is applied for the target localization by particular radar systems. As alternative methods of cooperative localization, the arithmetic average of the target coordinates estimated by two single independent UWB radars and the Taylor series method is considered. PMID:24021968

Through-the-wall localization of a moving target by two independent ultra wideband (UWB) radar systems.

PubMed

Kocur, Dušan; Svecová, Mária; Rovňáková, Jana

2013-09-09

In the case of through-the-wall localization of moving targets by ultra wideband (UWB) radars, there are applications in which handheld sensors equipped only with one transmitting and two receiving antennas are applied. Sometimes, the radar using such a small antenna array is not able to localize the target with the required accuracy. With a view to improve through-the-wall target localization, cooperative positioning based on a fusion of data retrieved from two independent radar systems can be used. In this paper, the novel method of the cooperative localization referred to as joining intersections of the ellipses is introduced. This method is based on a geometrical interpretation of target localization where the target position is estimated using a properly created cluster of the ellipse intersections representing potential positions of the target. The performance of the proposed method is compared with the direct calculation method and two alternative methods of cooperative localization using data obtained by measurements with the M-sequence UWB radars. The direct calculation method is applied for the target localization by particular radar systems. As alternative methods of cooperative localization, the arithmetic average of the target coordinates estimated by two single independent UWB radars and the Taylor series method is considered.

Advanced Unsupervised Classification Methods to Detect Anomalies on Earthen Levees Using Polarimetric SAR Imagery

PubMed Central

Marapareddy, Ramakalavathi; Aanstoos, James V.; Younan, Nicolas H.

2016-01-01

Fully polarimetric Synthetic Aperture Radar (polSAR) data analysis has wide applications for terrain and ground cover classification. The dynamics of surface and subsurface water events can lead to slope instability resulting in slough slides on earthen levees. Early detection of these anomalies by a remote sensing approach could save time versus direct assessment. We used L-band Synthetic Aperture Radar (SAR) to screen levees for anomalies. SAR technology, due to its high spatial resolution and soil penetration capability, is a good choice for identifying problematic areas on earthen levees. Using the parameters entropy (H), anisotropy (A), alpha (α), and eigenvalues (λ, λ1, λ2, and λ3), we implemented several unsupervised classification algorithms for the identification of anomalies on the levee. The classification techniques applied are H/α, H/A, A/α, Wishart H/α, Wishart H/A/α, and H/α/λ classification algorithms. In this work, the effectiveness of the algorithms was demonstrated using quad-polarimetric L-band SAR imagery from the NASA Jet Propulsion Laboratory’s (JPL’s) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). The study area is a section of the lower Mississippi River valley in the Southern USA, where earthen flood control levees are maintained by the US Army Corps of Engineers. PMID:27322270

On the application of neural networks to the classification of phase modulated waveforms

NASA Astrophysics Data System (ADS)

Buchenroth, Anthony; Yim, Joong Gon; Nowak, Michael; Chakravarthy, Vasu

2017-04-01

Accurate classification of phase modulated radar waveforms is a well-known problem in spectrum sensing. Identification of such waveforms aids situational awareness enabling radar and communications spectrum sharing. While various feature extraction and engineering approaches have sought to address this problem, the use of a machine learning algorithm that best utilizes these features is becomes foremost. In this effort, a comparison of a standard shallow and a deep learning approach are explored. Experiments provide insights into classifier architecture, training procedure, and performance.

Cramer-Rao Lower Bound Evaluation for Linear Frequency Modulation Based Active Radar Networks Operating in a Rice Fading Environment.

PubMed

Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

2016-12-06

This paper investigates the joint target parameter (delay and Doppler) estimation performance of linear frequency modulation (LFM)-based radar networks in a Rice fading environment. The active radar networks are composed of multiple radar transmitters and multichannel receivers placed on moving platforms. First, the log-likelihood function of the received signal for a Rician target is derived, where the received signal scattered off the target comprises of dominant scatterer (DS) component and weak isotropic scatterers (WIS) components. Then, the analytically closed-form expressions of the Cramer-Rao lower bounds (CRLBs) on the Cartesian coordinates of target position and velocity are calculated, which can be adopted as a performance metric to access the target parameter estimation accuracy for LFM-based radar network systems in a Rice fading environment. It is found that the cumulative Fisher information matrix (FIM) is a linear combination of both DS component and WIS components, and it also demonstrates that the joint CRLB is a function of signal-to-noise ratio (SNR), target's radar cross section (RCS) and transmitted waveform parameters, as well as the relative geometry between the target and the radar network architectures. Finally, numerical results are provided to indicate that the joint target parameter estimation performance of active radar networks can be significantly improved with the exploitation of DS component.

Micro-Doppler classification of riders and riderless horses

NASA Astrophysics Data System (ADS)

Tahmoush, David

2014-05-01

Micro-range Micro-Doppler can be used to isolate particular parts of the radar signature, and in this case we demonstrate the differences in the signature between a walking horse versus a walking horse with a rider. Using micro-range micro-Doppler, we can distinguish the radar returns from the rider as separate from the radar returns of the horse.

The Research on Tunnel Surrounding Rock Classification Based on Geological Radar and Probability Theory

NASA Astrophysics Data System (ADS)

Xiao Yong, Zhao; Xin, Ji Yong; Shuang Ying, Zuo

2018-03-01

In order to effectively classify the surrounding rock types of tunnels, a multi-factor tunnel surrounding rock classification method based on GPR and probability theory is proposed. Geological radar was used to identify the geology of the surrounding rock in front of the face and to evaluate the quality of the rock face. According to the previous survey data, the rock uniaxial compressive strength, integrity index, fissure and groundwater were selected for classification. The related theories combine them into a multi-factor classification method, and divide the surrounding rocks according to the great probability. Using this method to classify the surrounding rock of the Ma’anshan tunnel, the surrounding rock types obtained are basically the same as those of the actual surrounding rock, which proves that this method is a simple, efficient and practical rock classification method, which can be used for tunnel construction.

Airborne ladar man-in-the-loop operations in tactical environments

NASA Astrophysics Data System (ADS)

Grobmyer, Joseph E., Jr.; Lum, Tommy; Morris, Robert E.; Hard, Sarah J.; Pratt, H. L.; Florence, Tom; Peddycoart, Ed

2004-09-01

The U.S. Army Research, Development and Engineering Command (RDECOM) is developing approaches and processes that will exploit the characteristics of current and future Laser Radar (LADAR) sensor systems for critical man-in-the-loop tactical processes. The importance of timely and accurate target detection, classification, identification, and engagement for future combat systems has been documented and is viewed as a critical enabling factor for FCS survivability and lethality. Recent work has demonstrated the feasibility of using low cost but relatively capable personal computer class systems to exploit the information available in Ladar sensor frames to present the war fighter or analyst with compelling and usable imagery for use in the target identification and engagement processes in near real time. The advantages of LADAR imagery are significant in environments presenting cover for targets and the associated difficulty for automated target recognition (ATR) technologies.

Millimeter wave radars raise weapon IQ

NASA Astrophysics Data System (ADS)

Lerner, E. J.

1985-02-01

The problems encountered by laser and IR homing devices for guided munitions may be tractable with warhead-mounted mm-wave radars. Operating at about 100 GHz and having several kilometers range, mm-wave radars see through darkness, fog, rain and smoke. The radar must be coupled with an analyzer that discerns moving and stationary targets and higher priority targets. The target lock-on can include shut-off of the transmitter and reception of naturally-generated mm-waves bouncing off the target when in the terminal phase of the flight. Monopulse transmitters have simplified the radar design, although mass production of finline small radar units has yet to be accomplished, particularly in combining GaAs, ferrites and other materials on one monolithic chip.

Unsupervised Classification of PolSAR Data Using a Scattering Similarity Measure Derived From a Geodesic Distance

NASA Astrophysics Data System (ADS)

Ratha, Debanshu; Bhattacharya, Avik; Frery, Alejandro C.

2018-01-01

In this letter, we propose a novel technique for obtaining scattering components from Polarimetric Synthetic Aperture Radar (PolSAR) data using the geodesic distance on the unit sphere. This geodesic distance is obtained between an elementary target and the observed Kennaugh matrix, and it is further utilized to compute a similarity measure between scattering mechanisms. The normalized similarity measure for each elementary target is then modulated with the total scattering power (Span). This measure is used to categorize pixels into three categories i.e. odd-bounce, double-bounce and volume, depending on which of the above scattering mechanisms dominate. Then the maximum likelihood classifier of [J.-S. Lee, M. R. Grunes, E. Pottier, and L. Ferro-Famil, Unsupervised terrain classification preserving polarimetric scattering characteristics, IEEE Trans. Geos. Rem. Sens., vol. 42, no. 4, pp. 722731, April 2004.] based on the complex Wishart distribution is iteratively used for each category. Dominant scattering mechanisms are thus preserved in this classification scheme. We show results for L-band AIRSAR and ALOS-2 datasets acquired over San Francisco and Mumbai, respectively. The scattering mechanisms are better preserved using the proposed methodology than the unsupervised classification results using the Freeman-Durden scattering powers on an orientation angle (OA) corrected PolSAR image. Furthermore, (1) the scattering similarity is a completely non-negative quantity unlike the negative powers that might occur in double- bounce and odd-bounce scattering component under Freeman Durden decomposition (FDD), and (2) the methodology can be extended to more canonical targets as well as for bistatic scattering.

Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter.

PubMed

Bolisetti, Siva Karteek; Patwary, Mohammad; Ahmed, Khawza; Soliman, Abdel-Hamid; Abdel-Maguid, Mohamed

2015-01-01

The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper.

On the Compressive Sensing Systems (Part 1)

DTIC Science & Technology

2015-02-01

resolution between targets of classical radar is limited by the radar uncertainty principle. B. Fundamentals on CS and CS-Based Radar ( CSR ) Under...appropriate conditions, CSR can beat the traditional radar. We now consider K targets with unknown range-velocities and corresponding reflection...sparse target scene. A CSR has the following features: 1) Eliminating the need of matched filter at the receiver; 2) Requiring low sampling bandwidth

Sensor fusion approaches for EMI and GPR-based subsurface threat identification

NASA Astrophysics Data System (ADS)

Torrione, Peter; Morton, Kenneth, Jr.; Besaw, Lance E.

2011-06-01

Despite advances in both electromagnetic induction (EMI) and ground penetrating radar (GPR) sensing and related signal processing, neither sensor alone provides a perfect tool for detecting the myriad of possible buried objects that threaten the lives of Soldiers and civilians. However, while neither GPR nor EMI sensing alone can provide optimal detection across all target types, the two approaches are highly complementary. As a result, many landmine systems seek to make use of both sensing modalities simultaneously and fuse the results from both sensors to improve detection performance for targets with widely varying metal content and GPR responses. Despite this, little work has focused on large-scale comparisons of different approaches to sensor fusion and machine learning for combining data from these highly orthogonal phenomenologies. In this work we explore a wide array of pattern recognition techniques for algorithm development and sensor fusion. Results with the ARA Nemesis landmine detection system suggest that nonlinear and non-parametric classification algorithms provide significant performance benefits for single-sensor algorithm development, and that fusion of multiple algorithms can be performed satisfactorily using basic parametric approaches, such as logistic discriminant classification, for the targets under consideration in our data sets.

Evaluation of Hydrometeor Classification for Winter Mixed-Phase Precipitation Events

NASA Astrophysics Data System (ADS)

Hickman, B.; Troemel, S.; Ryzhkov, A.; Simmer, C.

2016-12-01

Hydrometeor classification algorithms (HCL) typically discriminate radar echoes into several classes including rain (light, medium, heavy), hail, dry snow, wet snow, ice crystals, graupel and rain-hail mixtures. Despite the strength of HCL for precipitation dominated by a single phase - especially warm-season classification - shortcomings exist for mixed-phase precipitation classification. Properly identifying mixed-phase can lead to more accurate precipitation estimates, and better forecasts for aviation weather and ground warnings. Cold season precipitation classification is also highly important due to their potentially high impact on society (e.g. black ice, ice accumulation, snow loads), but due to the varying nature of the hydrometeor - density, dielectric constant, shape - reliable classification via radar alone is not capable. With the addition of thermodynamic information of the atmosphere, either from weather models or sounding data, it has been possible to extend more and more into winter time precipitation events. Yet, inaccuracies still exist in separating more benign (ice pellets) from more the more hazardous (freezing rain) events. We have investigated winter mixed-phase precipitation cases which include freezing rain, ice pellets, and rain-snow transitions from several events in Germany in order to move towards a reliable nowcasting of winter precipitation in hopes to provide faster, more accurate winter time warnings. All events have been confirmed to have the specified precipitation from ground reports. Classification of the events is achieved via a combination of inputs from a bulk microphysics numerical weather prediction model and the German dual-polarimetric C-band radar network, into a 1D spectral bin microphysical model (SBC) which explicitly treats the processes of melting, refreezing, and ice nucleation to predict four near-surface precipitation types: rain, snow, freezing rain, ice pellets, rain/snow mixture, and freezing rain/pellet mixture. Evaluation of the classification is performed by means of disdrometer data, in-situ ground observations, and eye-witness reports from the European Severe Weather Database (ESWD). Additionally, a comparison to an existing radar based HCL is performed as a sanity check and a performance evaluator.

Computing the apparent centroid of radar targets

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

Lee, C.E.

1996-12-31

A high-frequency multibounce radar scattering code was used as a simulation platform for demonstrating an algorithm to compute the ARC of specific radar targets. To illustrate this simulation process, several targets models were used. Simulation results for a sphere model were used to determine the errors of approximation associated with the simulation; verifying the process. The severity of glint induced tracking errors was also illustrated using a model of an F-15 aircraft. It was shown, in a deterministic manner, that the ARC of a target can fall well outside its physical extent. Finally, the apparent radar centroid simulation based onmore » a ray casting procedure is well suited for use on most massively parallel computing platforms and could lead to the development of a near real-time radar tracking simulation for applications such as endgame fuzing, survivability, and vulnerability analyses using specific radar targets and fuze algorithms.« less

Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks.

PubMed

Park, Jinhee; Javier, Rios Jesus; Moon, Taesup; Kim, Youngwook

2016-11-24

Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN) directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost.

Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest citations from the Aerospace Database)

NASA Technical Reports Server (NTRS)

1998-01-01

The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

Bistatic and Multistatic Radar: Surveillance, Countermeasures, and Radar Cross Sections. (Latest Citations from the Aerospace Database)

NASA Technical Reports Server (NTRS)

1997-01-01

The bibliography contains citations concerning the design, development, testing, and evaluation of bistatic and multistatic radar used in surveillance and countermeasure technology. Citations discuss radar cross sections, target recognition and characteristics, ghost recognition, motion image compensation, and wavelet analysis. Stealth aircraft design, stealth target tracking, synthetic aperture radar, and space applications are examined.

Cramer-Rao Lower Bound Evaluation for Linear Frequency Modulation Based Active Radar Networks Operating in a Rice Fading Environment

PubMed Central

Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

2016-01-01

This paper investigates the joint target parameter (delay and Doppler) estimation performance of linear frequency modulation (LFM)-based radar networks in a Rice fading environment. The active radar networks are composed of multiple radar transmitters and multichannel receivers placed on moving platforms. First, the log-likelihood function of the received signal for a Rician target is derived, where the received signal scattered off the target comprises of dominant scatterer (DS) component and weak isotropic scatterers (WIS) components. Then, the analytically closed-form expressions of the Cramer-Rao lower bounds (CRLBs) on the Cartesian coordinates of target position and velocity are calculated, which can be adopted as a performance metric to access the target parameter estimation accuracy for LFM-based radar network systems in a Rice fading environment. It is found that the cumulative Fisher information matrix (FIM) is a linear combination of both DS component and WIS components, and it also demonstrates that the joint CRLB is a function of signal-to-noise ratio (SNR), target’s radar cross section (RCS) and transmitted waveform parameters, as well as the relative geometry between the target and the radar network architectures. Finally, numerical results are provided to indicate that the joint target parameter estimation performance of active radar networks can be significantly improved with the exploitation of DS component. PMID:27929433

Numeric Computation of the Radar Cross Section of In-flight Projectiles

DTIC Science & Technology

2016-11-01

SUBJECT TERMS computational electromagnetics , radar signature, ballistic trajectory, radar cross section, RCS 16. SECURITY CLASSIFICATION OF: 17...under the generic category of rockets, artillery, and mortar (RAM). The electromagnetic (EM) modeling team at the US Army Research Laboratory (ARL) is...ARL-TR-5145. 5. Balanis C. Advanced engineering electromagnetics . New York (NY): Wiley; 1989. 6. Ruck G, Barrick DE, Stuart WD, Krichbaum CK

Tracking moving radar targets with parallel, velocity-tuned filters

DOEpatents

Bickel, Douglas L.; Harmony, David W.; Bielek, Timothy P.; Hollowell, Jeff A.; Murray, Margaret S.; Martinez, Ana

2013-04-30

Radar data associated with radar illumination of a movable target is processed to monitor motion of the target. A plurality of filter operations are performed in parallel on the radar data so that each filter operation produces target image information. The filter operations are defined to have respectively corresponding velocity ranges that differ from one another. The target image information produced by one of the filter operations represents the target more accurately than the target image information produced by the remainder of the filter operations when a current velocity of the target is within the velocity range associated with the one filter operation. In response to the current velocity of the target being within the velocity range associated with the one filter operation, motion of the target is tracked based on the target image information produced by the one filter operation.

Mapping forested wetlands in the Great Zhan River Basin through integrating optical, radar, and topographical data classification techniques.

PubMed

Na, X D; Zang, S Y; Wu, C S; Li, W L

2015-11-01

Knowledge of the spatial extent of forested wetlands is essential to many studies including wetland functioning assessment, greenhouse gas flux estimation, and wildlife suitable habitat identification. For discriminating forested wetlands from their adjacent land cover types, researchers have resorted to image analysis techniques applied to numerous remotely sensed data. While with some success, there is still no consensus on the optimal approaches for mapping forested wetlands. To address this problem, we examined two machine learning approaches, random forest (RF) and K-nearest neighbor (KNN) algorithms, and applied these two approaches to the framework of pixel-based and object-based classifications. The RF and KNN algorithms were constructed using predictors derived from Landsat 8 imagery, Radarsat-2 advanced synthetic aperture radar (SAR), and topographical indices. The results show that the objected-based classifications performed better than per-pixel classifications using the same algorithm (RF) in terms of overall accuracy and the difference of their kappa coefficients are statistically significant (p<0.01). There were noticeably omissions for forested and herbaceous wetlands based on the per-pixel classifications using the RF algorithm. As for the object-based image analysis, there were also statistically significant differences (p<0.01) of Kappa coefficient between results performed based on RF and KNN algorithms. The object-based classification using RF provided a more visually adequate distribution of interested land cover types, while the object classifications based on the KNN algorithm showed noticeably commissions for forested wetlands and omissions for agriculture land. This research proves that the object-based classification with RF using optical, radar, and topographical data improved the mapping accuracy of land covers and provided a feasible approach to discriminate the forested wetlands from the other land cover types in forestry area.

Cognitive Nonlinear Radar

DTIC Science & Technology

2013-01-01

intelligently selecting waveform parameters using adaptive algorithms. The adaptive algorithms optimize the waveform parameters based on (1) the EM...the environment. 15. SUBJECT TERMS cognitive radar, adaptive sensing, spectrum sensing, multi-objective optimization, genetic algorithms, machine...detection and classification block diagram. .........................................................6 Figure 5. Genetic algorithm block diagram

Statistics-based optimization of the polarimetric radar hydrometeor classification algorithm and its application for a squall line in South China

NASA Astrophysics Data System (ADS)

Wu, Chong; Liu, Liping; Wei, Ming; Xi, Baozhu; Yu, Minghui

2018-03-01

A modified hydrometeor classification algorithm (HCA) is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results—especially in the mixed rain-hail region—can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar-detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.

Development of dual sensor hand-held detector

NASA Astrophysics Data System (ADS)

Sezgin, Mehmet

2010-04-01

In this paper hand-held dual sensor detector development requirements are considered dedicated to buried object detection. Design characteristics of such a system are categorized and listed. Hardware and software structures, ergonomics, user interface, environmental and EMC/EMI tests to be applied and performance test issues are studied. Main properties of the developed system (SEZER) are presented, which contains Metal Detector (MD) and Ground Penetrating Radar (GPR). The realized system has ergonomic structure and can detect both metallic and non-metallic buried objects. Moreover classification of target is possible if it was defined to the signal processing software in learning phase.

Hailstone classifier based on Rough Set Theory

NASA Astrophysics Data System (ADS)

Wan, Huisong; Jiang, Shuming; Wei, Zhiqiang; Li, Jian; Li, Fengjiao

2017-09-01

The Rough Set Theory was used for the construction of the hailstone classifier. Firstly, the database of the radar image feature was constructed. It included transforming the base data reflected by the Doppler radar into the bitmap format which can be seen. Then through the image processing, the color, texture, shape and other dimensional features should be extracted and saved as the characteristic database to provide data support for the follow-up work. Secondly, Through the Rough Set Theory, a machine for hailstone classifications can be built to achieve the hailstone samples’ auto-classification.

Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis

PubMed Central

Ritchie, Matthew; Ash, Matthew; Chen, Qingchao; Chetty, Kevin

2016-01-01

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques. PMID:27589760

Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis.

PubMed

Ritchie, Matthew; Ash, Matthew; Chen, Qingchao; Chetty, Kevin

2016-08-31

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

Sensor management in RADAR/IRST track fusion

NASA Astrophysics Data System (ADS)

Hu, Shi-qiang; Jing, Zhong-liang

2004-07-01

In this paper, a novel radar management strategy technique suitable for RADAR/IRST track fusion, which is based on Fisher Information Matrix (FIM) and fuzzy stochastic decision approach, is put forward. Firstly, optimal radar measurements' scheduling is obtained by the method of maximizing determinant of the Fisher information matrix of radar and IRST measurements, which is managed by the expert system. Then, suggested a "pseudo sensor" to predict the possible target position using the polynomial method based on the radar and IRST measurements, using "pseudo sensor" model to estimate the target position even if the radar is turned off. At last, based on the tracking performance and the state of target maneuver, fuzzy stochastic decision is used to adjust the optimal radar scheduling and retrieve the module parameter of "pseudo sensor". The experiment result indicates that the algorithm can not only limit Radar activity effectively but also keep the tracking accuracy of active/passive system well. And this algorithm eliminates the drawback of traditional Radar management methods that the Radar activity is fixed and not easy to control and protect.

High-resolution three-dimensional imaging radar

NASA Technical Reports Server (NTRS)

Cooper, Ken B. (Inventor); Chattopadhyay, Goutam (Inventor); Siegel, Peter H. (Inventor); Dengler, Robert J. (Inventor); Schlecht, Erich T. (Inventor); Mehdi, Imran (Inventor); Skalare, Anders J. (Inventor)

2010-01-01

A three-dimensional imaging radar operating at high frequency e.g., 670 GHz, is disclosed. The active target illumination inherent in radar solves the problem of low signal power and narrow-band detection by using submillimeter heterodyne mixer receivers. A submillimeter imaging radar may use low phase-noise synthesizers and a fast chirper to generate a frequency-modulated continuous-wave (FMCW) waveform. Three-dimensional images are generated through range information derived for each pixel scanned over a target. A peak finding algorithm may be used in processing for each pixel to differentiate material layers of the target. Improved focusing is achieved through a compensation signal sampled from a point source calibration target and applied to received signals from active targets prior to FFT-based range compression to extract and display high-resolution target images. Such an imaging radar has particular application in detecting concealed weapons or contraband.

Classification of finger movements by using the ultra-wide band radar.

PubMed

Eldosoky, Mohamed A A

2010-12-01

The coding system of finger movements depends on the differences in the characteristics of the muscles that are responsible for these movements. The ability of ultra-wide band (UWB) radar for use as a tool for identifying the movements of each finger is presented. This will facilitate the ability of the UWB radar in designing a coding system for the movement of fingers of each hand.

Distributed MIMO Radar for Imaging and High Resolution Target Localization

DTIC Science & Technology

2012-02-02

Reduction in Distributed MIMO Radar with Multi-Carrier OFDM Signals Carl Georgeson 11/23/2010 Approved 17 • 10-019 Algorithms for Target Location and...28-2012 Final Report 04/15/2009 - 11/30/2011 Distributed MIMO Radar for Imaging and High Resolution Target Localization FA9550-09-1-0303 Alexander M...error for the general case of MIMO radar with multiple waveforms with non-coherent and coherent observations; (b) finds a closed-form solution for the

A Novel Sensor Selection and Power Allocation Algorithm for Multiple-Target Tracking in an LPI Radar Network

PubMed Central

She, Ji; Wang, Fei; Zhou, Jianjiang

2016-01-01

Radar networks are proven to have numerous advantages over traditional monostatic and bistatic radar. With recent developments, radar networks have become an attractive platform due to their low probability of intercept (LPI) performance for target tracking. In this paper, a joint sensor selection and power allocation algorithm for multiple-target tracking in a radar network based on LPI is proposed. It is found that this algorithm can minimize the total transmitted power of a radar network on the basis of a predetermined mutual information (MI) threshold between the target impulse response and the reflected signal. The MI is required by the radar network system to estimate target parameters, and it can be calculated predictively with the estimation of target state. The optimization problem of sensor selection and power allocation, which contains two variables, is non-convex and it can be solved by separating power allocation problem from sensor selection problem. To be specific, the optimization problem of power allocation can be solved by using the bisection method for each sensor selection scheme. Also, the optimization problem of sensor selection can be solved by a lower complexity algorithm based on the allocated powers. According to the simulation results, it can be found that the proposed algorithm can effectively reduce the total transmitted power of a radar network, which can be conducive to improving LPI performance. PMID:28009819

Multi Ray Model for Near-Ground Millimeter Wave Radar

PubMed Central

Litvak, Boris; Pinhasi, Yosef

2017-01-01

A quasi-optical multi-ray model for a short-range millimeter wave radar is presented. The model considers multi-path effects emerging while multiple rays are scattered from the target and reflected to the radar receiver. Among the examined scenarios, the special case of grazing ground reflections is analyzed. Such a case becomes relevant when short range anti-collision radars are employed in vehicles. Such radars operate at millimeter wavelengths, and are aimed at the detection of targets located several tens of meters from the transmitter. Reflections from the road are expected to play a role in the received signal strength, together with the direct line-of-sight beams illuminated and scattered from the target. The model is demonstrated experimentally using radar operating in the W-band. Controlled measurements were done to distinguish between several scattering target features. The experimental setup was designed to imitate vehicle near-ground millimeter wave radars operating in vehicles. A comparison between analytical calculations and experimental results is made and discussed. PMID:28867776

NCTR using a polarization-agile coherent radar system

NASA Astrophysics Data System (ADS)

Walton, E. K.; Moffatt, D. L.; Garber, F. D.; Kamis, A.; Lai, C. Y.

1986-01-01

This report describes the results of the first year of a research project performed by the Ohio State University ElectroScience Laboratory (OSU/ESL) for the Naval Weapons Center (NWC). The goal of this project is to explore the use of the polarization properties of the signal scattered from a radar target for the purpose of radar target identification. Various radar target identification algorithms were applied to the case of a full polarization coherent radar system, and were tested using a specific data base and noise model. The data base used to test the performance of the radar target identification algorithms developed here is a unique set of measurements made on scale models of aircraft. Measurements were made using the OSU/ESL Compact Radar Measurement Range. The range was operated in a broad-band (1-12 GHZ) mode and the full polarization matrix was measured. Calibrated values (amplitude and phase) of the RCS for the three polarization states were thus available. The polarization states are listed below.

Radar study of seabirds and bats on windward Hawai'i

USGS Publications Warehouse

Reynolds, M.H.; Cooper, B.A.; Day, Robert H.

1997-01-01

Modified marine surveillance radar was used to study the presence/ absence, abundance, and flight activity of four nocturnal species: Hawaiian darkrumped petrel [Pterodroma phaeopygia sandwichensis (Ridgeway)], Newell's shearwater [Puffinus auricularis newelli (Henshaw)], Band-rumped storm-petrel [Oceanodroma castro (Harcourt)], and Hawaiian hoary bat (Lasiurus cinereus semotus Sanborn & Crespo). Hawaiian seabirds were recorded flying to or from inland nesting colonies at seven sampling sites on the windward side of the island of Hawai'i. In total, 527 radar "targets" identified as petrel or shearwater-type on the basis of speed, flight behavior, and radar signal strength were observed during eight nights of sampling. Mean movement rates (targets per minute) for seabird targets were 0.1, 0.1, 0.3, 3.8, 0.9, and 2.2 for surveys at Kahakai, Kapoho, Mauna Loa, Pali Uli, Pu'ulena Crater, and Waipi'o Valley, respectively. Two percent of the petrel and shearwater-type targets detected on radar were confirmed visually or aurally. Flight paths for seabird targets showed strong directionality at six sampling sites. Mean flight speed for seabird targets (n = 524) was 61 km/hr for all survey areas. Peak detection times for seabirds were from 0430 to 0530 hours for birds flying to sea and 2000 to 2150 hours for birds returning to colonies. Most inland, low-elevation sampling sites could not be surveyed reliably for seabirds during the evening activity periods because of radar interference from insects and rapidly flying bats. At those inland sites predawn sampling was the best time for using radar to detect Hawaiian seabirds moving seaward. Hawaiian hoary bats were recorded at eight sampling sites. Eighty-six to 89 radar targets that exhibited erratic flight behavior were identified as "batlike" targets; 17% of these batlike radar targets were confirmed visually. Band-rumped storm-petrels were not identified during our surveys.

Automotive System for Remote Surface Classification.

PubMed

Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

2017-04-01

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions.

Automotive System for Remote Surface Classification

PubMed Central

Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

2017-01-01

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions. PMID:28368297

A fast recognition method of warhead target in boost phase using kinematic features

NASA Astrophysics Data System (ADS)

Chen, Jian; Xu, Shiyou; Tian, Biao; Wu, Jianhua; Chen, Zengping

2015-12-01

The radar targets number increases from one to more when the ballistic missile is in the process of separating the lower stage rocket or casting covers or other components. It is vital to identify the warhead target quickly among these multiple targets for radar tracking. A fast recognition method of the warhead target is proposed to solve this problem by using kinematic features, utilizing fuzzy comprehensive method and information fusion method. In order to weaken the influence of radar measurement noise, an extended Kalman filter with constant jerk model (CJEKF) is applied to obtain more accurate target's motion information. The simulation shows the validity of the algorithm and the effects of the radar measurement precision upon the algorithm's performance.

SAR image classification based on CNN in real and simulation datasets

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-04-01

Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

Shuttle orbiter radar cross-sectional analysis

NASA Technical Reports Server (NTRS)

Cooper, D. W.; James, R.

1979-01-01

Theoretical and model simulation studies on signal to noise levels and shuttle radar cross section are described. Pre-mission system calibrations, system configuration, and postmission system calibration of the tracking radars are described. Conversion of target range, azimuth, and elevation into radar centered east north vertical position coordinates are evaluated. The location of the impinging rf energy with respect to the target vehicles body axis triad is calculated. Cross section correlation between the two radars is presented.

Cloud Type Classification (cldtype) Value-Added Product

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

Flynn, Donna; Shi, Yan; Lim, K-S

The Cloud Type (cldtype) value-added product (VAP) provides an automated cloud type classification based on macrophysical quantities derived from vertically pointing lidar and radar. Up to 10 layers of clouds are classified into seven cloud types based on predetermined and site-specific thresholds of cloud top, base and thickness. Examples of thresholds for selected U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility sites are provided in Tables 1 and 2. Inputs for the cldtype VAP include lidar and radar cloud boundaries obtained from the Active Remotely Sensed Cloud Location (ARSCL) and Surface Meteorological Systems (MET) data. Rainmore » rates from MET are used to determine when radar signal attenuation precludes accurate cloud detection. Temporal resolution and vertical resolution for cldtype are 1 minute and 30 m respectively and match the resolution of ARSCL. The cldtype classification is an initial step for further categorization of clouds. It was developed for use by the Shallow Cumulus VAP to identify potential periods of interest to the LASSO model and is intended to find clouds of interest for a variety of users.« less

Moving target detection for frequency agility radar by sparse reconstruction

NASA Astrophysics Data System (ADS)

Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

2016-09-01

Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

Linearizing an intermodulation radar transmitter by filtering switched tones

NASA Astrophysics Data System (ADS)

Mazzaro, Gregory J.; Sherbondy, Andrew J.; Ranney, Kenneth I.; Sherbondy, Kelly D.; Martone, Anthony F.

2017-05-01

For nonlinear radar, the transmit power required to measure a detectable response from a target is relatively high, and generating that high power is achieved at the cost of linearity. This paper applies the distortion mitigation technique Linearization by Time-Multiplexed Spectrum (LITMUS) to intermodulation radar, a type of nonlinear radar which receives spectral content produced by the mixing of multiple frequencies at a nonlinear target. By implementing LITMUS, an experimental detection system for an intermodulation radar achieves a signal-to-noise ratio up to 20 dB for a total transmit power of approximately 80 mW and nonlinear targets placed at a standoff distance of 2 meters.

Moving target detection for frequency agility radar by sparse reconstruction.

PubMed

Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi

2016-09-01

Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.

SENTINEL-1 and SENTINEL-2 Data Fusion for Wetlands Mapping: Balikdami, Turkey

NASA Astrophysics Data System (ADS)

Kaplan, G.; Avdan, U.

2018-04-01

Wetlands provide a number of environmental and socio-economic benefits such as their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Remote sensing technology has proven to be a useful and frequent application in monitoring and mapping wetlands. Combining optical and microwave satellite data can help with mapping and monitoring the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing radar and optical remote sensing data can increase the wetland classification accuracy. In this paper, data from the fine spatial resolution optical satellite, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, were fused for mapping wetlands. Both Sentinel-1 and Sentinel-2 images were pre-processed. After the pre-processing, vegetation indices were calculated using the Sentinel-2 bands and the results were included in the fusion data set. For the classification of the fused data, three different classification approaches were used and compared. The results showed significant improvement in the wetland classification using both multispectral and microwave data. Also, the presence of the red edge bands and the vegetation indices used in the data set showed significant improvement in the discrimination between wetlands and other vegetated areas. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, showing an overall classification accuracy of approximately 90 % in the object-based classification method. For future research, we recommend multi-temporal image use, terrain data collection, as well as a comparison of the used method with the traditional image fusion techniques.

A Noncontact FMCW Radar Sensor for Displacement Measurement in Structural Health Monitoring

PubMed Central

Li, Cunlong; Chen, Weimin; Liu, Gang; Yan, Rong; Xu, Hengyi; Qi, Yi

2015-01-01

This paper investigates the Frequency Modulation Continuous Wave (FMCW) radar sensor for multi-target displacement measurement in Structural Health Monitoring (SHM). The principle of three-dimensional (3-D) displacement measurement of civil infrastructures is analyzed. The requirements of high-accuracy displacement and multi-target identification for the measuring sensors are discussed. The fundamental measuring principle of FMCW radar is presented with rigorous mathematical formulas, and further the multiple-target displacement measurement is analyzed and simulated. In addition, a FMCW radar prototype is designed and fabricated based on an off-the-shelf radar frontend and data acquisition (DAQ) card, and the displacement error induced by phase asynchronism is analyzed. The conducted outdoor experiments verify the feasibility of this sensing method applied to multi-target displacement measurement, and experimental results show that three targets located at different distances can be distinguished simultaneously with millimeter level accuracy. PMID:25822139

A noncontact FMCW radar sensor for displacement measurement in structural health monitoring.

PubMed

Li, Cunlong; Chen, Weimin; Liu, Gang; Yan, Rong; Xu, Hengyi; Qi, Yi

2015-03-26

This paper investigates the Frequency Modulation Continuous Wave (FMCW) radar sensor for multi-target displacement measurement in Structural Health Monitoring (SHM). The principle of three-dimensional (3-D) displacement measurement of civil infrastructures is analyzed. The requirements of high-accuracy displacement and multi-target identification for the measuring sensors are discussed. The fundamental measuring principle of FMCW radar is presented with rigorous mathematical formulas, and further the multiple-target displacement measurement is analyzed and simulated. In addition, a FMCW radar prototype is designed and fabricated based on an off-the-shelf radar frontend and data acquisition (DAQ) card, and the displacement error induced by phase asynchronism is analyzed. The conducted outdoor experiments verify the feasibility of this sensing method applied to multi-target displacement measurement, and experimental results show that three targets located at different distances can be distinguished simultaneously with millimeter level accuracy.

Clutter attenuation using the Doppler effect in standoff electromagnetic quantum sensing

NASA Astrophysics Data System (ADS)

Lanzagorta, Marco; Jitrik, Oliverio; Uhlmann, Jeffrey; Venegas, Salvador

2016-05-01

In the context of traditional radar systems, the Doppler effect is crucial to detect and track moving targets in the presence of clutter. In the quantum radar context, however, most theoretical performance analyses to date have assumed static targets. In this paper we consider the Doppler effect at the single photon level. In particular, we describe how the Doppler effect produced by clutter and moving targets modifies the quantum distinguishability and the quantum radar error detection probability equations. Furthermore, we show that Doppler-based delayline cancelers can reduce the effects of clutter in the context of quantum radar, but only in the low-brightness regime. Thus, quantum radar may prove to be an important technology if the electronic battlefield requires stealthy tracking and detection of moving targets in the presence of clutter.

35-GHz radar sensor for automotive collision avoidance

NASA Astrophysics Data System (ADS)

Zhang, Jun

1999-07-01

This paper describes the development of a radar sensor system used for automotive collision avoidance. Because the heavy truck may have great larger radar cross section than a motorcyclist has, the radar receiver may have a large dynamic range. And multi-targets at different speed may confuse the echo spectrum causing the ambiguity between range and speed of target. To get more information about target and background and to adapt to the large dynamic range and multi-targets, a frequency modulated and pseudo- random binary sequences phase modulated continuous wave radar system is described. The analysis of this double- modulation system is given. A high-speed signal processing and data processing component are used to process and combine the data and information from echo at different direction and at every moment.

Event Recognition for Contactless Activity Monitoring Using Phase-Modulated Continuous Wave Radar.

PubMed

Forouzanfar, Mohamad; Mabrouk, Mohamed; Rajan, Sreeraman; Bolic, Miodrag; Dajani, Hilmi R; Groza, Voicu Z

2017-02-01

The use of remote sensing technologies such as radar is gaining popularity as a technique for contactless detection of physiological signals and analysis of human motion. This paper presents a methodology for classifying different events in a collection of phase modulated continuous wave radar returns. The primary application of interest is to monitor inmates where the presence of human vital signs amidst different, interferences needs to be identified. A comprehensive set of features is derived through time and frequency domain analyses of the radar returns. The Bhattacharyya distance is used to preselect the features with highest class separability as the possible candidate features for use in the classification process. The uncorrelated linear discriminant analysis is performed to decorrelate, denoise, and reduce the dimension of the candidate feature set. Linear and quadratic Bayesian classifiers are designed to distinguish breathing, different human motions, and nonhuman motions. The performance of these classifiers is evaluated on a pilot dataset of radar returns that contained different events including breathing, stopped breathing, simple human motions, and movement of fan and water. Our proposed pattern classification system achieved accuracies of up to 93% in stationary subject detection, 90% in stop-breathing detection, and 86% in interference detection. Our proposed radar pattern recognition system was able to accurately distinguish the predefined events amidst interferences. Besides inmate monitoring and suicide attempt detection, this paper can be extended to other radar applications such as home-based monitoring of elderly people, apnea detection, and home occupancy detection.

Detection of Fast Moving and Accelerating Targets Compensating Range and Doppler Migration

DTIC Science & Technology

2014-06-01

Radon -Fourier transform has been introduced to realize long- term coherent integration of the moving targets with range migration [8, 9]. Radon ...2010) Long-time coherent integration for radar target detection base on Radon -Fourier transform, in Proceedings of the IEEE Radar Conference, pp...432–436. 9. Xu, J., Yu, J., Peng, Y. & Xia, X. (2011) Radon -Fourier transform for radar target detection, I: Generalized Doppler filter bank, IEEE

Study to investigate and evaluate means of optimizing the Ku-band combined radar/communication functions for the space shuttle

NASA Technical Reports Server (NTRS)

Weber, C. L.; Udalov, S.; Alem, W.

1977-01-01

The performance of the space shuttle orbiter's Ku-Band integrated radar and communications equipment is analyzed for the radar mode of operation. The block diagram of the rendezvous radar subsystem is described. Power budgets for passive target detection are calculated, based on the estimated values of system losses. Requirements for processing of radar signals in the search and track modes are examined. Time multiplexed, single-channel, angle tracking of passive scintillating targets is analyzed. Radar performance in the presence of main lobe ground clutter is considered and candidate techniques for clutter suppression are discussed. Principal system parameter drivers are examined for the case of stationkeeping at ranges comparable to target dimension. Candidate ranging waveforms for short range operation are analyzed and compared. The logarithmic error discriminant utilized for range, range rate and angle tracking is formulated and applied to the quantitative analysis of radar subsystem tracking loops.

Multiple targets detection method in detection of UWB through-wall radar

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

2017-11-01

In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

Estimating Elevation Angles From SAR Crosstalk

NASA Technical Reports Server (NTRS)

Freeman, Anthony

1994-01-01

Scheme for processing polarimetric synthetic-aperture-radar (SAR) image data yields estimates of elevation angles along radar beam to target resolution cells. By use of estimated elevation angles, measured distances along radar beam to targets (slant ranges), and measured altitude of aircraft carrying SAR equipment, one can estimate height of target terrain in each resolution cell. Monopulselike scheme yields low-resolution topographical data.

Study to investigate and evaluate means of optimizing the radar function for the space shuttle. [(pulse radar)

NASA Technical Reports Server (NTRS)

1975-01-01

Results are discussed of a study to define a radar and antenna system which best suits the space shuttle rendezvous requirements. Topics considered include antenna characteristics and antenna size tradeoffs, fundamental sources of measurement errors inherent in the target itself, backscattering crosssection models of the target and three basic candidate radar types. Antennas up to 1.5 meters in diameter are within specified installation constraints, however, a 1 meter diameter paraboloid and a folding, four slot backfeed on a two gimbal mount implemented for a spiral acquisition scan is recommended. The candidate radar types discussed are: (1) noncoherent pulse radar (2) coherent pulse radar and (3) pulse Doppler radar with linear FM ranging. The radar type recommended is a pulse Doppler with linear FM ranging. Block diagrams of each radar system are shown.

Improving angular resolution with Scan-MUSIC algorithm for real complex targets using 35-GHz millimeter-wave radar

NASA Astrophysics Data System (ADS)

Ly, Canh

2004-08-01

Scan-MUSIC algorithm, developed by the U.S. Army Research Laboratory (ARL), improves angular resolution for target detection with the use of a single rotatable radar scanning the angular region of interest. This algorithm has been adapted and extended from the MUSIC algorithm that has been used for a linear sensor array. Previously, it was shown that the SMUSIC algorithm and a Millimeter Wave radar can be used to resolve two closely spaced point targets that exhibited constructive interference, but not for the targets that exhibited destructive interference. Therefore, there were some limitations of the algorithm for the point targets. In this paper, the SMUSIC algorithm is applied to a problem of resolving real complex scatterer-type targets, which is more useful and of greater practical interest, particular for the future Army radar system. The paper presents results of the angular resolution of the targets, an M60 tank and an M113 Armored Personnel Carrier (APC), that are within the mainlobe of a Κα-band radar antenna. In particular, we applied the algorithm to resolve centroids of the targets that were placed within the beamwidth of the antenna. The collected coherent data using the stepped-frequency radar were compute magnitudely for the SMUSIC calculation. Even though there were significantly different signal returns for different orientations and offsets of the two targets, we resolved those two target centroids when they were as close as about 1/3 of the antenna beamwidth.

Classifying coastal resources by integrating optical and radar imagery and color infrared photography

USGS Publications Warehouse

Ramsey, Elijah W.; Nelson, Gene A.; Sapkota, Sijan

1998-01-01

A progressive classification of a marsh and forest system using Landsat Thematic Mapper (TM), color infrared (CIR) photograph, and ERS-1 synthetic aperture radar (SAR) data improved classification accuracy when compared to classification using solely TM reflective band data. The classification resulted in a detailed identification of differences within a nearly monotypic black needlerush marsh. Accuracy percentages of these classes were surprisingly high given the complexities of classification. The detailed classification resulted in a more accurate portrayal of the marsh transgressive sequence than was obtainable with TM data alone. Individual sensor contribution to the improved classification was compared to that using only the six reflective TM bands. Individually, the green reflective CIR and SAR data identified broad categories of water, marsh, and forest. In combination with TM, SAR and the green CIR band each improved overall accuracy by about 3% and 15% respectively. The SAR data improved the TM classification accuracy mostly in the marsh classes. The green CIR data also improved the marsh classification accuracy and accuracies in some water classes. The final combination of all sensor data improved almost all class accuracies from 2% to 70% with an overall improvement of about 20% over TM data alone. Not only was the identification of vegetation types improved, but the spatial detail of the classification approached 10 m in some areas.

Synthetic aperture radar target detection, feature extraction, and image formation techniques

NASA Technical Reports Server (NTRS)

Li, Jian

1994-01-01

This report presents new algorithms for target detection, feature extraction, and image formation with the synthetic aperture radar (SAR) technology. For target detection, we consider target detection with SAR and coherent subtraction. We also study how the image false alarm rates are related to the target template false alarm rates when target templates are used for target detection. For feature extraction from SAR images, we present a computationally efficient eigenstructure-based 2D-MODE algorithm for two-dimensional frequency estimation. For SAR image formation, we present a robust parametric data model for estimating high resolution range signatures of radar targets and for forming high resolution SAR images.

A Technique for Real-Time Ionospheric Ranging Error Correction Based On Radar Dual-Frequency Detection

NASA Astrophysics Data System (ADS)

Lyu, Jiang-Tao; Zhou, Chen

2017-12-01

Ionospheric refraction is one of the principal error sources for limiting the accuracy of radar systems for space target detection. High-accuracy measurement of the ionospheric electron density along the propagation path of radar wave is the most important procedure for the ionospheric refraction correction. Traditionally, the ionospheric model and the ionospheric detection instruments, like ionosonde or GPS receivers, are employed for obtaining the electron density. However, both methods are not capable of satisfying the requirements of correction accuracy for the advanced space target radar system. In this study, we propose a novel technique for ionospheric refraction correction based on radar dual-frequency detection. Radar target range measurements at two adjacent frequencies are utilized for calculating the electron density integral exactly along the propagation path of the radar wave, which can generate accurate ionospheric range correction. The implementation of radar dual-frequency detection is validated by a P band radar located in midlatitude China. The experimental results present that the accuracy of this novel technique is more accurate than the traditional ionospheric model correction. The technique proposed in this study is very promising for the high-accuracy radar detection and tracking of objects in geospace.

Electromagnetic approaches to wall characterization, wall mitigation, and antenna design for through-the-wall radar systems

NASA Astrophysics Data System (ADS)

Thajudeen, Christopher

Through-the-wall imaging (TWI) is a topic of current interest due to its wide range of public safety, law enforcement, and defense applications. Among the various available technologies such as, acoustic, thermal, and optical imaging, which can be employed to sense and image targets of interest, electromagnetic (EM) imaging, in the microwave frequency bands, is the most widely utilized technology and has been at the forefront of research in recent years. The primary objectives for any Through-the-Wall Radar Imaging (TWRI) system are to obtain a layout of the building and/or inner rooms, detect if there are targets of interest including humans or weapons, determine if there are countermeasures being employed to further obscure the contents of a building or room of interest, and finally to classify the detected targets. Unlike conventional radar scenarios, the presence of walls, made of common construction materials such as brick, drywall, plywood, cinder block, and solid concrete, adversely affects the ability of any conventional imaging technique to properly image targets enclosed within building structures as the propagation through the wall can induce shadowing effects on targets of interest which may result in image degradation, errors in target localization, and even complete target masking. For many applications of TWR systems, the wall ringing signals are strong enough to mask the returns from targets not located a sufficient distance behind the wall, beyond the distance of the wall ringing, and thus without proper wall mitigation, target detection becomes extremely difficult. The results presented in this thesis focus on the development of wall parameter estimation, and intra-wall and wall-type characterization techniques for use in both the time and frequency domains as well as analysis of these techniques under various real world scenarios such as reduced system bandwidth scenarios, various wall backing scenarios, the case of inhomogeneous walls, presence of ground reflections, and situations where they may be applied to the estimation of the parameters associated with an interior wall. It is demonstrated through extensive computer simulations and laboratory experiments that, by proper exploitation of the electromagnetic characteristics of walls, one can efficiently extract the constitutive parameters associated with unknown wall(s) as well as to characterize and image the intra-wall region. Additionally, it is possible, to a large extent, to remove the negative wall effects, such as shadowing and incorrect target localization, as well as to enhance the imaging and classification of targets behind walls. In addition to the discussion of post processing the radar data to account for wall effects, the design of antenna elements used for transmit (Tx) and receive (Rx) operations in TWR radars is also discussed but limited to antennas for mobile, handheld, or UAV TWR systems which impose design requirements such as low profiles, wide operational bands, and in most cases lend themselves to fabrication using surface printing techniques. A new class of wideband antennas, formed though the use of printed metallic paths in the form of Peano and Hilbert space-filling curves (SFC) to provide top-loading properties that miniaturize monopole antenna elements, has been developed for applications in conformal and/or low profile antennas systems, such as mobile platforms for TWRI and communication systems. Additionally, boresight gain enhancements of a stair-like antenna geometry, through the addition of parasitic self-similar patches and gate like ground plane structures, are presented.

Caracterisation des occupations du sol en milieu urbain par imagerie radar

NASA Astrophysics Data System (ADS)

Codjia, Claude

This study aims to test the relevance of medium and high-resolution SAR images on the characterization of the types of land use in urban areas. To this end, we have relied on textural approaches based on second-order statistics. Specifically, we look for texture parameters most relevant for discriminating urban objects. We have used in this regard Radarsat-1 in fine polarization mode and Radarsat-2 HH fine mode in dual and quad polarization and ultrafine mode HH polarization. The land uses sought were dense building, medium density building, low density building, industrial and institutional buildings, low density vegetation, dense vegetation and water. We have identified nine texture parameters for analysis, grouped into families according to their mathematical definitions in a first step. The parameters of similarity / dissimilarity include Homogeneity, Contrast, the Differential Inverse Moment and Dissimilarity. The parameters of disorder are Entropy and the Second Angular Momentum. The Standard Deviation and Correlation are the dispersion parameters and the Average is a separate family. It is clear from experience that certain combinations of texture parameters from different family used in classifications yield good results while others produce kappa of very little interest. Furthermore, we realize that if the use of several texture parameters improves classifications, its performance ceils from three parameters. The calculation of correlations between the textures and their principal axes confirm the results. Despite the good performance of this approach based on the complementarity of texture parameters, systematic errors due to the cardinal effects remain on classifications. To overcome this problem, a radiometric compensation model was developed based on the radar cross section (SER). A radar simulation from the digital surface model of the environment allowed us to extract the building backscatter zones and to analyze the related backscatter. Thus, we were able to devise a strategy of compensation of cardinal effects solely based on the responses of the objects according to their orientation from the plane of illumination through the radar's beam. It appeared that a compensation algorithm based on the radar cross section was appropriate. Some examples of the application of this algorithm on HH polarized RADARSAT-2 images are presented as well. Application of this algorithm will allow considerable gains with regard to certain forms of automation (classification and segmentation) at the level of radar imagery thus generating a higher level of quality in regard to visual interpretation. Application of this algorithm on RADARSAT-1 and RADARSAT-2 images with HH, HV, VH, and VV polarisations helped make considerable gains and eliminate most of the classification errors due to the cardinal effects.

A multi-sensor scenario for coastal surveillance

NASA Astrophysics Data System (ADS)

van den Broek, A. C.; van den Broek, S. P.; van den Heuvel, J. C.; Schwering, P. B. W.; van Heijningen, A. W. P.

2007-10-01

Maritime borders and coastal zones are susceptible to threats such as drug trafficking, piracy, undermining economical activities. At TNO Defence, Security and Safety various studies aim at improving situational awareness in a coastal zone. In this study we focus on multi-sensor surveillance of the coastal environment. We present a study on improving classification results for small sea surface targets using an advanced sensor suite and a scenario in which a small boat is approaching the coast. A next generation sensor suite mounted on a tower has been defined consisting of a maritime surveillance and tracking radar system, capable of producing range profiles and ISAR imagery of ships, an advanced infrared camera and a laser range profiler. For this suite we have developed a multi-sensor classification procedure, which is used to evaluate the capabilities for recognizing and identifying non-cooperative ships in coastal waters. We have found that the different sensors give complementary information. Each sensor has its own specific distance range in which it contributes most. A multi-sensor approach reduces the number of misclassifications and reliable classification results are obtained earlier compared to a single sensor approach.

Passive Coherent Detection and Target Location with Multiple Non-Cooperative Transmitters

DTIC Science & Technology

2015-06-01

to detect, separate, classify, locate, and track sources of emissions in multi-target environments—triggered the development of passive radar...radar capitalizes on transmitters of opportunity to detect and locate sources of transmission or targets without deliberate emissions . The...equipment as all necessary hardware is currently available on most naval ships. 3 Bistatic radar geometry. Figure 1. B. HISTORY The concept of

Calibration of polarimetric radar systems with good polarization isolation

NASA Technical Reports Server (NTRS)

Sarabandi, Kamal; Ulaby, Fawwaz T.; Tassoudji, M. Ali

1990-01-01

A practical technique is proposed for calibrating single-antenna polarimetric radar systems using a metal sphere plus any second target with a strong cross-polarized radar cross section. This technique assumes perfect isolation between antenna ports. It is shown that all magnitudes and phases (relative to one of the like-polarized linear polarization configurations) of the radar transfer function can be calibrated without knowledge of the scattering matrix of the second target. Comparison of the values measured (using this calibration technique) for a tilted cylinder at X-band with theoretical values shows agreement within + or - 0.3 dB in magnitude and + or - 5 degrees in phase. The radar overall cross-polarization isolation was 25 dB. The technique is particularly useful for calibrating a radar under field conditions, because it does not require the careful alignment of calibration targets.

Analysis of Features for Synthetic Aperture Radar Target Classification

DTIC Science & Technology

2015-03-26

rewriting the variance of a class after projection as s2c = ∑ n wT (xc,n −mc)(xc,n −mc)T w, = wT Scw, (2.25) where subscript c ∈ [1, 2] is the class...such a case, the distribution of class c is N(mc,SW), where SW is the same as in Equation (2.29). Additionally, if m1 ≈ m2, then w approaches zero as...function of the bandwidth, B, and the speed of light, c , where [8] ρx = c 2B . (2.48) 21 Cross-range resolution, ρy, is a function of the wavelength

Applications of Remote Sensing for Studying Lateral Carbon Fluxes and Inundation Dynamics in Tidal Wetlands

NASA Astrophysics Data System (ADS)

Lamb, B. T.; Tzortziou, M.; McDonald, K. C.

2017-12-01

Wetlands play a key role in Earth's carbon cycle. However, wetland carbon cycling exhibits a high level of spatiotemporal dynamism, and thus, is not as well understood as carbon cycling in other ecosystems. In order to accurately characterize wetland carbon cycling and fluxes, wetland vegetation phenology, seasonal inundation dynamics, and tidal regimes must be understood as these factors influence carbon generation and transport. Here, we use radar remote sensing to map wetland properties in the Chesapeake Bay, the largest estuary in the United States with more than 1,500 square miles of tidal wetlands, across a range of tidal amplitudes, salinity regimes, and soil organic matter content levels. We have been using Sentinel-1 and ALOS PALSAR-1 radar measurements to characterize vegetation and seasonal inundation dynamics with the future goal of characterizing salinity gradients and tidal regimes. Differences in radar backscatter from various surface targets has been shown to effectively discriminate between dry soil, wet soil, vegetated areas, and open water. Radar polarization differences and ratios are particularly effective at distinguishing between vegetated and non-vegetated areas. Utilizing these principles, we have been characterizing wetland types using supervised classification techniques including: Random Forest, Maximum Likelihood, and Minimum Distance. The National Wetlands Inventory has been used as training and validation data. Ideally, the techniques we outline in this research will be applicable to the characterization of wetlands in coastal areas outside of Chesapeake Bay.

Radar for tracer particles

NASA Astrophysics Data System (ADS)

Ott, Felix; Herminghaus, Stephan; Huang, Kai

2017-05-01

We introduce a radar system capable of tracking a 5 mm spherical target continuously in three dimensions. The 10 GHz (X-band) radar system has a transmission power of 1 W and operates in the near field of the horn antennae. By comparing the phase shift of the electromagnetic wave traveling through the free space with an IQ-mixer, we obtain the relative movement of the target with respect to the antennae. From the azimuth and inclination angles of the receiving antennae obtained in the calibration, we reconstruct the target trajectory in a three-dimensional Cartesian system. Finally, we test the tracking algorithm with target moving in circular as well as in pendulum motions and discuss the capability of the radar system.

Coefficient of variation for use in crop area classification across multiple climates

NASA Astrophysics Data System (ADS)

Whelen, Tracy; Siqueira, Paul

2018-05-01

In this study, the coefficient of variation (CV) is introduced as a unitless statistical measurement for the classification of croplands using synthetic aperture radar (SAR) data. As a measurement of change, the CV is able to capture changing backscatter responses caused by cycles of planting, growing, and harvesting, and thus is able to differentiate these areas from a more static forest or urban area. Pixels with CV values above a given threshold are classified as crops, and below the threshold are non-crops. This paper uses cross-polarized L-band SAR data from the ALOS PALSAR satellite to classify eleven regions across the United States, covering a wide range of major crops and climates. Two separate sets of classification were done, with the first targeting the optimum classification thresholds for each dataset, and the second using a generalized threshold for all datasets to simulate a large-scale operationalized situation. Overall accuracies for the first phase of classification ranged from 66%-81%, and 62%-84% for the second phase. Visual inspection of the results shows numerous possibilities for improving the classifications while still using the same classification method, including increasing the number and temporal frequency of input images in order to better capture phenological events and mitigate the effects of major precipitation events, as well as more accurate ground truth data. These improvements would make the CV method a viable tool for monitoring agriculture throughout the year on a global scale.

Adaptive waveform optimization design for target detection in cognitive radar

NASA Astrophysics Data System (ADS)

Zhang, Xiaowen; Wang, Kaizhi; Liu, Xingzhao

2017-01-01

The problem of adaptive waveform design for target detection in cognitive radar (CR) is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended target with unknown target impulse response (TIR). In order to estimate the TIR accurately, the Kalman filter is used in target tracking. In each Kalman filtering iteration, a flexible online waveform spectrum optimization design taking both detection and range resolution into account is modeled in Fourier domain. Unlike existing CR waveform, the proposed waveform can be simultaneously updated according to the environment information fed back by receiver and radar performance demands. Moreover, the influence of waveform spectral phase to radar performance is analyzed. Simulation results demonstrate that CR with the proposed waveform performs better than a traditional radar system with a fixed waveform and offers more flexibility and suitability. In addition, waveform spectral phase will not influence tracking, detection, and range resolution performance but will greatly influence waveform forming speed and peak-to-average power ratio.

Doppler characteristics of sea clutter.

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

Raynal, Ann Marie; Doerry, Armin Walter

2010-06-01

Doppler radars can distinguish targets from clutter if the target's velocity along the radar line of sight is beyond that of the clutter. Some targets of interest may have a Doppler shift similar to that of clutter. The nature of sea clutter is different in the clutter and exo-clutter regions. This behavior requires special consideration regarding where a radar can expect to find sea-clutter returns in Doppler space and what detection algorithms are most appropriate to help mitigate false alarms and increase probability of detection of a target. This paper studies the existing state-of-the-art in the understanding of Doppler characteristicsmore » of sea clutter and scattering from the ocean to better understand the design and performance choices of a radar in differentiating targets from clutter under prevailing sea conditions.« less

Exploration of Data Fusion between Polarimetric Radar and Multispectral Image Data

DTIC Science & Technology

2012-09-01

target decomposition theorems in radar polarimetry . Transactions on Geoscience and Remote Sensing, 34(2), 498–518. Cloude, S. R. (1985). Target...Proceedings of the Journees Internationales De La Polarimetrie Radar (JIPR ‘90), Nantes, France. Huynen, J. R. (1965). Measurement of theTarget scattering...J. A. (2006). Review of passive imaging polarimetry for remote sensing applications. Applied Optics, 45(22), 5453–5469. Vanzyl, J., Zebker, H

A system for the real-time display of radar and video images of targets

NASA Technical Reports Server (NTRS)

Allen, W. W.; Burnside, W. D.

1990-01-01

Described here is a software and hardware system for the real-time display of radar and video images for use in a measurement range. The main purpose is to give the reader a clear idea of the software and hardware design and its functions. This system is designed around a Tektronix XD88-30 graphics workstation, used to display radar images superimposed on video images of the actual target. The system's purpose is to provide a platform for tha analysis and documentation of radar images and their associated targets in a menu-driven, user oriented environment.

The composition of M-type asteroids: Synthesis of spectroscopic and radar observations

NASA Astrophysics Data System (ADS)

Neeley, J. R.; Ockert-Bell, M. E.; Clark, B. E.; Shepard, M. K.; Cloutis, E. A.; Fornasier, S.; Bus, S. J.

2011-10-01

This work updates our and expands our long term radar-driven observational campaign of 27 main-belt asteroids (MBAs) focused on Bus-DeMeo Xc- and Xk-type objects (Tholen X and M class asteroids) using the Arecibo radar and NASA Infrared Telescope Facilities (IRTF). Seventeen of our targets were near-simultaneously observed with radar and those observations are described in companion paper (Shepard et al., 2010). We utilized visible wavelength for a more complete compositional analysis of our targets. Compositional evidence is derived from our target asteroid spectra using three different methods: 1) a χ2 search for spectral matches in the RELAB database, 2) parametric comparisons with meteorites and 3) linear discriminant analysis. This paper synthesizes the results of the RELAB search, parametric comparisons, and linear discriminant analysis with compositional suggestions based on radar observations. We find that for six of seventeen targets with radar data, our spectral results are consistent with their radar analog (16 Psyche, 21 Lutetia, 69 Hesperia, 135 Hertha, 216 Kleopatra, and 497 Iva). For twenty out of twenty-seven objects our statistical comparisons with RELAB meteorites result in consistent analog identification, providing a degree of confidence in our parametric methods.

Eyeballing oscillators for pulsed Doppler radar

NASA Astrophysics Data System (ADS)

Goldman, S.

1985-03-01

The visibility of small targets to a Doppler radar system in the presence of large targets is limited by phase noise. Such limitations occur when an airborne radar searches the ground for a mobile vehicle. Under these conditions, the performance of the Doppler radar depends greatly on the specifications of its phased-locked oscillator. Goldman (1984) has discussed the steps required to evaluate the noise resulting from a pulsed Doppler radar system. In the present investigation, these techniques are applied in reverse to determine system specifications for oscillator noise. A 95-GHz pulsed Doppler radar system is used as an example of specifying system phase noise.

Wind turbine impact on operational weather radar I/Q data: characterisation and filtering

NASA Astrophysics Data System (ADS)

Norin, Lars

2017-05-01

For the past 2 decades wind turbines have been growing in number all over the world as a response to the increasing demand for renewable energy. However, the rapid expansion of wind turbines presents a problem for many radar systems, including weather radars. Wind turbines in the line of sight of a weather radar can have a negative impact on the radar's measurements. As weather radars are important instruments for meteorological offices, finding a way for wind turbines and weather radars to co-exist would be of great societal value.Doppler weather radars base their measurements on in-phase and quadrature phase (I/Q) data. In this work a month's worth of recordings of high-resolution I/Q data from an operational Swedish C-band weather radar are presented. The impact of point targets, such as masts and wind turbines, on the I/Q data is analysed and characterised. It is shown that the impact of point targets on single radar pulses, when normalised by amplitude, is manifested as a distinct and highly repeatable signature. The shape of this signature is found to be independent of the size, shape and yaw angle of the wind turbine. It is further demonstrated how the robustness of the point target signature can be used to identify and filter out the impact of wind turbines in the radar's signal processor.

Identification of corn fields using multidate radar data

NASA Technical Reports Server (NTRS)

Shanmugan, K. S.; Ulaby, F. T.; Narayanan, V.; Dobson, C.

1983-01-01

Airborne C- and L-band radar data acquired over a test site in western kansas were analyzed to determine corn-field identification accuracies obtainable using single-channel, multichannel, and multidate radar data. An automated pattern-recognition procedure was used to classify 144 fields into three categories: corn, pasture land, and bare soil (including wheat stubble and fallow). Corn fields were identified with accuracies ranging from 85 percent for single channel, single-date data to 100 percent for single-channel, multidate data. The effects of radar parameters such as frequency, polarization, and look angle as well as the effects of soil moisture on the classification accuracy are also presented.

Synthetic aperture radar target simulator

NASA Technical Reports Server (NTRS)

Zebker, H. A.; Held, D. N.; Goldstein, R. M.; Bickler, T. C.

1984-01-01

A simulator for simulating the radar return, or echo, from a target seen by a SAR antenna mounted on a platform moving with respect to the target is described. It includes a first-in first-out memory which has digital information clocked in at a rate related to the frequency of a transmitted radar signal and digital information clocked out with a fixed delay defining range between the SAR and the simulated target, and at a rate related to the frequency of the return signal. An RF input signal having a frequency similar to that utilized by a synthetic aperture array radar is mixed with a local oscillator signal to provide a first baseband signal having a frequency considerably lower than that of the RF input signal.

Study of time-reversal-based signal processing applied to polarimetric GPR detection of elongated targets

NASA Astrophysics Data System (ADS)

Santos, Vinicius Rafael N.; Teixeira, Fernando L.

2017-04-01

Ground penetrating radar (GPR) is a useful sensing modality for mapping and identification of underground infrastructure networks, such as metal and concrete pipes (gas, water or sewer), phone conduits or cables, and other buried objects. Due to the polarization-dependent response of typical targets, it is of interest to investigate the optimum antenna arrangement and/or combination of arrangements that maximize the detection and classification capabilities of polarimetric GPR imaging systems. Here, we provide a preliminary study of time-reversal-based techniques applied to target detection by GPR utilizing different relative orientations of linear-polarized antenna elements (with respect to each other, as well as to the targets). We modeled three different pipe materials (metallic, plastic and concrete) and GPR systems operating at center frequencies of 100 MHz and 200 MHz. Full-wave numerical simulations are adopted to account for mutual coupling between targets. This type of assessment study may contribute to the improvement of GPR data interpretation of infrastructure networks in urban area surveys and in other engineering studies.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors

PubMed Central

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L.; Rufo, Elena

2013-01-01

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation. PMID:23609804

Computational burden resulting from image recognition of high resolution radar sensors.

PubMed

López-Rodríguez, Patricia; Fernández-Recio, Raúl; Bravo, Ignacio; Gardel, Alfredo; Lázaro, José L; Rufo, Elena

2013-04-22

This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation.

Middle Atmosphere Program. Handbook for MAP. Volume 30: International School on Atmospheric Radar

NASA Technical Reports Server (NTRS)

Fukao, Shoichiro (Editor)

1989-01-01

Broad, tutorial coverage is given to the technical and scientific aspects of mesosphere stratosphere troposphere (MST) meteorological radar systems. Control issues, signal processing, atmospheric waves, the historical aspects of radar atmospheric dynamics, incoherent scatter radars, radar echoes, radar targets, and gravity waves are among the topics covered.

Radar cross sections of standard and complex shape targets

NASA Technical Reports Server (NTRS)

Sohel, M. S.

1974-01-01

The theoretical, analytical, and experimental results are described for radar cross sections (RCS) of different-shaped targets. Various techniques for predicting RCS are given, and RCS of finite standard targets are presented. Techniques used to predict the RCS of complex targets are made, and the RCS complex shapes are provided.

Mutual information-based LPI optimisation for radar network

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Zhou, Jianjiang; Wang, Fei; Chen, Jun

2015-07-01

Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.

SAR image dataset of military ground targets with multiple poses for ATR

NASA Astrophysics Data System (ADS)

Belloni, Carole; Balleri, Alessio; Aouf, Nabil; Merlet, Thomas; Le Caillec, Jean-Marc

2017-10-01

Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.

KU-Band rendezvous radar performance computer simulation model

NASA Technical Reports Server (NTRS)

Griffin, J. W.

1980-01-01

The preparation of a real time computer simulation model of the KU band rendezvous radar to be integrated into the shuttle mission simulator (SMS), the shuttle engineering simulator (SES), and the shuttle avionics integration laboratory (SAIL) simulator is described. To meet crew training requirements a radar tracking performance model, and a target modeling method were developed. The parent simulation/radar simulation interface requirements, and the method selected to model target scattering properties, including an application of this method to the SPAS spacecraft are described. The radar search and acquisition mode performance model and the radar track mode signal processor model are examined and analyzed. The angle, angle rate, range, and range rate tracking loops are also discussed.

Ultra-Wideband EMI Sensing: Non-Metallic Target Detection and Automatic Classification of Unexploded Ordnance

NASA Astrophysics Data System (ADS)

Sigman, John Brevard

Buried explosive hazards present a pressing problem worldwide. Millions of acres and thousands of sites are contaminated in the United States alone [1, 2]. There are three categories of explosive hazards: metallic, intermediate-electrical conducting (IEC), and non-conducting targets. Metallic target detection and classification by electromagnetic (EM) signature has been the subject of research for many years. Key to the success of this research is modern multi-static Electromagnetic Induction (EMI) sensors, which are able to measure the wideband EMI response from metallic buried targets. However, no hardware solutions exist which can characterize IEC and non-conducting targets. While high-conducting metallic targets exhibit a quadrature peak response for frequencies in a traditional EMI regime under 100 kHz, the response of intermediate-conducting objects manifests at higher frequencies, between 100 kHz and 15 MHz. In addition to high-quality electromagnetic sensor data and robust electromagnetic models, a classification procedure is required to discriminate Targets of Interest (TOI) from clutter. Currently, costly human experts are used for this task. This expense and effort can be spared by using statistical signal processing and machine learning. This thesis has two main parts. In the first part, we explore using the high frequency EMI (HFEMI) band (100 kHz-15 MHz) for detection of carbon fiber UXO, voids, and of materials with characteristics that may be associated with improvised explosive devices (IED). We constructed an HFEMI sensing instrument, and apply the techniques of metal detection to sensing in a band of frequencies which are the transition between the induction and radar bands. In this transition domain, physical considerations and technological issues arise that cannot be solved via the approaches used in either of the bracketing lower and higher frequency ranges. In the second half of this thesis, we present a procedure for automatic classification of UXO. For maximum generality, our algorithm is robust and can handle sparse training examples of multi-class data. This procedure uses an unsupervised starter, semi-supervised techniques to gather training data, and concludes with supervised learning until all TOI are found. Additionally, an inference method for estimating the number of remaining true positives from a partial Receiver Operating Characteristic (ROC) curve is presented and applied to live-site dig histories.

Classification and correction of the radar bright band with polarimetric radar

NASA Astrophysics Data System (ADS)

Hall, Will; Rico-Ramirez, Miguel; Kramer, Stefan

2015-04-01

The annular region of enhanced radar reflectivity, known as the Bright Band (BB), occurs when the radar beam intersects a layer of melting hydrometeors. Radar reflectivity is related to rainfall through a power law equation and so this enhanced region can lead to overestimations of rainfall by a factor of up to 5, so it is important to correct for this. The BB region can be identified by using several techniques including hydrometeor classification and freezing level forecasts from mesoscale meteorological models. Advances in dual-polarisation radar measurements and continued research in the field has led to increased accuracy in the ability to identify the melting snow region. A method proposed by Kitchen et al (1994), a form of which is currently used operationally in the UK, utilises idealised Vertical Profiles of Reflectivity (VPR) to correct for the BB enhancement. A simpler and more computationally efficient method involves the formation of an average VPR from multiple elevations for correction that can still cause a significant decrease in error (Vignal 2000). The purpose of this research is to evaluate a method that relies only on analysis of measurements from an operational C-band polarimetric radar without the need for computationally expensive models. Initial results show that LDR is a strong classifier of melting snow with a high Critical Success Index of 97% when compared to the other variables. An algorithm based on idealised VPRs resulted in the largest decrease in error when BB corrected scans are compared to rain gauges and to lower level scans with a reduction in RMSE of 61% for rain-rate measurements. References Kitchen, M., R. Brown, and A. G. Davies, 1994: Real-time correction of weather radar data for the effects of bright band, range and orographic growth in widespread precipitation. Q.J.R. Meteorol. Soc., 120, 1231-1254. Vignal, B. et al, 2000: Three methods to determine profiles of reflectivity from volumetric radar data to correct precipitation estimates. J. Appl. Meteor., 39(10), 1715-1726.

Automated target recognition using passive radar and coordinated flight models

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.; Lanterman, Aaron D.

2003-09-01

Rather than emitting pulses, passive radar systems rely on illuminators of opportunity, such as TV and FM radio, to illuminate potential targets. These systems are particularly attractive since they allow receivers to operate without emitting energy, rendering them covert. Many existing passive radar systems estimate the locations and velocities of targets. This paper focuses on adding an automatic target recognition (ATR) component to such systems. Our approach to ATR compares the Radar Cross Section (RCS) of targets detected by a passive radar system to the simulated RCS of known targets. To make the comparison as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. The estimated positions become inputs for an algorithm that uses a coordinated flight model to compute probable aircraft orientation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of several potential target classes as they execute the estimated maneuvers. The RCS is then scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. The Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern, so that the RCS can be further scaled. The Rician model compares the RCS of the illuminated aircraft with those of the potential targets. This comparison results in target identification.

Radar Resource Management in a Dense Target Environment

DTIC Science & Technology

2014-03-01

problem faced by networked MFRs . While relaxing our assumptions concerning information gain presents numerous challenges worth exploring, future research...linear programming MFR multifunction phased array radar MILP mixed integer linear programming NATO North Atlantic Treaty Organization PDF probability...1: INTRODUCTION Multifunction phased array radars ( MFRs ) are capable of performing various tasks in rapid succession. The performance of target search

Maritime microwave radar and electro-optical data fusion for homeland security

NASA Astrophysics Data System (ADS)

Seastrand, Mark J.

2004-09-01

US Customs is responsible for monitoring all incoming air and maritime traffic, including the island of Puerto Rico as a US territory. Puerto Rico offers potentially obscure points of entry to drug smugglers. This environment sets forth a formula for an illegal drug trade - based relatively near the continental US. The US Customs Caribbean Air and Marine Operations Center (CAMOC), located in Puntas Salinas, has the charter to monitor maritime and Air Traffic Control (ATC) radars. The CAMOC monitors ATC radars and advises the Air and Marine Branch of US Customs of suspicious air activity. In turn, the US Coast Guard and/or US Customs will launch air and sea assets as necessary. The addition of a coastal radar and camera system provides US Customs a maritime monitoring capability for the northwestern end of Puerto Rico (Figure 1). Command and Control of the radar and camera is executed at the CAMOC, located 75 miles away. The Maritime Microwave Surveillance Radar performs search, primary target acquisition and target tracking while the Midwave Infrared (MWIR) camera performs target identification. This wide area surveillance, using a combination of radar and MWIR camera, offers the CAMOC a cost and manpower effective approach to monitor, track and identify maritime targets.

Sea ice type maps from Alaska synthetic aperture radar facility imagery: An assessment

NASA Technical Reports Server (NTRS)

Fetterer, Florence M.; Gineris, Denise; Kwok, Ronald

1994-01-01

Synthetic aperture radar (SAR) imagery received at the Alaskan SAR Facility is routinely and automatically classified on the Geophysical Processor System (GPS) to create ice type maps. We evaluated the wintertime performance of the GPS classification algorithm by comparing ice type percentages from supervised classification with percentages from the algorithm. The root mean square (RMS) difference for multiyear ice is about 6%, while the inconsistency in supervised classification is about 3%. The algorithm separates first-year from multiyear ice well, although it sometimes fails to correctly classify new ice and open water owing to the wide distribution of backscatter for these classes. Our results imply a high degree of accuracy and consistency in the growing archive of multiyear and first-year ice distribution maps. These results have implications for heat and mass balance studies which are furthered by the ability to accurately characterize ice type distributions over a large part of the Arctic.

Fisheries imaging radar surveillance test /FIRST/ - Bering Sea test

NASA Technical Reports Server (NTRS)

Woods, E. G.; Ivey, J. H.

1977-01-01

A joint NOAA, U.S. Coast Guard and NASA program is being conducted to determine if a synthetic aperture radar (SAR) system, such as planned for NASA's SEASAT, can be useful in monitoring fishing vessels within the newly established 200-mile fishing limit. As part of this program, data gathering field operations were conducted over concentrations of foreign fishing vessels in the Bering Sea off Alaska in April 1976. The Jet Propulsion Laboratory developed synthetic aperture L-band radar which was flown aboard the NASA Convair 990 aircraft, with a Coast Guard cutter and C-130 aircraft simultaneously gathering data to provide both radar imagery and sea truth information on the vessels being imaged. Results indicate that synthetic aperture radar systems have potential for all weather detection, enumeration and classification of fishing vessels.

Shuttle orbiter KU-band radar/communications system design evaluation

NASA Technical Reports Server (NTRS)

1979-01-01

An expanded introduction is presented which addresses the in-depth nature of the tasks and indicates continuity of the reported effort and results with previous work and related contracts, and the two major modes of operation which exist in the Ku-band system, namely, the radar mode and the communication mode, are described. The Ku-band radar system is designed to search for a target in a designated or undesignated mode, then track the detected target, which might be cooperative (active) or passive, providing accurate, estimates of the target range, range rate, angle and angle rate to enable the orbiter to rendezvous with this target. The radar mode is described along with a summary of its predicted performance. The principal sub-unit that implements the radar function is the electronics assembly 2(EA-2). The relationship of EA-2 to the remainder of the Ku-band system is shown. A block diagram of EA-2 is presented including the main command and status signals between EA-2 and the other Ku-band units.

Effects of target shape and reflection on laser radar cross sections.

PubMed

Steinvall, O

2000-08-20

Laser radar cross sections have been evaluated for a number of ideal targets such as cones, spheres, paraboloids, and cylinders by use of different reflection characteristics. The time-independent cross section is the ratio of the cross section of one of these forms to that of a plate with the same maximum radius. The time-dependent laser radar cross section involves the impulse response from the object shape multiplied by the beam's transverse profile and the surface bidirectional reflection distribution function. It can be clearly seen that knowledge of the combined effect of object shape and reflection characteristics is important for determining the shape and the magnitude of the laser radar return. The results of this study are of interest for many laser radar applications such as ranging, three-dimensional imaging-modeling, tracking, antisensor lasers, and target recognition.

Polarization differences in airborne ground penetrating radar performance for landmine detection

NASA Astrophysics Data System (ADS)

Dogaru, Traian; Le, Calvin

2016-05-01

The U.S. Army Research Laboratory (ARL) has investigated the ultra-wideband (UWB) radar technology for detection of landmines, improvised explosive devices and unexploded ordnance, for over two decades. This paper presents a phenomenological study of the radar signature of buried landmines in realistic environments and the performance of airborne synthetic aperture radar (SAR) in detecting these targets as a function of multiple parameters: polarization, depression angle, soil type and burial depth. The investigation is based on advanced computer models developed at ARL. The analysis includes both the signature of the targets of interest and the clutter produced by rough surface ground. Based on our numerical simulations, we conclude that low depression angles and H-H polarization offer the highest target-to-clutter ratio in the SAR images and therefore the best radar performance of all the scenarios investigated.

Calibration of complex polarimetric SAR imagery using backscatter correlations

NASA Technical Reports Server (NTRS)

Klein, Jeffrey D.

1992-01-01

A new technique for calibration of multipolarization synthetic aperture radar (SAR) imagery is described. If scatterer reciprocity and lack of correlation between co- and cross-polarized radar echoes (for azimuthally symmetric distributed targets) is assumed, the effects of signal leakage between the radar data channels can be removed without the use of known ground targets. If known targets are available, all data channels may be calibrated relative to one another and radiometrically as well. The method is verified with simulations and application to airborne SAR data.

The 3D laser radar vision processor system

NASA Astrophysics Data System (ADS)

Sebok, T. M.

1990-10-01

Loral Defense Systems (LDS) developed a 3D Laser Radar Vision Processor system capable of detecting, classifying, and identifying small mobile targets as well as larger fixed targets using three dimensional laser radar imagery for use with a robotic type system. This processor system is designed to interface with the NASA Johnson Space Center in-house Extra Vehicular Activity (EVA) Retriever robot program and provide to it needed information so it can fetch and grasp targets in a space-type scenario.

Radar Investigations of Asteroids

NASA Technical Reports Server (NTRS)

Ostro, S. J.

1984-01-01

Radar investigations of asteroids, including observations during 1984 to 1985 of at least 8 potential targets and continued analyses of radar data obtained during 1980 to 1984 for 30 other asteroids is proposed. The primary scientific objectives include estimation of echo strength, polarization, spectral shape, spectral bandwidth, and Doppler shift. These measurements yield estimates of target size, shape, and spin vector; place constraints on topography, morphology, density, and composition of the planetary surface; yield refined estimates of target orbital parameters; and reveals the presence of asteroidal satellites.

The 3D laser radar vision processor system

NASA Technical Reports Server (NTRS)

Sebok, T. M.

1990-01-01

Loral Defense Systems (LDS) developed a 3D Laser Radar Vision Processor system capable of detecting, classifying, and identifying small mobile targets as well as larger fixed targets using three dimensional laser radar imagery for use with a robotic type system. This processor system is designed to interface with the NASA Johnson Space Center in-house Extra Vehicular Activity (EVA) Retriever robot program and provide to it needed information so it can fetch and grasp targets in a space-type scenario.

Space Radar Image of Manaus, Brazil

NASA Image and Video Library

1999-01-27

These two images were created using data from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR). On the left is a false-color image of Manaus, Brazil acquired April 12, 1994, onboard space shuttle Endeavour. In the center of this image is the Solimoes River just west of Manaus before it combines with the Rio Negro to form the Amazon River. The scene is around 8 by 8 kilometers (5 by 5 miles) with north toward the top. The radar image was produced in L-band where red areas correspond to high backscatter at HH polarization, while green areas exhibit high backscatter at HV polarization. Blue areas show low backscatter at VV polarization. The image on the right is a classification map showing the extent of flooding beneath the forest canopy. The classification map was developed by SIR-C/X-SAR science team members at the University of California,Santa Barbara. The map uses the L-HH, L-HV, and L-VV images to classify the radar image into six categories: Red flooded forest Green unflooded tropical rain forest Blue open water, Amazon river Yellow unflooded fields, some floating grasses Gray flooded shrubs Black floating and flooded grasses Data like these help scientists evaluate flood damage on a global scale. Floods are highly episodic and much of the area inundated is often tree-covered. http://photojournal.jpl.nasa.gov/catalog/PIA01712

Radar waveform requirements for reliable detection of an aircraft-launched missile

NASA Astrophysics Data System (ADS)

Blair, W. Dale; Brandt-Pearce, Maite

1996-06-01

When tracking a manned aircraft with a phase array radar, detecting a missile launch (i.e., a target split) is particularly important because the missile can have a very small radar cross section (RCS) and drop below the horizon of the radar shortly after launch. Reliable detection of the launch is made difficult because the RCS of the missile is very small compared to that of the manned aircraft and the radar typically revisits a manned aircraft every few seconds. Furthermore, any measurements of the aircraft and missile taken shortly after the launch will be merged until the two targets are resolved in range, frequency, or space. In this paper, detection of the launched missile is addressed through the detection of the presence of target multiplicity with the in-phase and quadrature monopulse measurements. The probability of detecting the launch using monopulse processing will be studied with regard to the tracking signal-to-noise ratio and the number of pulses n the radar waveform.

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar.

PubMed

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-09-09

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar's estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method.

Joint synthetic aperture radar plus ground moving target indicator from single-channel radar using compressive sensing

DOEpatents

Thompson, Douglas; Hallquist, Aaron; Anderson, Hyrum

2017-10-17

The various embodiments presented herein relate to utilizing an operational single-channel radar to collect and process synthetic aperture radar (SAR) and ground moving target indicator (GMTI) imagery from a same set of radar returns. In an embodiment, data is collected by randomly staggering a slow-time pulse repetition interval (PRI) over a SAR aperture such that a number of transmitted pulses in the SAR aperture is preserved with respect to standard SAR, but many of the pulses are spaced very closely enabling movers (e.g., targets) to be resolved, wherein a relative velocity of the movers places them outside of the SAR ground patch. The various embodiments of image reconstruction can be based on compressed sensing inversion from undersampled data, which can be solved efficiently using such techniques as Bregman iteration. The various embodiments enable high-quality SAR reconstruction, and high-quality GMTI reconstruction from the same set of radar returns.

On the radar cross section (RCS) prediction of vehicles moving on the ground

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

Sabihi, Ahmad

2014-12-10

As readers should be aware, Radar Cross Section depends on the factors such as: Wave frequency and polarization, Target dimension, angle of ray incidence, Target’s material and covering, Type of radar system as monostatic or bistatic, space in which contains target and propagating waves, and etc. Having moved or stationed in vehicles can be effective in RCS values. Here, we investigate effective factors in RCS of moving targets on the ground or sea. Image theory in electromagnetic applies to be taken into account RCS of a target over the ground or sea.

Laser backscattered from partially convex targets of large sizes in random media for E-wave polarization.

PubMed

El-Ocla, Hosam

2006-08-01

The characteristics of a radar cross section (RCS) of partially convex targets with large sizes up to five wavelengths in free space and random media are studied. The nature of the incident wave is an important factor in remote sensing and radar detection applications. I investigate the effects of beam wave incidence on the performance of RCS, drawing on the method I used in a previous study on plane-wave incidence. A beam wave can be considered a plane wave if the target size is smaller than the beam width. Therefore, to have a beam wave with a limited spot on the target, the target size should be larger than the beam width (assuming E-wave incidence wave polarization. The effects of the target configuration, random medium parameters, and the beam width on the laser RCS and the enhancement in the radar cross section are numerically analyzed, resulting in the possibility of having some sort of control over radar detection using beam wave incidence.

New distributed radar technology based on UAV or UGV application

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo A.; Contarino, Vincent M.

2013-05-01

Regular micro and nano radars cannot provide reliable tracking of low altitude low profile aerial targets in urban and mountain areas because of reflection and re-reflections from buildings and terrain. They become visible and vulnerable to guided missiles if positioned on a tower or blimp. Doppler radar cannot distinguish moving cars and small low altitude aerial targets in an urban area. A new concept of pocket size distributed radar technology based on the application of UAV (Unmanned Air Vehicles), UGV (Unmanned Ground Vehicles) is proposed for tracking of low altitude low profile aerial targets at short and medium distances for protection of stadium, camp, military facility in urban or mountain areas.

A signature correlation study of ground target VHF/UHF ISAR imagery

NASA Astrophysics Data System (ADS)

Gatesman, Andrew J.; Beaudoin, Christopher J.; Giles, Robert H.; Kersey, William T.; Waldman, Jerry; Carter, Steve; Nixon, William E.

2003-09-01

VV and HH-polarized radar signatures of several ground targets were acquired in the VHF/UHF band (171-342 MHz) by using 1/35th scale models and an indoor radar range operating from 6 to 12 GHz. Data were processed into medianized radar cross sections as well as focused, ISAR imagery. Measurement validation was confirmed by comparing the radar cross section of a test object with a method of moments radar cross section prediction code. The signatures of several vehicles from three vehicle classes (tanks, trunks, and TELs) were measured and a signature cross-correlation study was performed. The VHF/UHF band is currently being exploited for its foliage penetration ability, however, the coarse image resolution which results from the relatively long radar wavelengths suggests a more challenging target recognition problem. One of the study's goals was to determine the amount of unique signature content in VHF/UHF ISAR imagery of military ground vehicles. Open-field signatures are compared with each other as well as with simplified shapes of similar size. Signatures were also acquired on one vehicle in a variety of configurations to determine the impact of monitor target variations on the signature content at these frequencies.

Buried landmine detection using multivariate normal clustering

NASA Astrophysics Data System (ADS)

Duston, Brian M.

2001-10-01

A Bayesian classification algorithm is presented for discriminating buried land mines from buried and surface clutter in Ground Penetrating Radar (GPR) signals. This algorithm is based on multivariate normal (MVN) clustering, where feature vectors are used to identify populations (clusters) of mines and clutter objects. The features are extracted from two-dimensional images created from ground penetrating radar scans. MVN clustering is used to determine the number of clusters in the data and to create probability density models for target and clutter populations, producing the MVN clustering classifier (MVNCC). The Bayesian Information Criteria (BIC) is used to evaluate each model to determine the number of clusters in the data. An extension of the MVNCC allows the model to adapt to local clutter distributions by treating each of the MVN cluster components as a Poisson process and adaptively estimating the intensity parameters. The algorithm is developed using data collected by the Mine Hunter/Killer Close-In Detector (MH/K CID) at prepared mine lanes. The Mine Hunter/Killer is a prototype mine detecting and neutralizing vehicle developed for the U.S. Army to clear roads of anti-tank mines.

Non-Cooperative Target Imaging and Parameter Estimation with Narrowband Radar Echoes.

PubMed

Yeh, Chun-mao; Zhou, Wei; Lu, Yao-bing; Yang, Jian

2016-01-20

This study focuses on the rotating target imaging and parameter estimation with narrowband radar echoes, which is essential for radar target recognition. First, a two-dimensional (2D) imaging model with narrowband echoes is established in this paper, and two images of the target are formed on the velocity-acceleration plane at two neighboring coherent processing intervals (CPIs). Then, the rotating velocity (RV) is proposed to be estimated by utilizing the relationship between the positions of the scattering centers among two images. Finally, the target image is rescaled to the range-cross-range plane with the estimated rotational parameter. The validity of the proposed approach is confirmed using numerical simulations.

Analysis of data acquired by synthetic aperture radar and LANDSAT Multispectral Scanner over Kershaw County, South Carolina, during the summer season

NASA Technical Reports Server (NTRS)

Wu, S. T.

1983-01-01

Data acquired by synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) were processed and analyzed to derive forest-related resources inventory information. The SAR data were acquired by using the NASA aircraft X-band SAR with linear (HH, VV) and cross (HV, VH) polarizations and the SEASAT L-band SAR. After data processing and data quality examination, the three polarization (HH, HV, and VV) data from the aircraft X-band SAR were used in conjunction with LANDSAT MSS for multisensor data classification. The results of accuracy evaluation for the SAR, MSS and SAR/MSS data using supervised classification show that the SAR-only data set contains low classification accuracy for several land cover classes. However, the SAR/MSS data show that significant improvement in classification accuracy is obtained for all eight land cover classes. These results suggest the usefulness of using combined SAR/MSS data for forest-related cover mapping. The SAR data also detect several small special surface features that are not detectable by MSS data.

G0-WISHART Distribution Based Classification from Polarimetric SAR Images

NASA Astrophysics Data System (ADS)

Hu, G. C.; Zhao, Q. H.

2017-09-01

Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

Compressive Sensing for Radar and Radar Sensor Networks

DTIC Science & Technology

2013-12-02

Zero Correlation Zone Sequence Pair Sets for MIMO Radar Inspired by recent advances in MIMO radar, we apply orthogonal phase coded waveforms to MIMO ...radar system in order to gain better range resolution and target direction finding performance [2]. We provide and investigate a generalized MIMO radar...ZCZ) sequence-Pair Set (ZCZPS). We also study the MIMO radar ambiguity function of the system using phase coded waveforms, based on which we analyze

Subsurface polarimetric migration imaging for full polarimetric ground-penetrating radar

NASA Astrophysics Data System (ADS)

Feng, Xuan; Yu, Yue; Liu, Cai; Fehler, Michael

2015-08-01

Polarization is a property of electromagnetic wave that generally refers to the locus of the electric field vector, which can be used to characterize surface properties by polarimetric radar. However, its use has been less common in the ground-penetrating radar (GPR) community. Full polarimetric GPR data include scattering matrices, by which the polarization properties can be extracted, at each survey point. Different components of the measured scattering matrix are sensitive to different types of subsurface objects, which offers a potential improvement in the detection ability of GPR. This paper develops a polarimetric migration imaging method. By merging the Pauli polarimetric decomposition technique with the Krichhoff migration equation, we develop a polarimetric migration algorithm, which can extract three migrated coefficients that are sensitive to different types of objects. Then fusing the three migrated coefficients, we can obtain subsurface colour-coded reconstructed object images, which can be employed to interpret both the geometrical information and the scattering mechanism of the subsurface objects. A 3-D full polarimetric GPR data set was acquired in a laboratory experiment and was used to test the method. In the laboratory experiment, four objects-a scatterer, a ball, a plate and a dihedral target-were buried in homogeneous dry sand under a flat ground surface. By merging the reconstructed image with polarization properties, we enhanced the subsurface image and improved the classification ability of GPR.

Measurements of the radar cross section and Inverse Synthetic Aperture Radar (ISAR) images of a Piper Navajo at 9.5 GHz and 49 GHz

NASA Astrophysics Data System (ADS)

Dinger, R.; Kinzel, G.; Lam, W.; Jones, S.

1993-01-01

Studies were conducted of the enhanced radar cross section (RCS) and improved inverse synthetic aperture radar (ISAR) image quality that may result at millimeter-wave (mmw) frequencies. To study the potential for mmw radar in these areas, a program was initiated in FY-90 to design and fabricate a 49.0- to 49.5-GHz stepped-frequency radar. After conducting simultaneous measurements of the RCS of an airborne Piper Navajo twin-engine aircraft at 9.0 and 49.0 GHz, the RCS at 49.0 GHz was always found to be higher than at 9.0 GHz by an amount that depended on the target aspect angle. The largest increase was 19 dB and was measured at nose-on incidence; at other angles of incidence, the increase ranged from 3 to 10 dB. The increase averaged over a 360-degree aspect-angle change was 7.2 dB. The 49.0-GHz radar has demonstrated a capability to gather well-calibrated millimeter-wave RCS data of flying targets. In addition, the successful ISAR images obtainable with short aperture time suggest that 49.0-GHz radar may have a role to play in noncooperative target identification (NCTI).

How to Create and Manipulate Radar Range-Doppler Plots

DTIC Science & Technology

2014-12-01

the radar interacts, we can then also simulate jamming it to produce false targets. We start by setting up the relevant radar equations that allow the...radar at r = 0 for the duration of the scenario, with the target at r = r0 at t = 0. To facilitate later discussion, suppose that t = 0 starts a coherent...interval. The time from the start of one pulse to the next is 100 µs, so that t ≃ 32×100µs. The range difference vtd/2 is then, making use of SI units, vtd

Radar observation of known and unknown clear echoes

NASA Technical Reports Server (NTRS)

Glover, K. M.; Konrad, T. G.

1979-01-01

Target cross-section as a function of wavelength for known insects, known bird, and dot targets is presented. Tracking data using the time series analysis was tabulated for known birds. Examples were selected from these early works to give entomologists some indication of the types of information that are available by radar as well as examples of the different sources of clear-air radar backscatter.

VHF/UHF imagery and RCS measurements of ground targets in forested terrain

NASA Astrophysics Data System (ADS)

Gatesman, Andrew J.; Beaudoin, Christopher J.; Giles, Robert H.; Waldman, Jerry; Nixon, William E.

2002-08-01

The monostatic VV and HH-polarized radar signatures of several targets and trees have been measured at foliage penetration frequencies (VHF/UHF) by using 1/35th scale models and an indoor radar range operating at X-band. An array of high-fidelity scale model ground vehicles and test objects as well as scaled ground terrain and trees have been fabricated for the study. Radar measurement accuracy has been confirmed by comparing the signature of a test object with a method of moments radar cross section prediction code. In addition to acquiring signatures of targets located on a smooth, dielectric ground plane, data have also been acquired with targets located in simulated wooded terrain that included scaled tree trunks and tree branches. In order to assure the correct backscattering behavior, all dielectric properties of live tree wood and moist soil were scaled properly to match the complex dielectric constant of the full-scale materials. The impact of the surrounding tree clutter on the VHF/UHF radar signatures of ground vehicles was accessed. Data were processed into high-resolution, polar-formatted ISAR imagery and signature comparisons are made between targets in open-field and forested scenarios.

Gesture recognition for smart home applications using portable radar sensors.

PubMed

Wan, Qian; Li, Yiran; Li, Changzhi; Pal, Ranadip

2014-01-01

In this article, we consider the design of a human gesture recognition system based on pattern recognition of signatures from a portable smart radar sensor. Powered by AAA batteries, the smart radar sensor operates in the 2.4 GHz industrial, scientific and medical (ISM) band. We analyzed the feature space using principle components and application-specific time and frequency domain features extracted from radar signals for two different sets of gestures. We illustrate that a nearest neighbor based classifier can achieve greater than 95% accuracy for multi class classification using 10 fold cross validation when features are extracted based on magnitude differences and Doppler shifts as compared to features extracted through orthogonal transformations. The reported results illustrate the potential of intelligent radars integrated with a pattern recognition system for high accuracy smart home and health monitoring purposes.

Attention-Based Recurrent Temporal Restricted Boltzmann Machine for Radar High Resolution Range Profile Sequence Recognition.

PubMed

Zhang, Yifan; Gao, Xunzhang; Peng, Xuan; Ye, Jiaqi; Li, Xiang

2018-05-16

The High Resolution Range Profile (HRRP) recognition has attracted great concern in the field of Radar Automatic Target Recognition (RATR). However, traditional HRRP recognition methods failed to model high dimensional sequential data efficiently and have a poor anti-noise ability. To deal with these problems, a novel stochastic neural network model named Attention-based Recurrent Temporal Restricted Boltzmann Machine (ARTRBM) is proposed in this paper. RTRBM is utilized to extract discriminative features and the attention mechanism is adopted to select major features. RTRBM is efficient to model high dimensional HRRP sequences because it can extract the information of temporal and spatial correlation between adjacent HRRPs. The attention mechanism is used in sequential data recognition tasks including machine translation and relation classification, which makes the model pay more attention to the major features of recognition. Therefore, the combination of RTRBM and the attention mechanism makes our model effective for extracting more internal related features and choose the important parts of the extracted features. Additionally, the model performs well with the noise corrupted HRRP data. Experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that our proposed model outperforms other traditional methods, which indicates that ARTRBM extracts, selects, and utilizes the correlation information between adjacent HRRPs effectively and is suitable for high dimensional data or noise corrupted data.

Indoor imagery with a 3D through-wall synthetic aperture radar

NASA Astrophysics Data System (ADS)

Sévigny, Pascale; DiFilippo, David J.; Laneve, Tony; Fournier, Jonathan

2012-06-01

Through-wall radar imaging is an emerging technology with great interest to military and police forces operating in an urban environment. A through-wall imaging radar can potentially provide interior room layouts as well as detection and localization of targets of interest within a building. In this paper, we present our through-wall radar system mounted on the side of a vehicle and driven along a path in front of a building of interest. The vehicle is equipped with a LIDAR (Light Detection and Ranging) and motion sensors that provide auxiliary information. The radar uses an ultra wideband frequency-modulated continuous wave (FMCW) waveform to obtain high range resolution. Our system is composed of a vertical linear receive array to discriminate targets in elevation, and two transmit elements operated in a slow multiple-input multiple output (MIMO) configuration to increase the achievable elevation resolution. High resolution in the along-track direction is obtained through synthetic aperture radar (SAR) techniques. We present experimental results that demonstrate the 3-D capability of the radar. We further demonstrate target detection behind challenging walls, and imagery of internal wall features. Finally, we discuss future work.

Invariant-feature-based adaptive automatic target recognition in obscured 3D point clouds

NASA Astrophysics Data System (ADS)

Khuon, Timothy; Kershner, Charles; Mattei, Enrico; Alverio, Arnel; Rand, Robert

2014-06-01

Target recognition and classification in a 3D point cloud is a non-trivial process due to the nature of the data collected from a sensor system. The signal can be corrupted by noise from the environment, electronic system, A/D converter, etc. Therefore, an adaptive system with a desired tolerance is required to perform classification and recognition optimally. The feature-based pattern recognition algorithm architecture as described below is particularly devised for solving a single-sensor classification non-parametrically. Feature set is extracted from an input point cloud, normalized, and classifier a neural network classifier. For instance, automatic target recognition in an urban area would require different feature sets from one in a dense foliage area. The figure above (see manuscript) illustrates the architecture of the feature based adaptive signature extraction of 3D point cloud including LIDAR, RADAR, and electro-optical data. This network takes a 3D cluster and classifies it into a specific class. The algorithm is a supervised and adaptive classifier with two modes: the training mode and the performing mode. For the training mode, a number of novel patterns are selected from actual or artificial data. A particular 3D cluster is input to the network as shown above for the decision class output. The network consists of three sequential functional modules. The first module is for feature extraction that extracts the input cluster into a set of singular value features or feature vector. Then the feature vector is input into the feature normalization module to normalize and balance it before being fed to the neural net classifier for the classification. The neural net can be trained by actual or artificial novel data until each trained output reaches the declared output within the defined tolerance. In case new novel data is added after the neural net has been learned, the training is then resumed until the neural net has incrementally learned with the new novel data. The associative memory capability of the neural net enables the incremental learning. The back propagation algorithm or support vector machine can be utilized for the classification and recognition.

In Situ Verification of the NASA D3R's Hydrometeor Classification and Rainfall Products during the OLYMPEx Field Campaign

NASA Astrophysics Data System (ADS)

Chen, H.; Chandra, C. V.

2017-12-01

As a ground validation (GV) radar for the Global Precipitation Measurement (GPM) satellite mission, the NASA dual-frequency, dual-polarization, Doppler radar (D3R) was deployed just north of Pacific Beach, WA between November 8th, 2015 and January 15th, 2016, as part of the Olympic Mountains Experiment (OLYMPEx). The D3R's observations were coordinated with a diverse array of instruments including the NASA NPOL S-band radar, Autonomous Parsivel Unit (APU) disdrometers, rain gauges, and airborne probe. The Ku- and Ka-band D3R is analogous to the GPM core satellite dual-frequency precipitation radar (DPR), but can provide more detailed insight into the precipitation microphysics through the ground-based dual-frequency dual-polarization observations. Previous studies have revealed that the dual polarization radar can be used to identify different hydrometeor types and their size and shape information. However, most of the previous studies are devoted to S-, C-, and/or X-band frequencies since they are standard operating frequency in many countries. This paper presents a region-based hydrometeor classification methodology applied for the NASA D3R measurements collected during OLYMPEx. This paper also details the differential phase based attenuation correction methodology and rainfall algorithm developed for the D3R. The D3R's hydrometeor classification and rainfall products are evaluated using other remote sensors and in situ measurements. In particular, the derived hydrometeor types are cross compared with collocated S-band products and images collected by the airborne probe. The rainfall performance are assessed using rain gauge and disdrometer observations. Results show that the NASA D3R has great potential for monitoring precipitation microphysics and rainfall estimation, especially light rainfall that is hard to be observed by traditional ground or space based sensors.

Remote Sensing and Wetland Ecology: a South African Case Study.

PubMed

De Roeck, Els R; Verhoest, Niko E C; Miya, Mtemi H; Lievens, Hans; Batelaan, Okke; Thomas, Abraham; Brendonck, Luc

2008-05-26

Remote sensing offers a cost efficient means for identifying and monitoring wetlands over a large area and at different moments in time. In this study, we aim at providing ecologically relevant information on characteristics of temporary and permanent isolated open water wetlands, obtained by standard techniques and relatively cheap imagery. The number, surface area, nearest distance, and dynamics of isolated temporary and permanent wetlands were determined for the Western Cape, South Africa. Open water bodies (wetlands) were mapped from seven Landsat images (acquired during 1987 - 2002) using supervised maximum likelihood classification. The number of wetlands fluctuated over time. Most wetlands were detected in the winter of 2000 and 2002, probably related to road constructions. Imagery acquired in summer contained fewer wetlands than in winter. Most wetlands identified from Landsat images were smaller than one hectare. The average distance to the nearest wetland was larger in summer. In comparison to temporary wetlands, fewer, but larger permanent wetlands were detected. In addition, classification of non-vegetated wetlands on an Envisat ASAR radar image (acquired in June 2005) was evaluated. The number of detected small wetlands was lower for radar imagery than optical imagery (acquired in June 2002), probably because of deterioration of the spatial information content due the extensive pre-processing requirements of the radar image. Both optical and radar classifications allow to assess wetland characteristics that potentially influence plant and animal metacommunity structure. Envisat imagery, however, was less suitable than Landsat imagery for the extraction of detailed ecological information, as only large wetlands can be detected. This study has indicated that ecologically relevant data can be generated for the larger wetlands through relatively cheap imagery and standard techniques, despite the relatively low resolution of Landsat and Envisat imagery. For the characterisation of very small wetlands, high spatial resolution optical or radar images are needed. This study exemplifies the benefits of integrating remote sensing and ecology and hence stimulates interdisciplinary research of isolated wetlands.

Study to investigate and evaluate means of optimizing the radar function for the space shuttle

NASA Technical Reports Server (NTRS)

1976-01-01

A detailed analysis of the spiral scan was performed for antenna sizes ranging from 20 inches to 36 inches in diameter and for search angles characteristic of both the radar and the communication acquisition modes. The power budgets for passive target radar detection were calculated for antenna diameters ranging from 20 to 36 inches. Dwell times commensurate with spiral scan were used for these budget calculations. The signal design for the candidate pulse Doppler system is summarized. Ground return analysis carried out for the passive target radar mode is examined, and the details are presented. A concluding description of the proposed candidate radar/communication system configuration is given.

Birds and insects as radar targets - A review

NASA Technical Reports Server (NTRS)

Vaughn, C. R.

1985-01-01

A review of radar cross-section measurements of birds and insects is presented. A brief discussion of some possible theoretical models is also given and comparisons made with the measurements. The comparisons suggest that most targets are, at present, better modeled by a prolate spheroid having a length-to-width ratio between 3 and 10 than by the often used equivalent weight water sphere. In addition, many targets observed with linear horizontal polarization have maximum cross sections much better estimated by a resonant half-wave dipole than by a water sphere. Also considered are birds and insects in the aggregate as a local radar 'clutter' source. Order-of-magnitude estimates are given for many reasonable target number densities. These estimates are then used to predict X-band volume reflectivities. Other topics that are of interest to the radar engineer are discussed, including the doppler bandwidth due to the internal motions of a single bird, the radar cross-section probability densities of single birds and insects, the variability of the functional form of the probability density functions, and the Fourier spectra of single birds and insects.

Radar fall detection using principal component analysis

NASA Astrophysics Data System (ADS)

Jokanovic, Branka; Amin, Moeness; Ahmad, Fauzia; Boashash, Boualem

2016-05-01

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.

Synchronized Radar-Target Simulator

NASA Technical Reports Server (NTRS)

Chin, B. C.

1985-01-01

Apparatus for testing radar system generates signals that simulate amplitude and phase characteristics of target returns and their variation with antenna-pointing direction. Antenna movement causes equipment to alter test signal in imitation of behavior of real signal received during tracking.

Current test results for the Athena radar responsive tag

NASA Astrophysics Data System (ADS)

Ormesher, Richard C.; Martinez, Ana; Plummer, Kenneth W.; Erlandson, David; Delaware, Sheri; Clark, David R.

2006-05-01

Sandia National Laboratories has teamed with General Atomics and Sierra Monolithics to develop the Athena tag for the Army's Radar Tag Engagement (RaTE) program. The radar-responsive Athena tag can be used for Blue Force tracking and Combat Identification (CID) as well as data collection, identification, and geolocation applications. The Athena tag is small (~4.5" x 2.4" x 4.2"), battery-powered, and has an integral antenna. Once remotely activated by a Synthetic Aperture Radar (SAR) or Moving Target Indicator (MTI) radar, the tag transponds modulated pulses to the radar at a low transmit power. The Athena tag can operate Ku-band and X-band airborne SAR and MTI radars. This paper presents results from current tag development testing activities. Topics covered include recent field tests results from the AN/APY-8 Lynx, F16/APG-66, and F15E/APG-63 V(1) radars and other Fire Control radars. Results show that the Athena tag successfully works with multiple radar platforms, in multiple radar modes, and for multiple applications. Radar-responsive tags such as Athena have numerous applications in military and government arenas. Military applications include battlefield situational awareness, combat identification, targeting, personnel recovery, and unattended ground sensors. Government applications exist in nonproliferation, counter-drug, search-and-rescue, and land-mapping activities.

Compressed Sensing in On-Grid MIMO Radar.

PubMed

Minner, Michael F

2015-01-01

The accurate detection of targets is a significant problem in multiple-input multiple-output (MIMO) radar. Recent advances of Compressive Sensing offer a means of efficiently accomplishing this task. The sparsity constraints needed to apply the techniques of Compressive Sensing to problems in radar systems have led to discretizations of the target scene in various domains, such as azimuth, time delay, and Doppler. Building upon recent work, we investigate the feasibility of on-grid Compressive Sensing-based MIMO radar via a threefold azimuth-delay-Doppler discretization for target detection and parameter estimation. We utilize a colocated random sensor array and transmit distinct linear chirps to a small scene with few, slowly moving targets. Relying upon standard far-field and narrowband assumptions, we analyze the efficacy of various recovery algorithms in determining the parameters of the scene through numerical simulations, with particular focus on the ℓ 1-squared Nonnegative Regularization method.

Target deception jamming method against spaceborne synthetic aperture radar using electromagnetic scattering

NASA Astrophysics Data System (ADS)

Sun, Qingyang; Shu, Ting; Tang, Bin; Yu, Wenxian

2018-01-01

A method is proposed to perform target deception jamming against spaceborne synthetic aperture radar. Compared with the traditional jamming methods using deception templates to cover the target or region of interest, the proposed method aims to generate a verisimilar deceptive target in various attitude with high fidelity using the electromagnetic (EM) scattering. Based on the geometrical model for target deception jamming, the EM scattering data from the deceptive target was first simulated by applying an EM calculation software. Then, the proposed jamming frequency response (JFR) is calculated offline by further processing. Finally, the deception jamming is achieved in real time by a multiplication between the proposed JFR and the spectrum of intercepted radar signals. The practical implementation is presented. The simulation results prove the validity of the proposed method.

An algorithm for automatic target recognition using passive radar and an EKF for estimating aircraft orientation

NASA Astrophysics Data System (ADS)

Ehrman, Lisa M.

2005-07-01

Rather than emitting pulses, passive radar systems rely on "illuminators of opportunity," such as TV and FM radio, to illuminate potential targets. These systems are attractive since they allow receivers to operate without emitting energy, rendering them covert. Until recently, most of the research regarding passive radar has focused on detecting and tracking targets. This dissertation focuses on extending the capabilities of passive radar systems to include automatic target recognition. The target recognition algorithm described in this dissertation uses the radar cross section (RCS) of potential targets, collected over a short period of time, as the key information for target recognition. To make the simulated RCS as accurate as possible, the received signal model accounts for aircraft position and orientation, propagation losses, and antenna gain patterns. An extended Kalman filter (EKF) estimates the target's orientation (and uncertainty in the estimate) from velocity measurements obtained from the passive radar tracker. Coupling the aircraft orientation and state with the known antenna locations permits computation of the incident and observed azimuth and elevation angles. The Fast Illinois Solver Code (FISC) simulates the RCS of potential target classes as a function of these angles. Thus, the approximated incident and observed angles allow the appropriate RCS to be extracted from a database of FISC results. Using this process, the RCS of each aircraft in the target class is simulated as though each is executing the same maneuver as the target detected by the system. Two additional scaling processes are required to transform the RCS into a power profile (magnitude only) simulating the signal in the receiver. First, the RCS is scaled by the Advanced Refractive Effects Prediction System (AREPS) code to account for propagation losses that occur as functions of altitude and range. Then, the Numerical Electromagnetic Code (NEC2) computes the antenna gain pattern, further scaling the RCS. A Rician likelihood model compares the scaled RCS of the illuminated aircraft with those of the potential targets. To improve the robustness of the result, the algorithm jointly optimizes over feasible orientation profiles and target types via dynamic programming.

Measurement level AIS/radar fusion for maritime surveillance

NASA Astrophysics Data System (ADS)

Habtemariam, Biruk K.; Tharmarasa, R.; Meger, Eric; Kirubarajan, T.

2012-05-01

Using the Automatic Identification System (AIS) ships identify themselves intermittently by broadcasting their location information. However, traditionally radars are used as the primary source of surveillance and AIS is considered as a supplement with a little interaction between these data sets. The data from AIS is much more accurate than radar data with practically no false alarms. But unlike the radar data, the AIS measurements arrive unpredictably, depending on the type and behavior of a ship. The AIS data includes target IDs that can be associated to initialized tracks. In multitarget maritime surveillance environment, for some targets the revisit interval form the AIS could be very large. In addition, the revisit intervals for various targets can be different. In this paper, we proposed a joint probabilistic data association based tracking algorithm that addresses the aforementioned issues to fuse the radar measurements with AIS data. Multiple AIS IDs are assigned to a track, with probabilities updated by both AIS and radar measurements to resolve the ambiguity in the AIS ID source. Experimental results based on simulated data demonstrate the performance the proposed technique.

Lithologic discrimination of volcanic and sedimentary rocks by spectral examination of Landsat TM data from the Puma, Central Andes Mountains

NASA Technical Reports Server (NTRS)

Fielding, E. J.

1986-01-01

The Central Andes are widely used as a modern example of noncollisional mountain-building processes. The Puna is a high plateau in the Chilean and Argentine Central Andes extending southward from the altiplano of Bolivia and Peru. Young tectonic and volcanic features are well exposed on the surface of the arid Puna, making them prime targets for the application of high-resolution space imagery such as Shuttle Imaging Radar B and Landsat Thematic Mapper (TM). Two TM scene quadrants from this area are analyzed using interactive color image processing, examination, and automated classification algorithms. The large volumes of these high-resolution datasets require significantly different techniques than have been used previously for the interpretation of Landsat MSS data. Preliminary results include the determination of the radiance spectra of several volcanic and sedimentary rock units and the use of the spectra for automated classification. Structural interpretations have revealed several previously unknown folds in late Tertiary strata, and key zones have been targeted to be investigated in the field. The synoptic view of space imagery is already filling a critical gap between low-resolution geophysical data and traditional geologic field mapping in the reconnaissance study of poorly mapped mountain frontiers such as the Puna.

Assessment of UWB radar for improvised explosive device detection

NASA Astrophysics Data System (ADS)

Kegege, Obadiah; Li, Junfei; Foltz, Heinrich

2006-05-01

The goal of our research is to assess the capability of ultra-wide-band (UWB) radar for detection of roadside improvised explosive devices (IEDs). Radar scattering signatures of artillery shells over a broadband frequency range, with different Tx/Rx polarizations, and at various aspect angles have been explored based on simulation and indoor measurement. Characteristics of IEDs versus clutter, wave penetration at different frequencies are also investigated. Finally, visibility of IED targets is tested on a moving cart in outdoor settings, with IED targets on ground surface, recessed, and buried underground at different distances away from the radar.

Fusion of radar and satellite target measurements

NASA Astrophysics Data System (ADS)

Moy, Gabriel; Blaty, Donald; Farber, Morton; Nealy, Carlton

2011-06-01

A potentially high payoff for the ballistic missile defense system (BMDS) is the ability to fuse the information gathered by various sensor systems. In particular, it may be valuable in the future to fuse measurements made using ground based radars with passive measurements obtained from satellite-based EO/IR sensors. This task can be challenging in a multitarget environment in view of the widely differing resolution between active ground-based radar and an observation made by a sensor at long range from a satellite platform. Additionally, each sensor system could have a residual pointing bias which has not been calibrated out. The problem is further compounded by the possibility that an EO/IR sensor may not see exactly the same set of targets as a microwave radar. In order to better understand the problems involved in performing the fusion of metric information from EO/IR satellite measurements with active microwave radar measurements, we have undertaken a study of this data fusion issue and of the associated data processing techniques. To carry out this analysis, we have made use of high fidelity simulations to model the radar observations from a missile target and the observations of the same simulated target, as gathered by a constellation of satellites. In the paper, we discuss the improvements seen in our tests when fusing the state vectors, along with the improvements in sensor bias estimation. The limitations in performance due to the differing phenomenology between IR and microwave radar are discussed as well.

Photonics-based real-time ultra-high-range-resolution radar with broadband signal generation and processing.

PubMed

Zhang, Fangzheng; Guo, Qingshui; Pan, Shilong

2017-10-23

Real-time and high-resolution target detection is highly desirable in modern radar applications. Electronic techniques have encountered grave difficulties in the development of such radars, which strictly rely on a large instantaneous bandwidth. In this article, a photonics-based real-time high-range-resolution radar is proposed with optical generation and processing of broadband linear frequency modulation (LFM) signals. A broadband LFM signal is generated in the transmitter by photonic frequency quadrupling, and the received echo is de-chirped to a low frequency signal by photonic frequency mixing. The system can operate at a high frequency and a large bandwidth while enabling real-time processing by low-speed analog-to-digital conversion and digital signal processing. A conceptual radar is established. Real-time processing of an 8-GHz LFM signal is achieved with a sampling rate of 500 MSa/s. Accurate distance measurement is implemented with a maximum error of 4 mm within a range of ~3.5 meters. Detection of two targets is demonstrated with a range-resolution as high as 1.875 cm. We believe the proposed radar architecture is a reliable solution to overcome the limitations of current radar on operation bandwidth and processing speed, and it is hopefully to be used in future radars for real-time and high-resolution target detection and imaging.

Performance Analysis for Joint Target Parameter Estimation in UMTS-Based Passive Multistatic Radar with Antenna Arrays Using Modified Cramér-Rao Lower Bounds.

PubMed

Shi, Chenguang; Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-10-18

In this study, the modified Cramér-Rao lower bounds (MCRLBs) on the joint estimation of target position and velocity is investigated for a universal mobile telecommunication system (UMTS)-based passive multistatic radar system with antenna arrays. First, we analyze the log-likelihood redfunction of the received signal for a complex Gaussian extended target. Then, due to the non-deterministic transmitted data symbols, the analytically closed-form expressions of the MCRLBs on the Cartesian coordinates of target position and velocity are derived for a multistatic radar system with N t UMTS-based transmit station of L t antenna elements and N r receive stations of L r antenna elements. With the aid of numerical simulations, it is shown that increasing the number of receiving elements in each receive station can reduce the estimation errors. In addition, it is demonstrated that the MCRLB is not only a function of signal-to-noise ratio (SNR), the number of receiving antenna elements and the properties of the transmitted UMTS signals, but also a function of the relative geometric configuration between the target and the multistatic radar system.The analytical expressions for MCRLB will open up a new dimension for passive multistatic radar system by aiding the optimal placement of receive stations to improve the target parameter estimation performance.

Performance Analysis for Joint Target Parameter Estimation in UMTS-Based Passive Multistatic Radar with Antenna Arrays Using Modified Cramér-Rao Lower Bounds

PubMed Central

Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-01-01

In this study, the modified Cramér-Rao lower bounds (MCRLBs) on the joint estimation of target position and velocity is investigated for a universal mobile telecommunication system (UMTS)-based passive multistatic radar system with antenna arrays. First, we analyze the log-likelihood redfunction of the received signal for a complex Gaussian extended target. Then, due to the non-deterministic transmitted data symbols, the analytically closed-form expressions of the MCRLBs on the Cartesian coordinates of target position and velocity are derived for a multistatic radar system with Nt UMTS-based transmit station of Lt antenna elements and Nr receive stations of Lr antenna elements. With the aid of numerical simulations, it is shown that increasing the number of receiving elements in each receive station can reduce the estimation errors. In addition, it is demonstrated that the MCRLB is not only a function of signal-to-noise ratio (SNR), the number of receiving antenna elements and the properties of the transmitted UMTS signals, but also a function of the relative geometric configuration between the target and the multistatic radar system.The analytical expressions for MCRLB will open up a new dimension for passive multistatic radar system by aiding the optimal placement of receive stations to improve the target parameter estimation performance. PMID:29057805

UAVSAR Program: Initial Results from New Instrument Capabilities

NASA Technical Reports Server (NTRS)

Lou, Yunling; Hensley, Scott; Moghaddam, Mahta; Moller, Delwyn; Chapin, Elaine; Chau, Alexandra; Clark, Duane; Hawkins, Brian; Jones, Cathleen; Marks, Phillip;

Hybrid Radar Emitter Recognition Based on Rough k-Means Classifier and Relevance Vector Machine

PubMed Central

Yang, Zhutian; Wu, Zhilu; Yin, Zhendong; Quan, Taifan; Sun, Hongjian

2013-01-01

Due to the increasing complexity of electromagnetic signals, there exists a significant challenge for recognizing radar emitter signals. In this paper, a hybrid recognition approach is presented that classifies radar emitter signals by exploiting the different separability of samples. The proposed approach comprises two steps, namely the primary signal recognition and the advanced signal recognition. In the former step, a novel rough k-means classifier, which comprises three regions, i.e., certain area, rough area and uncertain area, is proposed to cluster the samples of radar emitter signals. In the latter step, the samples within the rough boundary are used to train the relevance vector machine (RVM). Then RVM is used to recognize the samples in the uncertain area; therefore, the classification accuracy is improved. Simulation results show that, for recognizing radar emitter signals, the proposed hybrid recognition approach is more accurate, and presents lower computational complexity than traditional approaches. PMID:23344380

Synthetic-Aperture Coherent Imaging From A Circular Path

NASA Technical Reports Server (NTRS)

Jin, Michael Y.

1995-01-01

Imaging algorithms based on exact point-target responses. Developed for use in reconstructing image of target from data gathered by radar, sonar, or other transmitting/receiving coherent-signal sensory apparatus following circular observation path around target. Potential applications include: Wide-beam synthetic-aperture radar (SAR) from aboard spacecraft in circular orbit around target planet; SAR from aboard airplane flying circular course at constant elevation around central ground point, toward which spotlight radar beam pointed; Ultrasonic reflection tomography in medical setting, using one transducer moving in circle around patient or else multiple transducers at fixed positions on circle around patient; and Sonar imaging of sea floor to high resolution, without need for large sensory apparatus.

Calibration of a polarimetric imaging SAR

NASA Technical Reports Server (NTRS)

Sarabandi, K.; Pierce, L. E.; Ulaby, F. T.

1991-01-01

Calibration of polarimetric imaging Synthetic Aperture Radars (SAR's) using point calibration targets is discussed. The four-port network calibration technique is used to describe the radar error model. The polarimetric ambiguity function of the SAR is then found using a single point target, namely a trihedral corner reflector. Based on this, an estimate for the backscattering coefficient of the terrain is found by a deconvolution process. A radar image taken by the JPL Airborne SAR (AIRSAR) is used for verification of the deconvolution calibration method. The calibrated responses of point targets in the image are compared both with theory and the POLCAL technique. Also, response of a distributed target are compared using the deconvolution and POLCAL techniques.

Determination of rain rate from a spaceborne radar using measurements of total attenuation

NASA Technical Reports Server (NTRS)

Meneghini, R.; Eckerman, J.; Atlas, D.

1981-01-01

Studies shows that path-integrated rain rates can be determined by means of a direct measurement of attenuation. For ground based radars this is done by measuring the backscattering cross section of a fixed target in the presence and absence of rain along the radar beam. A ratio of the two measurements yields a factor proportional to the attenuation from which the average rain rate is deduced. The technique is extended to spaceborne radars by choosing the ground as reference target. The technique is also generalized so that both the average and range-profiled rain rates are determined. The accuracies of the resulting estimates are evaluated for a narrow beam radar located on a low earth orbiting satellite.

Joint Filter and Waveform Design for Radar STAP in Signal Dependent Interference (Preprint)

DTIC Science & Technology

2015-10-01

scheduling for extended targets in radar using information theoretic measures , tracking etc can be seen in [45]–[50], [51]–[56], and the references...range gate, the measured snapshot vector consists of the target returns and the undesired returns, i.e. clutter returns, interference and noise. The...D. Cochran, S. Suvorova, S. Howard, and W. Moran, “Waveform libraries: Measures of effectiveness for radar scheduling,” IEEE Signal Processing

Synergy between Sentinel-1 radar time series and Sentinel-2 optical for the mapping of restored areas in Danube delta

NASA Astrophysics Data System (ADS)

Niculescu, Simona; Lardeux, Cédric; Hanganu, Jenica

2018-05-01

Wetlands are important and valuable ecosystems, yet, since 1900, more than 50 % of wetlands have been lost worldwide. An example of altered and partially restored coastal wetlands is the Danube Delta in Romania. Over time, human intervention has manifested itself in more than a quarter of the entire Danube surface. This intervention was brutal and has rendered ecosystem restoration very difficult. Studies for the rehabilitation / re-vegetation were started immediately after the Danube Delta was declared as a Biosphere Reservation in 1990. Remote sensing offers accurate methods for detecting and mapping change in restored wetlands. Vegetation change detection is a powerful indicator of restoration success. The restoration projects use vegetative cover as an important indicator of restoration success. To follow the evolution of the vegetation cover of the restored areas, satellite images radar and optical of last generation have been used, such as Sentinel-1 and Sentinel-2. Indeed the sensor sensitivity to the landscape depends on the wavelength what- ever radar or optical data and their polarization for radar data. Combining this kind of data is particularly relevant for the classification of wetland vegetation, which are associated with the density and size of the vegetation. In addition, the high temporal acquisition frequency of Sentinel-1 which are not sensitive to cloud cover al- low to use temporal signature of the different land cover. Thus we analyse the polarimetric and temporal signature of Sentinel-1 data in order to better understand the signature of the different study classes. In a second phase, we performed classifications based on the Random Forest supervised classification algorithm involving the entire Sentinel-1 time series, then starting from a Sentinel-2 collection and finally involving combinations of Sentinel-1 and -2 data.

A radar survey of M- and X-class asteroids II. Summary and synthesis

NASA Astrophysics Data System (ADS)

Shepard, Michael K.; Clark, Beth Ellen; Ockert-Bell, Maureen; Nolan, Michael C.; Howell, Ellen S.; Magri, Christopher; Giorgini, Jon D.; Benner, Lance A. M.; Ostro, Steven J.; Harris, Alan W.; Warner, Brian D.; Stephens, Robert D.; Mueller, Michael

2010-07-01

Using the S-band radar at Arecibo Observatory, we observed six new M-class main-belt asteroids (MBAs), and re-observed one, bringing the total number of Tholen M-class asteroids observed with radar to 19. The mean radar albedo for all our targets is σ=0.28±0.13, significantly higher than the mean radar albedo of every other class (Magri, C., Nolan, M.C., Ostro, S.J., Giorgini, J.D. [2007]. Icarus 186, 126-151). Seven of these objects (Asteroids 16 Psyche, 129 Antigone, 216 Kleopatra, 347 Pariana, 758 Mancunia, 779 Nina, 785 Zwetana) have radar albedos indicative of a very high metal content (meanσ=0.41±0.13), and consistent with a remnant iron/nickel core interpretation (irons) or exotic high metal meteorite types such as CB. We propose designating these high radar albedo objects as Mm. Two asteroids, 110 Lydia and 678 Fredegundis, have more moderate radar albedos (meanσ=0.22), but exhibit high values (σ˜0.35) at some rotation phases suggesting a significant metal content. The remaining 10 objects have moderate radar albedos (σ=0.20±0.06) at all rotation phases. Most of our targets have visible/near-infrared spectra (Hardersen, P.S., Gaffey, M.J., Abell, P.A. [2005]. Icarus 175, 141-158; Fornasier, S., Clark, B.E., Dotto, E., Migliorini, A., Ockert-Bell, M., Barucci, M.A. [2009]. Icarus, submitted for publication) that indicate the presence of at least some silicate phases. All of the non-Mm asteroids show a positive correlation between visual and radar albedo but the reasons for this are not clear. All of the higher radar albedo targets (the 7 Mm asteroids, Lydia, and Fredegundis) show moderate to large variations in radar albedo with rotation phase. We suggest that their high radar reflectivity exaggerates irregularities in the asteroid shape to cause this behavior. One-third of our targets show evidence for asteroid-scale concavities or bifurcation. Based on all the evidence available, we suggest that most Tholen M-class asteroids are not remnant iron cores or enstatite chondrites, but rather collisional composites of silicates and irons with compositions more analogous to stony-iron meteorites and high-iron carbonaceous chondrites.

Application of SEASAT-1 Synthetic Aperture Radar (SAR) data to enhance and detect geological lineaments and to assist LANDSAT landcover classification mapping. [Appalachian Region, West Virginia

NASA Technical Reports Server (NTRS)

Sekhon, R.

1981-01-01

Digital SEASAT-1 synthetic aperture radar (SAR) data were used to enhance linear features to extract geologically significant lineaments in the Appalachian region. Comparison of Lineaments thus mapped with an existing lineament map based on LANDSAT MSS images shows that appropriately processed SEASAT-1 SAR data can significantly improve the detection of lineaments. Merge MSS and SAR data sets were more useful fo lineament detection and landcover classification than LANDSAT or SEASAT data alone. About 20 percent of the lineaments plotted from the SEASAT SAR image did not appear on the LANDSAT image. About 6 percent of minor lineaments or parts of lineaments present in the LANDSAT map were missing from the SEASAT map. Improvement in the landcover classification (acreage and spatial estimation accuracy) was attained by using MSS-SAR merged data. The aerial estimation of residential/built-up and forest categories was improved. Accuracy in estimating the agricultural and water categories was slightly reduced.

Single-Pol Synthetic Aperture Radar Terrain Classification using Multiclass Confidence for One-Class Classifiers

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

Koch, Mark William; Steinbach, Ryan Matthew; Moya, Mary M

2015-10-01

Except in the most extreme conditions, Synthetic aperture radar (SAR) is a remote sensing technology that can operate day or night. A SAR can provide surveillance over a long time period by making multiple passes over a wide area. For object-based intelligence it is convenient to segment and classify the SAR images into objects that identify various terrains and man-made structures that we call “static features.” In this paper we introduce a novel SAR image product that captures how different regions decorrelate at different rates. Using superpixels and their first two moments we develop a series of one-class classification algorithmsmore » using a goodness-of-fit metric. P-value fusion is used to combine the results from different classes. We also show how to combine multiple one-class classifiers to get a confidence about a classification. This can be used by downstream algorithms such as a conditional random field to enforce spatial constraints.« less

Automatic Synthetic Aperture Radar based oil spill detection and performance estimation via a semi-automatic operational service benchmark.

PubMed

Singha, Suman; Vespe, Michele; Trieschmann, Olaf

2013-08-15

Today the health of ocean is in danger as it was never before mainly due to man-made pollutions. Operational activities show regular occurrence of accidental and deliberate oil spill in European waters. Since the areas covered by oil spills are usually large, satellite remote sensing particularly Synthetic Aperture Radar represents an effective option for operational oil spill detection. This paper describes the development of a fully automated approach for oil spill detection from SAR. Total of 41 feature parameters extracted from each segmented dark spot for oil spill and 'look-alike' classification and ranked according to their importance. The classification algorithm is based on a two-stage processing that combines classification tree analysis and fuzzy logic. An initial evaluation of this methodology on a large dataset has been carried out and degree of agreement between results from proposed algorithm and human analyst was estimated between 85% and 93% respectively for ENVISAT and RADARSAT. Copyright © 2013 Elsevier Ltd. All rights reserved.

On the SAR derived alert in the detection of oil spills according to the analysis of the EGEMP.

PubMed

Ferraro, Guido; Baschek, Björn; de Montpellier, Geraldine; Njoten, Ove; Perkovic, Marko; Vespe, Michele

2010-01-01

Satellite services that deliver information about possible oil spills at sea currently use different labels of "confidence" to describe the detections based on radar image processing. A common approach is to use a classification differentiating between low, medium and high levels of confidence. There is an ongoing discussion on the suitability of the existing classification systems of possible oil spills detected by radar satellite images with regard to the relevant significance and correspondence to user requirements. This paper contains a basic analysis of user requirements, current technical possibilities of satellite services as well as proposals for a redesign of the classification system as an evolution towards a more structured alert system. This research work offers a first review of implemented methodologies for the categorisation of detected oil spills, together with the proposal of explorative ideas evaluated by the European Group of Experts on satellite Monitoring of sea-based oil Pollution (EGEMP). Copyright 2009 Elsevier Ltd. All rights reserved.

Time-frequency analysis of backscattered signals from diffuse radar targets

NASA Astrophysics Data System (ADS)

Kenny, O. P.; Boashash, B.

1993-06-01

The need for analysis of time-varying signals has led to the formulation of a class of joint time-frequency distributions (TFDs). One of these TFDs, the Wigner-Ville distribution (WVD), has useful properties which can be applied to radar imaging. The authors discuss time-frequency representation of the backscattered signal from a diffuse radar target. It is then shown that for point scatterers which are statistically dependent or for which the reflectivity coefficient has a nonzero mean value, reconstruction using time of flight positron emission tomography on time-frequency images is effective for estimating the scattering function of the target.

33 CFR 110.232 - Southeast Alaska.

Code of Federal Regulations, 2011 CFR

2011-07-01

... explosives anchorage. (5) A wooden vessel must: (i) Be fitted with a radar reflector screen of metal of sufficient size to permit target indication on the radar screen of commercial type radar; or (ii) Have steel...

33 CFR 110.232 - Southeast Alaska.

Code of Federal Regulations, 2010 CFR

2010-07-01

... explosives anchorage. (5) A wooden vessel must: (i) Be fitted with a radar reflector screen of metal of sufficient size to permit target indication on the radar screen of commercial type radar; or (ii) Have steel...

33 CFR 110.232 - Southeast Alaska.

Code of Federal Regulations, 2012 CFR

2012-07-01

... explosives anchorage. (5) A wooden vessel must: (i) Be fitted with a radar reflector screen of metal of sufficient size to permit target indication on the radar screen of commercial type radar; or (ii) Have steel...

33 CFR 110.232 - Southeast Alaska.

Code of Federal Regulations, 2014 CFR

2014-07-01

... explosives anchorage. (5) A wooden vessel must: (i) Be fitted with a radar reflector screen of metal of sufficient size to permit target indication on the radar screen of commercial type radar; or (ii) Have steel...

33 CFR 110.232 - Southeast Alaska.

Code of Federal Regulations, 2013 CFR

2013-07-01

... explosives anchorage. (5) A wooden vessel must: (i) Be fitted with a radar reflector screen of metal of sufficient size to permit target indication on the radar screen of commercial type radar; or (ii) Have steel...

radR: an open-source platform for acquiring and analysing data on biological targets observed by surveillance radar.

PubMed

Taylor, Philip D; Brzustowski, John M; Matkovich, Carolyn; Peckford, Michael L; Wilson, Dave

2010-10-26

Radar has been used for decades to study movement of insects, birds and bats. In spite of this, there are few readily available software tools for the acquisition, storage and processing of such data. Program radR was developed to solve this problem. Program radR is an open source software tool for the acquisition, storage and analysis of data from marine radars operating in surveillance mode. radR takes time series data with a two-dimensional spatial component as input from some source (typically a radar digitizing card) and extracts and retains information of biological relevance (i.e. moving targets). Low-level data processing is implemented in "C" code, but user-defined functions written in the "R" statistical programming language can be called at pre-defined steps in the calculations. Output data formats are designed to allow for future inclusion of additional data items without requiring change to C code. Two brands of radar digitizing card are currently supported as data sources. We also provide an overview of the basic considerations of setting up and running a biological radar study. Program radR provides a convenient, open source platform for the acquisition and analysis of radar data of biological targets.

radR: an open-source platform for acquiring and analysing data on biological targets observed by surveillance radar

PubMed Central

2010-01-01

Background Radar has been used for decades to study movement of insects, birds and bats. In spite of this, there are few readily available software tools for the acquisition, storage and processing of such data. Program radR was developed to solve this problem. Results Program radR is an open source software tool for the acquisition, storage and analysis of data from marine radars operating in surveillance mode. radR takes time series data with a two-dimensional spatial component as input from some source (typically a radar digitizing card) and extracts and retains information of biological relevance (i.e. moving targets). Low-level data processing is implemented in "C" code, but user-defined functions written in the "R" statistical programming language can be called at pre-defined steps in the calculations. Output data formats are designed to allow for future inclusion of additional data items without requiring change to C code. Two brands of radar digitizing card are currently supported as data sources. We also provide an overview of the basic considerations of setting up and running a biological radar study. Conclusions Program radR provides a convenient, open source platform for the acquisition and analysis of radar data of biological targets. PMID:20977735

Roadside IED detection using subsurface imaging radar and rotary UAV

NASA Astrophysics Data System (ADS)

Qin, Yexian; Twumasi, Jones O.; Le, Viet Q.; Ren, Yu-Jiun; Lai, C. P.; Yu, Tzuyang

2016-05-01

Modern improvised explosive device (IED) and mine detection sensors using microwave technology are based on ground penetrating radar operated by a ground vehicle. Vehicle size, road conditions, and obstacles along the troop marching direction limit operation of such sensors. This paper presents a new conceptual design using a rotary unmanned aerial vehicle (UAV) to carry subsurface imaging radar for roadside IED detection. We have built a UAV flight simulator with the subsurface imaging radar running in a laboratory environment and tested it with non-metallic and metallic IED-like targets. From the initial lab results, we can detect the IED-like target 10-cm below road surface while carried by a UAV platform. One of the challenges is to design the radar and antenna system for a very small payload (less than 3 lb). The motion compensation algorithm is also critical to the imaging quality. In this paper, we also demonstrated the algorithm simulation and experimental imaging results with different IED target materials, sizes, and clutters.

Surface water classification and monitoring using polarimetric synthetic aperture radar

NASA Astrophysics Data System (ADS)

Irwin, Katherine Elizabeth

Surface water classification using synthetic aperture radar (SAR) is an established practice for monitoring flood hazards due to the high temporal and spatial resolution it provides. Surface water change is a dynamic process that varies both spatially and temporally, and can occur on various scales resulting in significant impacts on affected areas. Small-scale flooding hazards, caused by beaver dam failure, is an example of surface water change, which can impact nearby infrastructure and ecosystems. Assessing these hazards is essential to transportation and infrastructure maintenance. With current satellite missions operating in multiple polarizations, spatio-temporal resolutions, and frequencies, a comprehensive comparison between SAR products for surface water monitoring is necessary. In this thesis, surface water extent models derived from high resolution single-polarization TerraSAR-X (TSX) data, medium resolution dual-polarization TSX data and low resolution quad-polarization RADARSAT-2 (RS-2) data are compared. There exists a compromise between acquiring SAR data with a high resolution or high information content. Multi-polarization data provides additional phase and intensity information, which makes it possible to better classify areas of flooded vegetation and wetlands. These locations are often where fluctuations in surface water occur and are essential for understanding dynamic underlying processes. However, often multi-polarized data is acquired at a low resolution, which cannot image these zones effectively. High spatial resolution, single-polarization TSX data provides the best model of open water. However, these single-polarization observations have limited information content and are affected by shadow and layover errors. This often hinders the classification of other land cover types. The dual-polarization TSX data allows for the classification of flooded vegetation, but classification is less accurate compared to the quad-polarization RS-2 data. The RS-2 data allows for the discrimination of open water, marshes/fields and forested areas. However, the RS-2 data is less applicable to small scale surface water monitoring (e.g. beaver dam failure), due to its low spatial resolution. By understanding the strengths and weaknesses of available SAR technology, an appropriate product can be chosen for a specific target application involving surface water change. This research benefits the eventual development of a space-based monitoring strategy over longer periods.

Search Radar Track-Before-Detect Using the Hough Transform.

DTIC Science & Technology

1995-03-01

before - detect processing method which allows previous data to help in target detection. The technique provides many advantages compared to...improved target detection scheme, applicable to search radars, using the Hough transform image processing technique. The system concept involves a track

TRMM Precipitation Radar Reflectivity Profiles Compared to High-Resolution Airborne and Ground-Based Radar Measurements

NASA Technical Reports Server (NTRS)

Heymsfield, G. M.; Geerts, B.; Tian, L.

1999-01-01

In this paper, TRMM (Tropical Rainfall Measuring Mission Satellite) Precipitation Radar (PR) products are evaluated by means of simultaneous comparisons with data from the high-altitude ER-2 Doppler Radar (EDOP), as well as ground-based radars. The comparison is aimed primarily at the vertical reflectivity structure, which is of key importance in TRMM rain type classification and latent heating estimation. The radars used in this study have considerably different viewing geometries and resolutions, demanding non-trivial mapping procedures in common earth-relative coordinates. Mapped vertical cross sections and mean profiles of reflectivity from the PR, EDOP, and ground-based radars are compared for six cases. These cases cover a stratiform frontal rainband, convective cells of various sizes and stages, and a hurricane. For precipitating systems that are large relative to the PR footprint size, PR reflectivity profiles compare very well to high-resolution measurements thresholded to the PR minimum reflectivity, and derived variables such as bright band height and rain types are accurate, even at high PR incidence angles. It was found that for, the PR reflectivity of convective cells small relative to the PR footprint is weaker than in reality. Some of these differences can be explained by non-uniform beam filling. For other cases where strong reflectivity gradients occur within a PR footprint, the reflectivity distribution is spread out due to filtering by the PR antenna illumination pattern. In these cases, rain type classification may err and be biased towards the stratiform type, and the average reflectivity tends to be underestimated. The limited sensitivity of the PR implies that the upper regions of precipitation systems remain undetected and that the PR storm top height estimate is unreliable, usually underestimating the actual storm top height. This applies to all cases but the discrepancy is larger for smaller cells where limited sensitivity is compounded by incomplete beam filling. Users of level three TRMM PR products should be aware of this scale dependency.

Automated classification of Permanent Scatterers time-series based on statistical characterization tests

NASA Astrophysics Data System (ADS)

Berti, Matteo; Corsini, Alessandro; Franceschini, Silvia; Iannacone, Jean Pascal

2013-04-01

The application of space borne synthetic aperture radar interferometry has progressed, over the last two decades, from the pioneer use of single interferograms for analyzing changes on the earth's surface to the development of advanced multi-interferogram techniques to analyze any sort of natural phenomena which involves movements of the ground. The success of multi-interferograms techniques in the analysis of natural hazards such as landslides and subsidence is widely documented in the scientific literature and demonstrated by the consensus among the end-users. Despite the great potential of this technique, radar interpretation of slope movements is generally based on the sole analysis of average displacement velocities, while the information embraced in multi interferogram time series is often overlooked if not completely neglected. The underuse of PS time series is probably due to the detrimental effect of residual atmospheric errors, which make the PS time series characterized by erratic, irregular fluctuations often difficult to interpret, and also to the difficulty of performing a visual, supervised analysis of the time series for a large dataset. In this work is we present a procedure for automatic classification of PS time series based on a series of statistical characterization tests. The procedure allows to classify the time series into six distinctive target trends (0=uncorrelated; 1=linear; 2=quadratic; 3=bilinear; 4=discontinuous without constant velocity; 5=discontinuous with change in velocity) and retrieve for each trend a series of descriptive parameters which can be efficiently used to characterize the temporal changes of ground motion. The classification algorithms were developed and tested using an ENVISAT datasets available in the frame of EPRS-E project (Extraordinary Plan of Environmental Remote Sensing) of the Italian Ministry of Environment (track "Modena", Northern Apennines). This dataset was generated using standard processing, then the time series are typically affected by a significant noise to signal ratio. The results of the analysis show that even with such a rough-quality dataset, our automated classification procedure can greatly improve radar interpretation of mass movements. In general, uncorrelated PS (type 0) are concentrated in flat areas such as fluvial terraces and valley bottoms, and along stable watershed divides; linear PS (type 1) are mainly located on slopes (both inside or outside mapped landslides) or near the edge of scarps or steep slopes; non-linear PS (types 2 to 5) typically fall inside landslide deposits or in the surrounding areas. The spatial distribution of classified PS allows to detect deformation phenomena not visible by considering the average velocity alone, and provide important information on the temporal evolution of the phenomena such as acceleration, deceleration, seasonal fluctuations, abrupt or continuous changes of the displacement rate. Based on these encouraging results we integrated all the classification algorithms into a Graphical User Interface (called PSTime) which is freely available as a standalone application.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator)

1981-01-01

Training and test data sets for CAM1S from NS-001 MSS data for two dates (geometrically adjusted to 30 meter resolution) were used to evaluate wavelength band. Two sets of tapes containing digitized HH and HV polarization data were obtained. Because the SAR data on the 9 track tapes contained no meaningful data, the 7 track tapes were copied onto 9 track tapes at LARS. The LARSYS programs were modified and a program was written to reformat the digitized SAR data into a LARSYS format. The radar imagery is being qualitatively interpreted. Results are to be used to identify possible cover types, to produce a classification map to aid in the numerical evaluation classification of radar data, and to develop an interpretation key for radar imagery. The four spatial resolution data sets were analyzed. A program was developed to reduce the spatial distortions resulting from variable viewing distance, and geometrically adjusted data sets were generated. A flowchart of steps taken to geometrically adjust a data set from the NS-001 scanner is presented.

Bi-Spectral Method for Radar Target Recognition

DTIC Science & Technology

2006-12-01

θazimuth=60° and ϕelevation=30° with HV Polarization....................................53 Figure 50 Comparison of Radar Range Profile with Actual...radar systems. A comparison of the NCTR techniques and their relative advantages and disadvantages in target recognition performance is presented. 8...32 f fR i R R c c f fi R R i R R c c A e A e A e ψ ψ π ψ ψ π ψ ψ π ψ ψ

Full-wave Characterization of Rough Terrain Surface Effects for Forward-looking Radar Applications: A Scattering and Imaging Study from the Electromagnetic Perspective

DTIC Science & Technology

2011-09-01

and Imaging Framework First, the parallelized 3-D FDTD algorithm is applied to simulate composite scattering from targets in a rough ground...solver as pertinent to forward-looking radar sensing , the effects of surface clutter on multistatic target imaging are illustrated with large-scale...Full-wave Characterization of Rough Terrain Surface Effects for Forward-looking Radar Applications: A Scattering and Imaging Study from the

Waveform-Diverse Multiple-Input Multiple-Output Radar Imaging Measurements

NASA Astrophysics Data System (ADS)

Stewart, Kyle B.

Multiple-input multiple-output (MIMO) radar is an emerging set of technologies designed to extend the capabilities of multi-channel radar systems. While conventional radar architectures emphasize the use of antenna array beamforming to maximize real-time power on target, MIMO radar systems instead attempt to preserve some degree of independence between their received signals and to exploit this expanded matrix of target measurements in the signal-processing domain. Specifically the use of sparse “virtual” antenna arrays may allow MIMO radars to achieve gains over traditional multi-channel systems by post-processing diverse received signals to implement both transmit and receive beamforming at all points of interest within a given scene. MIMO architectures have been widely examined for use in radar target detection, but these systems may yet be ideally suited to real and synthetic aperture radar imaging applications where their proposed benefits include improved resolutions, expanded area coverage, novel modes of operation, and a reduction in hardware size, weight, and cost. While MIMO radar's theoretical benefits have been well established in the literature, its practical limitations have not received great attention thus far. The effective use of MIMO radar techniques requires a diversity of signals, and to date almost all MIMO system demonstrations have made use of time-staggered transmission to satisfy this requirement. Doing so is reliable but can be prohibitively slow. Waveform-diverse systems have been proposed as an alternative in which multiple, independent waveforms are broadcast simultaneously over a common bandwidth and separated on receive using signal processing. Operating in this way is much faster than its time-diverse equivalent, but finding a set of suitable waveforms for this technique has proven to be a difficult problem. In light of this, many have questioned the practicality of MIMO radar imaging and whether or not its theoretical benefits may be extended to real systems. Work in this writing focuses specifically on the practical aspects of MIMO radar imaging systems and provides performance data sourced from experimental measurements made using a four-channel software-defined MIMO radar platform. Demonstrations of waveform-diverse imaging data products are provided and compared directly against time-diverse equivalents in order to assess the performance of prospective MIMO waveforms. These are sourced from the pseudo-noise, short-term shift orthogonal, and orthogonal frequency multiplexing signal families while experimental results demonstrate waveform-diverse measurements of polarimetric radar cross section, top-down stationary target images, and finally volumetric MIMO synthetic aperture radar imagery. The data presented represents some of the first available concerning the overall practicality of waveform-diverse MIMO radar architectures, and results suggest that such configurations may achieve a reasonable degree of performance even in the presence of significant practical limitations.

Determination of the Sources of Radar Scattering

NASA Technical Reports Server (NTRS)

Moore, R. K.; Zoughi, R.

1984-01-01

Fine-resolution radar backscattering measurements were proposed to determine the backscattering sources in various vegetation canopies and surface targets. The results were then used to improve the existing theoretical models of terrain scattering, and also to enhance understanding of the radar signal observed by an imaging radar over a vegetated area. Various experiments were performed on targets such as corn, milo, soybeans, grass, asphalt pavements, soil and concrete walkways. Due to the lack of available references on measurements of this type, the obtained results will be used primarily as a foundation or future experiments. The constituent backscattering characteristics of the vegetation canopies was also examined.

Range detection using entangled optical photons

NASA Astrophysics Data System (ADS)

Brandsema, Matthew J.; Narayanan, Ram M.; Lanzagorta, Marco

2015-05-01

Quantum radar is an emerging field that shows a lot of promise in providing significantly improved resolution compared to its classical radar counterpart. The key to this kind of resolution lies in the correlations created from the entanglement of the photons being used. Currently, the technology available only supports quantum radar implementation and validation in the optical regime, as opposed to the microwave regime, because microwave photons have very low energy compared to optical photons. Furthermore, there currently do not exist practical single photon detectors and generators in the microwave spectrum. Viable applications in the optical regime include deep sea target detection and high resolution detection in space. In this paper, we propose a conceptual architecture of a quantum radar which uses entangled optical photons based on Spontaneous Parametric Down Conversion (SPDC) methods. After the entangled photons are created and emerge from the crystal, the idler photon is detected very shortly thereafter. At the same time, the signal photon is sent out towards the target and upon its reflection will impinge on the detector of the radar. From these two measurements, correlation data processing is done to obtain the distance of the target away from the radar. Various simulations are then shown to display the resolution that is possible.

A study of 35-ghz radar-assisted orbital maneuvering vehicle/space telescope docking

NASA Technical Reports Server (NTRS)

Mcdonald, M. W.

1986-01-01

An experiment was conducted to study the effects of measuring range and range rate information from a complex radar target (a one-third scale model of the Edwin P. Hubble Space Telescope). The radar ranging system was a 35-GHz frequency-modulated continuous wave unit developed in the Communication Systems Branch of the Information and Electronic Systems Laboratory at Marshall Space Flight Cneter. Measurements were made over radar-to-target distances of 5 meters to 15 meters to simulate the close distance realized in the final stages of space vehicle docking. The Space Telescope model target was driven by an antenna positioner through a range of azimuth and elevation (pitch) angles to present a variety of visual aspects of the aft end to the radar. Measurements were obtained with and without a cube corner reflector mounted in the center of the aft end of the model. The results indicate that range and range rate measurements are performed significantly more accurately with the cooperative radar reflector affixed. The results further reveal that range rate (velocity) can be measured accurately enough to support the required soft docking with the Space Telescope.

Three-Dimensional ISAR Imaging Method for High-Speed Targets in Short-Range Using Impulse Radar Based on SIMO Array.

PubMed

Zhou, Xinpeng; Wei, Guohua; Wu, Siliang; Wang, Dawei

2016-03-11

This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes a missile motion parameter estimation method based on impulse radar. By analyzing the motion geometry relationship of the warhead scattering center after translational compensation, this paper derives the receiving antenna position and the time delay after translational compensation, and thus overcomes the shortcomings of conventional translational compensation methods. By analyzing the motion characteristics of the missile, this paper estimates the missile's rotation angle and the rotation matrix by establishing a new coordinate system. Simulation results validate the performance of the proposed algorithm.

Research on Radar Micro-Doppler Feature Parameter Estimation of Propeller Aircraft

NASA Astrophysics Data System (ADS)

He, Zhihua; Tao, Feixiang; Duan, Jia; Luo, Jingsheng

2018-01-01

The micro-motion modulation effect of the rotated propellers to radar echo can be a steady feature for aircraft target recognition. Thus, micro-Doppler feature parameter estimation is a key to accurate target recognition. In this paper, the radar echo of rotated propellers is modelled and simulated. Based on which, the distribution characteristics of the micro-motion modulation energy in time, frequency and time-frequency domain are analyzed. The micro-motion modulation energy produced by the scattering points of rotating propellers is accumulated using the Inverse-Radon (I-Radon) transform, which can be used to accomplish the estimation of micro-modulation parameter. Finally, it is proved that the proposed parameter estimation method is effective with measured data. The micro-motion parameters of aircraft can be used as the features of radar target recognition.

Radar Imaging for Moving Targets

DTIC Science & Technology

2009-06-01

MOVING TARGETS by Teo Beng Koon William June 2009 Thesis Advisor: Brett H. Borden Second Reader: Donald L. Walters THIS PAGE...Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project...TITLE AND SUBTITLE Radar Imaging for Moving Targets 6. AUTHOR(S) Teo Beng Koon William 5. FUNDING NUMBERS 7. PERFORMING ORGANIZATION NAME(S

Using doppler radar images to estimate aircraft navigational heading error

DOEpatents

Doerry, Armin W [Albuquerque, NM; Jordan, Jay D [Albuquerque, NM; Kim, Theodore J [Albuquerque, NM

2012-07-03

A yaw angle error of a motion measurement system carried on an aircraft for navigation is estimated from Doppler radar images captured using the aircraft. At least two radar pulses aimed at respectively different physical locations in a targeted area are transmitted from a radar antenna carried on the aircraft. At least two Doppler radar images that respectively correspond to the at least two transmitted radar pulses are produced. These images are used to produce an estimate of the yaw angle error.

FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar

NASA Astrophysics Data System (ADS)

Azim, Noor ul; Jun, Wang

2016-11-01

Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.

Distributed micro-radar system for detection and tracking of low-profile, low-altitude targets

NASA Astrophysics Data System (ADS)

Gorwara, Ashok; Molchanov, Pavlo

2016-05-01

Proposed airborne surveillance radar system can detect, locate, track, and classify low-profile, low-altitude targets: from traditional fixed and rotary wing aircraft to non-traditional targets like unmanned aircraft systems (drones) and even small projectiles. Distributed micro-radar system is the next step in the development of passive monopulse direction finder proposed by Stephen E. Lipsky in the 80s. To extend high frequency limit and provide high sensitivity over the broadband of frequencies, multiple angularly spaced directional antennas are coupled with front end circuits and separately connected to a direction finder processor by a digital interface. Integration of antennas with front end circuits allows to exclude waveguide lines which limits system bandwidth and creates frequency dependent phase errors. Digitizing of received signals proximate to antennas allows loose distribution of antennas and dramatically decrease phase errors connected with waveguides. Accuracy of direction finding in proposed micro-radar in this case will be determined by time accuracy of digital processor and sampling frequency. Multi-band, multi-functional antennas can be distributed around the perimeter of a Unmanned Aircraft System (UAS) and connected to the processor by digital interface or can be distributed between swarm/formation of mini/micro UAS and connected wirelessly. Expendable micro-radars can be distributed by perimeter of defense object and create multi-static radar network. Low-profile, lowaltitude, high speed targets, like small projectiles, create a Doppler shift in a narrow frequency band. This signal can be effectively filtrated and detected with high probability. Proposed micro-radar can work in passive, monostatic or bistatic regime.

Advanced studies of electromagnetic scattering

NASA Technical Reports Server (NTRS)

Ling, Hao

1994-01-01

In radar signature applications it is often desirable to generate the range profiles and inverse synthetic aperture radar (ISAR) images of a target. They can be used either as identification tools to distinguish and classify the target from a collection of possible targets, or as diagnostic/design tools to pinpoint the key scattering centers on the target. The simulation of synthetic range profiles and ISAR images is usually a time intensive task and computation time is of prime importance. Our research has been focused on the development of fast simulation algorithms for range profiles and ISAR images using the shooting and bouncing ray (SBR) method, a high frequency electromagnetic simulation technique for predicting the radar returns from realistic aerospace vehicles and the scattering by complex media.

Use of radar to study the movements of Marbled Murrelets at inland sites

Treesearch

Thomas E. Hamer; Brian A. Cooper; C. John Ralph

1995-01-01

A modified vehicle-mounted, X-band marine radar system was used to study the movements of marbled murrelets (Brachyramphus marmoratus) at inland and coastal sites in northern California during July. The ability of the radar to discriminate murrelets from other targets, and to estimate abundance was assessed. Murrelets were detected by radar at...

Automated intelligent video surveillance system for ships

NASA Astrophysics Data System (ADS)

Wei, Hai; Nguyen, Hieu; Ramu, Prakash; Raju, Chaitanya; Liu, Xiaoqing; Yadegar, Jacob

2009-05-01

To protect naval and commercial ships from attack by terrorists and pirates, it is important to have automatic surveillance systems able to detect, identify, track and alert the crew on small watercrafts that might pursue malicious intentions, while ruling out non-threat entities. Radar systems have limitations on the minimum detectable range and lack high-level classification power. In this paper, we present an innovative Automated Intelligent Video Surveillance System for Ships (AIVS3) as a vision-based solution for ship security. Capitalizing on advanced computer vision algorithms and practical machine learning methodologies, the developed AIVS3 is not only capable of efficiently and robustly detecting, classifying, and tracking various maritime targets, but also able to fuse heterogeneous target information to interpret scene activities, associate targets with levels of threat, and issue the corresponding alerts/recommendations to the man-in- the-loop (MITL). AIVS3 has been tested in various maritime scenarios and shown accurate and effective threat detection performance. By reducing the reliance on human eyes to monitor cluttered scenes, AIVS3 will save the manpower while increasing the accuracy in detection and identification of asymmetric attacks for ship protection.

Synthetic aperture radar for a crop information system: A multipolarization and multitemporal approach

NASA Astrophysics Data System (ADS)

Ban, Yifang

Acquisition of timely information is a critical requirement for successful management of an agricultural monitoring system. Crop identification and crop-area estimation can be done fairly successfully using satellite sensors operating in the visible and near-infrared (VIR) regions of the spectrum. However, data collection can be unreliable due to problems of cloud cover at critical stages of the growing season. The all-weather capability of synthetic aperture radar (SAR) imagery acquired from satellites provides data over large areas whenever crop information is required. At the same time, SAR is sensitive to surface roughness and should be able to provide surface information such as tillage-system characteristics. With the launch of ERS-1, the first long-duration SAR system became available. The analysis of airborne multipolarization SAR data, multitemporal ERS-1 SAR data, and their combinations with VIR data, is necessary for the development of image-analysis methodologies that can be applied to RADARSAT data for extracting agricultural crop information. The overall objective of this research is to evaluate multipolarization airborne SAR data, multitemporal ERS-1 SAR data, and combinations of ERS-1 SAR and satellite VIR data for crop classification using non-conventional algorithms. The study area is situated in Norwich Township, an agricultural area in Oxford County, southern Ontario, Canada. It has been selected as one of the few representative agricultural 'supersites' across Canada at which the relationships between radar data and agriculture are being studied. The major field crops are corn, soybeans, winter wheat, oats, barley, alfalfa, hay, and pasture. Using airborne C-HH and C-HV SAR data, it was found that approaches using contextual information, texture information and per-field classification for improving agricultural crop classification proved to be effective, especially the per-field classification method. Results show that three of the four best per-field classification accuracies (\\ K=0.91) are achieved using combinations of C-HH and C-VV SAR data. This confirms the strong potential of multipolarization data for crop classification. The synergistic effects of multitemporal ERS-1 SAR and Landsat TM data are evaluated for crop classification using an artificial neural network (ANN) approach. The results show that the per-field approach using a feed-forward ANN significantly improves the overall classification accuracy of both single-date and multitemporal SAR data. Using the combination of TM3,4,5 and Aug. 5 SAR data, the best per-field ANN classification of 96.8% was achieved. It represents an 8.5% improvement over a single TM3,4,5 classification alone. Using multitemporal ERS-1 SAR data acquired during the 1992 and 1993 growing seasons, the radar backscatter characteristics of crops and their underlying soils are analyzed. The SAR temporal backscatter profiles were generated for each crop type and the earliest times of the year for differentiation of individual crop types were determined. Orbital (incidence-angle) effects were also observed on all crops. The average difference between the two orbits was about 3 dB. Thus attention should be given to the local incidence-angle effects when using ERS-1 SAR data, especially when comparing fields from different scenes or different areas within the same scene. Finally, early- and mid-season multitemporal SAR data for crop classification using sequential-masking techniques are evaluated, based on the temporal backscatter profiles. It was found that all crops studied could be identified by July 21.

Drop Size Distribution - Based Separation of Stratiform and Convective Rain

NASA Technical Reports Server (NTRS)

Thurai, Merhala; Gatlin, Patrick; Williams, Christopher

2014-01-01

For applications in hydrology and meteorology, it is often desirable to separate regions of stratiform and convective rain from meteorological radar observations, both from ground-based polarimetric radars and from space-based dual frequency radars. In a previous study by Bringi et al. (2009), dual frequency profiler and dual polarization radar (C-POL) observations in Darwin, Australia, had shown that stratiform and convective rain could be separated in the log10(Nw) versus Do domain, where Do is the mean volume diameter and Nw is the scaling parameter which is proportional to the ratio of water content to the mass weighted mean diameter. Note, Nw and Do are two of the main drop size distribution (DSD) parameters. In a later study, Thurai et al (2010) confirmed that both the dual-frequency profiler based stratiform-convective rain separation and the C-POL radar based separation were consistent with each other. In this paper, we test this separation method using DSD measurements from a ground based 2D video disdrometer (2DVD), along with simultaneous observations from a collocated, vertically-pointing, X-band profiling radar (XPR). The measurements were made in Huntsville, Alabama. One-minute DSDs from 2DVD are used as input to an appropriate gamma fitting procedure to determine Nw and Do. The fitted parameters - after averaging over 3-minutes - are plotted against each other and compared with a predefined separation line. An index is used to determine how far the points lie from the separation line (as described in Thurai et al. 2010). Negative index values indicate stratiform rain and positive index indicate convective rain, and, moreover, points which lie somewhat close to the separation line are considered 'mixed' or 'transition' type precipitation. The XPR observations are used to evaluate/test the 2DVD data-based classification. A 'bright-band' detection algorithm was used to classify each vertical reflectivity profile as either stratiform or convective, depending on whether or not a clearly-defined melting layer is present at an expected height, and if present, maximum reflectivity within the melting layer as well as the corresponding height are determined. We will present results of quantitative comparisons between the XPR observations-based classifications and the simultaneous 2DVD data-based classifications. Time series comparisons will be presented for thirteen events in Huntsville.

Vector neural network signal integration for radar application

NASA Astrophysics Data System (ADS)

Bierman, Gregory S.

1994-07-01

The Litton Data Systems Vector Neural Network (VNN) is a unique multi-scan integration algorithm currently in development. The target of interest is a low-flying cruise missile. Current tactical radar cannot detect and track the missile in ground clutter at tactically useful ranges. The VNN solves this problem by integrating the energy from multiple frames to effectively increase the target's signal-to-noise ratio. The implementation plan is addressing the APG-63 radar. Real-time results will be available by March 1994.

Potential enhancements to the performance of ASDE radars derived from multistatic radar principles

DOT National Transportation Integrated Search

2001-10-14

Airport surface surveillance systems, such as airport surface detection equipment (ASDE) radars, are susceptible to multipath propagation and scattering effects that can result in the placement of false targets located at critical locations on airpor...

Supervised fully polarimetric classification of the Black Forest test site: From MAESTROI to MAC Europe

NASA Technical Reports Server (NTRS)

Degrandi, G.; Lavalle, C.; Degroof, H.; Sieber, A.

1992-01-01

A study on the performance of a supervised fully polarimetric maximum likelihood classifier for synthetic aperture radar (SAR) data when applied to a specific classification context: forest classification based on age classes and in the presence of a sloping terrain is presented. For the experimental part, the polarimetric AIRSAR data at P, L, and C-band, acquired over the German Black Forest near Freiburg in the frame of the 1989 MAESTRO-1 campaign and the 1991 MAC Europe campaign was used, MAESTRO-1 with an ESA/JRC sponsored campaign, and MAC Europe (Multi-sensor Aircraft Campaign); in both cases the multi-frequency polarimetric JPL Airborne Synthetic Aperture Radar (AIRSAR) radar was flown over a number of European test sites. The study is structured as follows. At first, the general characteristics of the classifier and the dependencies from some parameters, like frequency bands, feature vector, calibration, using test areas lying on a flat terrain are investigated. Once it is determined the optimal conditions for the classifier performance, we then move on to the study of the slope effect. The bulk of this work is performed using the Maestrol data set. Next the classifier performance with the MAC Europe data is considered. The study is divided into two stages: first some of the tests done on the Maestro data are repeated, to highlight the improvements due to the new processing scheme that delivers 16 look data. Second we experiment with multi images classification with two goals: to assess the possibility of using a training set measured from one image to classify areas in different images; and to classify areas on critical slopes using different viewing angles. The main points of the study are listed and some of the results obtained so far are highlighted.

IRST: a key system in modern warfare

NASA Astrophysics Data System (ADS)

Missirian, Jean-Michel; Ducruet, Laurent

1997-08-01

A naval infra red search and track (IRST) system is a passive surveillance device capable of detecting and tracking air and surface threats in the region where electromagnetic sensors are less efficient, typically within a few degrees around the horizon. The evolution in anti ship sea skimming missiles performances has outlined the benefit that can be gained from infrared systems in ship self-defense. The complementary nature of radar and IRST systems can also be exploited to full advantage in the field of multisensor data fusion. The combined use of radar and infrared secures the detection by redundancy of data; it substantially enhances target tracking, classification and identification and reduces the combat system's reaction time. Designing an IRST implies matching technical choices with operational requirements, and this under increasingly stringent cost constraints. This paper first reminds the benefits that can be obtained with an IRST system in the context of modern naval warfare, then retraces the evolutions from the first generation IRST systems, such as VAMPIR, to the second-generation systems now entering service. A general presentation of the current SAGEM SA IRST family is also made for naval, air and ground-based applications.

Onboard Radar Processing Development for Rapid Response Applications

NASA Technical Reports Server (NTRS)

Lou, Yunling; Chien, Steve; Clark, Duane; Doubleday, Josh; Muellerschoen, Ron; Wang, Charles C.

2011-01-01

We are developing onboard processor (OBP) technology to streamline data acquisition on-demand and explore the potential of the L-band SAR instrument onboard the proposed DESDynI mission and UAVSAR for rapid response applications. The technology would enable the observation and use of surface change data over rapidly evolving natural hazards, both as an aid to scientific understanding and to provide timely data to agencies responsible for the management and mitigation of natural disasters. We are adapting complex science algorithms for surface water extent to detect flooding, snow/water/ice classification to assist in transportation/ shipping forecasts, and repeat-pass change detection to detect disturbances. We are near completion of the development of a custom FPGA board to meet the specific memory and processing needs of L-band SAR processor algorithms and high speed interfaces to reformat and route raw radar data to/from the FPGA processor board. We have also developed a high fidelity Matlab model of the SAR processor that is modularized and parameterized for ease to prototype various SAR processor algorithms targeted for the FPGA. We will be testing the OBP and rapid response algorithms with UAVSAR data to determine the fidelity of the products.

An Orbital "Virtual Radar" from TRMM Passive Microwave and Lightning Observations

NASA Technical Reports Server (NTRS)

Boccippio, Dennis J.

2004-01-01

The retrieval of vertical structure from joint passive microwave and lightning observations is demonstrated. Three years of data from the TRMM (Tropical Rainfall Measuring Mission) are used as a training dataset for regression and classification neural networks; the TMI (TRMM Microwave Imager) and LIS (Lightning Imaging Sensor) provide the inputs, the PR (Precipitation Radar) provides the training targets. Both vertical reflectivity profile categorization (into 9 convective, 7 stratiform, 2 mixed and 6 anvil types) and geophysical parameters (surface rainfall, vertically integrated liquid (VIL), ice water content (IWC) and echo tops) are retrieved. Retrievals are successful over both land and ocean surfaces. The benefit of using lightning observations as inputs to these retrievals is quantitatively demonstrated; lightning essentially provides an additional convective/stratiform discriminator, and is most important for isolation of midlevel (tops in the mixed phase region) convective profile types (this is because high frequency passive microwave observations already provide good convective/stratiform discrimination for deep convective profiles). This is highly relevant as midlevel convective profiles account for an extremely large fraction of tropical rainfall, and yet are most difficult to discriminate from comparable-depth stratiform profile types using passive microwave observations alone.

Detection of bulk explosives using the GPR only portion of the HSTAMIDS system

NASA Astrophysics Data System (ADS)

Tabony, Joshua; Carlson, Douglas O.; Duvoisin, Herbert A., III; Torres-Rosario, Juan

2010-04-01

The legacy AN/PSS-14 (Army-Navy Portable Special Search-14) Handheld Mine Detecting Set (also called HSTAMIDS for Handheld Standoff Mine Detection System) has proven itself over the last 7 years as the state-of-the-art in land mine detection, both for the US Army and for Humanitarian Demining groups. Its dual GPR (Ground Penetrating Radar) and MD (Metal Detection) sensor has provided receiver operating characteristic curves (probability of detection or Pd versus false alarm rate or FAR) that routinely set the mark for such devices. Since its inception and type-classification in 2003 as the US (United States) Army standard, the desire for use of the AN/PSS-14 against alternate threats - such as bulk explosives - has recently become paramount. To this end, L-3 CyTerra has developed and tested bulk explosive detection and discrimination algorithms using only the Stepped Frequency Continuous Wave (SFCW) Ground Penetrating Radar (GPR) portion of the system, versus the fused version that is used to optimally detect land mines. Performance of the new bulk explosive algorithm against representative zero-metal bulk explosive target and clutter emplacements is depicted, with the utility to the operator also described.

Fractal dimension and nonlinear dynamical processes

NASA Astrophysics Data System (ADS)

McCarty, Robert C.; Lindley, John P.

1993-11-01

Mandelbrot, Falconer and others have demonstrated the existence of dimensionally invariant geometrical properties of non-linear dynamical processes known as fractals. Barnsley defines fractal geometry as an extension of classical geometry. Such an extension, however, is not mathematically trivial Of specific interest to those engaged in signal processing is the potential use of fractal geometry to facilitate the analysis of non-linear signal processes often referred to as non-linear time series. Fractal geometry has been used in the modeling of non- linear time series represented by radar signals in the presence of ground clutter or interference generated by spatially distributed reflections around the target or a radar system. It was recognized by Mandelbrot that the fractal geometries represented by man-made objects had different dimensions than the geometries of the familiar objects that abound in nature such as leaves, clouds, ferns, trees, etc. The invariant dimensional property of non-linear processes suggests that in the case of acoustic signals (active or passive) generated within a dispersive medium such as the ocean environment, there exists much rich structure that will aid in the detection and classification of various objects, man-made or natural, within the medium.

Planetary surface characterization from dual-polarization radar observations

NASA Astrophysics Data System (ADS)

Virkki, Anne; Planetary Radar Team of the Arecibo Observatory

2017-10-01

We present a new method to investigate the physical properties of planetary surfaces using dual-polarization radar measurements. The number of radar observations has increased radically during the last five years, allowing us to compare the radar scattering properties of different small-body populations and compositional types. There has also been progress in the laboratory studies of the materials that are relevant to asteroids and comets.In a typical planetary radar measurement a circularly polarized signal is transmitted using a frequency of 2380 MHz (wavelength of 12.6 cm) or 8560 MHz (3.5 cm). The echo is received simultaneously in the same circular (SC) and the opposite circular (OC) polarization as the transmitted signal. The delay and doppler frequency of the signal give highly accurate astrometric information, and the intensity and the polarization are suggestive of the physical properties of the target's near-surface.The radar albedo describes the radar reflectivity of the target. If the effective near-surface is smooth and homogeneous in the wavelength-scale, the echo is received fully in the OC polarization. Wavelength-scale surface roughness or boulders within the effective near-surface volume increase the received echo power in both polarizations. However, there is a lack in the literature describing exactly how the physical properties of the target affect the radar albedo in each polarization, or how they can be derived from the radar measurements.To resolve this problem, we utilize the information that the diffuse components of the OC and SC parts are correlated when the near-surface contains wavelength-scale scatterers such as boulders. A linear least-squares fit to the detected values of OC and SC radar albedos allows us to separate the diffusely scattering part from the quasi-specular part. Combined with the spectro-photometric information of the target and laboratory studies of the permittivity-density dependence, the method provides us with a new way to characterize the density or porosity of the the fine-grained regolith layer, and distinguish it from the centimeter-to-meter-scale boulders. We present the application of the method to asteroids, comets, and the Galilean moons.

Entropy-Based Classification of Subsurface Scatterers: A Valuable Tool for the Analysis of Data Obtained by the Fully Polarimetric WISDOM Radar

NASA Astrophysics Data System (ADS)

Plettemeier, D.; Statz, C.; Hahnel, R.; Benedix, W. S.; Hamran, S. E.; Ciarletti, V.

2016-12-01

The "Water Ice Subsurface Deposition on Mars" Experiment (WISDOM) is a Ground Penetrating Radar (GPR) and part of the 2020 ExoMars Rover payload. It will be the first GPR operating on a planetary rover and the first fully polarimetric radar tasked at probing the subsurface of Mars. WISDOM operates at frequencies between 500 MHz and 3 GHz yielding a centimetric resolution and a penetration depth of about 3 meters in Martian soil. Its prime scientific objective is the detailed characterization of the material distribution within the first few meters of the Martian subsurface as a contribution to the search for evidence of past life. For the first time, WISDOM will give access to the geological structure, electromagnetic nature, and hydrological state of the shallow subsurface by retrieving the layering and properties of the buried reflectors at an unprecedented resolution and, due to the fully polarimetric measurements, amount of information. Furthermore, a "real time" subsurface analysis will support the drill operations by identifying locations of high scientific interest and low risk. Key element in the WISDOM data analysis is the fast and reliable classification and correct localization of subsurface scatterers and layers. The fully polarimetric nature of the WISDOM measurements allows the use of the entropy-alpha decomposition (H-alpha). This method enables the classification of reconstructed images of the subsurface (obtained by inverse imaging algorithms, e.g. f-k migration) with regard to the main scattering mechanisms of geological features present in the image of the subsurface. It is, for example, possible to differentiate smooth surfaces, rough surfaces, isolated spherical scatterers, double- and bounce scattering, anisotropic scatterers, clouds of small scatterers of similar shape as well as layers of oblate spheroids. Preliminary tests under laboratory conditions suggest the feasibility and value of the approach for the classification of geological features in the Martian subsurface in the context of WISDOM data processing and operations. It is a fast and reliable tool leveraging the whole amount of information provided by the fully polarimetric WISDOM Radar.

A New Method of Synthetic Aperture Radar Image Reconstruction Using Modified Convolution Back-Projection Algorithm.

DTIC Science & Technology

1986-08-01

SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTIONAVAILABILITY OF REPORT N/A \\pproved for public release, 21b. OECLASS FI) CAT ) ON/OOWNGRAOING SCMEOLLE...from this set of projections. The Convolution Back-Projection (CBP) algorithm is widely used technique in Computer Aide Tomography ( CAT ). In this work...University of Illinois at Urbana-Champaign. 1985 Ac % DTICEl_ FCTE " AUG 1 11986 Urbana. Illinois U,) I A NEW METHOD OF SYNTHETIC APERTURE RADAR IMAGE

Information extraction and transmission techniques for spaceborne synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Frost, V. S.; Yurovsky, L.; Watson, E.; Townsend, K.; Gardner, S.; Boberg, D.; Watson, J.; Minden, G. J.; Shanmugan, K. S.

1984-01-01

Information extraction and transmission techniques for synthetic aperture radar (SAR) imagery were investigated. Four interrelated problems were addressed. An optimal tonal SAR image classification algorithm was developed and evaluated. A data compression technique was developed for SAR imagery which is simple and provides a 5:1 compression with acceptable image quality. An optimal textural edge detector was developed. Several SAR image enhancement algorithms have been proposed. The effectiveness of each algorithm was compared quantitatively.

Classification of earth terrain using polarimetric synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Lim, H. H.; Swartz, A. A.; Yueh, H. A.; Kong, J. A.; Shin, R. T.; Van Zyl, J. J.

1989-01-01

Supervised and unsupervised classification techniques are developed and used to classify the earth terrain components from SAR polarimetric images of San Francisco Bay and Traverse City, Michigan. The supervised techniques include the Bayes classifiers, normalized polarimetric classification, and simple feature classification using discriminates such as the absolute and normalized magnitude response of individual receiver channel returns and the phase difference between receiver channels. An algorithm is developed as an unsupervised technique which classifies terrain elements based on the relationship between the orientation angle and the handedness of the transmitting and receiving polariation states. It is found that supervised classification produces the best results when accurate classifier training data are used, while unsupervised classification may be applied when training data are not available.

A modal radar cross section of thin-wire targets via the singularity expansion method

NASA Technical Reports Server (NTRS)

Richards, M. A.; Shumpert, T. H.; Riggs, L. S.

1992-01-01

A modal radar cross section (RCS) of arbitrary wire scatterers is constructed in terms of SEM parameters. Numerical results are presented for both straight and L-shaped wire targets and are compared to computations performed in the frequency domain using the method of moments.

The design and performance characteristics of a cellular logic 3-D image classification processor

NASA Astrophysics Data System (ADS)

Ankeney, L. A.

1981-04-01

The introduction of high resolution scanning laser radar systems which are capable of collecting range and reflectivity images, is predicted to significantly influence the development of processors capable of performing autonomous target classification tasks. Actively sensed range images are shown to be superior to passively collected infrared images in both image stability and information content. An illustrated tutorial introduces cellular logic (neighborhood) transformations and two and three dimensional erosion and dilation operations which are used for noise filters and geometric shape measurement. A unique 'cookbook' approach to selecting a sequence of neighborhood transformations suitable for object measurement is developed and related to false alarm rate and algorithm effectiveness measures. The cookbook design approach is used to develop an algorithm to classify objects based upon their 3-D geometrical features. A Monte Carlo performance analysis is used to demonstrate the utility of the design approach by characterizing the ability of the algorithm to classify randomly positioned three dimensional objects in the presence of additive noise, scale variations, and other forms of image distortion.

An interpretation model of GPR point data in tunnel geological prediction

NASA Astrophysics Data System (ADS)

He, Yu-yao; Li, Bao-qi; Guo, Yuan-shu; Wang, Teng-na; Zhu, Ya

2017-02-01

GPR (Ground Penetrating Radar) point data plays an absolutely necessary role in the tunnel geological prediction. However, the research work on the GPR point data is very little and the results does not meet the actual requirements of the project. In this paper, a GPR point data interpretation model which is based on WD (Wigner distribution) and deep CNN (convolutional neural network) is proposed. Firstly, the GPR point data is transformed by WD to get the map of time-frequency joint distribution; Secondly, the joint distribution maps are classified by deep CNN. The approximate location of geological target is determined by observing the time frequency map in parallel; Finally, the GPR point data is interpreted according to the classification results and position information from the map. The simulation results show that classification accuracy of the test dataset (include 1200 GPR point data) is 91.83% at the 200 iteration. Our model has the advantages of high accuracy and fast training speed, and can provide a scientific basis for the development of tunnel construction and excavation plan.

Residual translation compensations in radar target narrowband imaging based on trajectory information

NASA Astrophysics Data System (ADS)

Yue, Wenjue; Peng, Bo; Wei, Xizhang; Li, Xiang; Liao, Dongping

2018-05-01

High velocity translation will result in defocusing scattering centers in radar imaging. In this paper, we propose a Residual Translation Compensations (RTC) method based on target trajectory information to eliminate the translation effects in radar imaging. Translation could not be simply regarded as a uniformly accelerated motion in reality. So the prior knowledge of the target trajectory is introduced to enhance compensation precision. First we use the two-body orbit model to figure out the radial distance. Then, stepwise compensations are applied to eliminate residual propagation delay based on conjugate multiplication method. Finally, tomography is used to confirm the validity of the method. Compare with translation parameters estimation method based on the spectral peak of the conjugate multiplied signal, RTC method in this paper enjoys a better tomography result. When the Signal Noise Ratio (SNR) of the radar echo signal is 4dB, the scattering centers can also be extracted clearly.

Laser radar cross-section estimation from high-resolution image data.

PubMed

Osche, G R; Seeber, K N; Lok, Y F; Young, D S

1992-05-10

A methodology for the estimation of ladar cross sections from high-resolution image data of geometrically complex targets is presented. Coherent CO(2) laser radar was used to generate high-resolution amplitude imagery of a UC-8 Buffalo test aircraft at a range of 1.3 km at nine different aspect angles. The average target ladar cross section was synthesized from these data and calculated to be sigma(T) = 15.4 dBsm, which is similar to the expected microwave radar cross sections. The aspect angle dependence of the cross section shows pronounced peaks at nose on and broadside, which are also in agreement with radar results. Strong variations in both the mean amplitude and the statistical distributions of amplitude with the aspect angle have also been observed. The relative mix of diffuse and specular returns causes significant deviations from a simple Lambertian or Swerling II target, especially at broadside where large normal surfaces are present.

Multisensor data fusion for integrated maritime surveillance

NASA Astrophysics Data System (ADS)

Premji, A.; Ponsford, A. M.

1995-01-01

A prototype Integrated Coastal Surveillance system has been developed on Canada's East Coast to provide effective surveillance out to and beyond the 200 nautical mile Exclusive Economic Zone. The system has been designed to protect Canada's natural resources, and to monitor and control the coastline for smuggling, drug trafficking, and similar illegal activity. This paper describes the Multiple Sensor - Multiple Target data fusion system that has been developed. The fusion processor has been developed around the celebrated Multiple Hypothesis Tracking algorithm which accommodates multiple targets, new targets, false alarms, and missed detections. This processor performs four major functions: plot-to-track association to form individual radar tracks; fusion of radar tracks with secondary sensor reports; track identification and tagging using secondary reports; and track level fusion to form common tracks. Radar data from coherent and non-coherent radars has been used to evaluate the performance of the processor. This paper presents preliminary results.

Active Collision Avoidance for Planetary Landers

NASA Technical Reports Server (NTRS)

Rickman, Doug; Hannan, Mike; Srinivasan, Karthik

2014-01-01

Present day robotic missions to other planets require precise, a priori knowledge of the terrain to pre-determine a landing spot that is safe. Landing sites can be miles from the mission objective, or, mission objectives may be tailored to suit landing sites. Future robotic exploration missions should be capable of autonomously identifying a safe landing target within a specified target area selected by mission requirements. Such autonomous landing sites must (1) 'see' the surface, (2) identify a target, and (3) land the vehicle. Recent advances in radar technology have resulted in small, lightweight, low power radars that are used for collision avoidance and cruise control systems in automobiles. Such radar systems can be adapted for use as active hazard avoidance systems for planetary landers. The focus of this CIF proposal is to leverage earlier work on collision avoidance systems for MSFC's Mighty Eagle lander and evaluate the use of automotive radar systems for collision avoidance in planetary landers.

Three-Dimensional ISAR Imaging Method for High-Speed Targets in Short-Range Using Impulse Radar Based on SIMO Array

PubMed Central

Zhou, Xinpeng; Wei, Guohua; Wu, Siliang; Wang, Dawei

2016-01-01

This paper proposes a three-dimensional inverse synthetic aperture radar (ISAR) imaging method for high-speed targets in short-range using an impulse radar. According to the requirements for high-speed target measurement in short-range, this paper establishes the single-input multiple-output (SIMO) antenna array, and further proposes a missile motion parameter estimation method based on impulse radar. By analyzing the motion geometry relationship of the warhead scattering center after translational compensation, this paper derives the receiving antenna position and the time delay after translational compensation, and thus overcomes the shortcomings of conventional translational compensation methods. By analyzing the motion characteristics of the missile, this paper estimates the missile’s rotation angle and the rotation matrix by establishing a new coordinate system. Simulation results validate the performance of the proposed algorithm. PMID:26978372

Parameter Estimation and Image Reconstruction of Rotating Targets with Vibrating Interference in the Terahertz Band

NASA Astrophysics Data System (ADS)

Yang, Qi; Deng, Bin; Wang, Hongqiang; Qin, Yuliang

2017-07-01

Rotation is one of the typical micro-motions of radar targets. In many cases, rotation of the targets is always accompanied with vibrating interference, and it will significantly affect the parameter estimation and imaging, especially in the terahertz band. In this paper, we propose a parameter estimation method and an image reconstruction method based on the inverse Radon transform, the time-frequency analysis, and its inverse. The method can separate and estimate the rotating Doppler and the vibrating Doppler simultaneously and can obtain high-quality reconstructed images after vibration compensation. In addition, a 322-GHz radar system and a 25-GHz commercial radar are introduced and experiments on rotating corner reflectors are carried out in this paper. The results of the simulation and experiments verify the validity of the methods, which lay a foundation for the practical processing of the terahertz radar.

Automated Detection of a Crossing Contact Based on Its Doppler Shift

DTIC Science & Technology

2009-03-01

contacts in passive sonar systems. A common approach is the application of high- gain processing followed by successive classification criteria. Most...contacts in passive sonar systems. A common approach is the application of high-gain processing followed by successive classification criteria...RESEARCH MOTIVATION The trade-off between the false alarm and detection probability is fundamental in radar and sonar . (Chevalier, 2002) A common

OTH Radar Surveillance at WARF During the LRAPP Church Opal Exercise

DTIC Science & Technology

1976-11-01

UNCLASSIFIED AD NUMBER ADC010483 CLASSIFICATION CHANGES TO: unclassified FROM: secret LIMITATION CHANGES TO: Approved for public release... DDC SRI STANFORD RESEARCH INSTITUTE Menlo Park, California 94025 U.S.A.D SECRET UNCLASSIFIED The views and conclusions contained in this document are...3 SRI 6-4696 DECLASSIFIED ON 31 December 2005 SECRET (This page is UNCLASSIFIED) . ... ..... .. SECRET SECURITY CLASSIFICATION OF THIS PAGE (When

Target Tracking Using SePDAF under Ambiguous Angles for Distributed Array Radar

PubMed Central

Long, Teng; Zhang, Honggang; Zeng, Tao; Chen, Xinliang; Liu, Quanhua; Zheng, Le

2016-01-01

Distributed array radar can improve radar detection capability and measurement accuracy. However, it will suffer cyclic ambiguity in its angle estimates according to the spatial Nyquist sampling theorem since the large sparse array is undersampling. Consequently, the state estimation accuracy and track validity probability degrades when the ambiguous angles are directly used for target tracking. This paper proposes a second probability data association filter (SePDAF)-based tracking method for distributed array radar. Firstly, the target motion model and radar measurement model is built. Secondly, the fusion result of each radar’s estimation is employed to the extended Kalman filter (EKF) to finish the first filtering. Thirdly, taking this result as prior knowledge, and associating with the array-processed ambiguous angles, the SePDAF is applied to accomplish the second filtering, and then achieving a high accuracy and stable trajectory with relatively low computational complexity. Moreover, the azimuth filtering accuracy will be promoted dramatically and the position filtering accuracy will also improve. Finally, simulations illustrate the effectiveness of the proposed method. PMID:27618058

Medical applications of shortwave FM radar: remote monitoring of cardiac and respiratory motion.

PubMed

Mostov, K; Liptsen, E; Boutchko, R

2010-03-01

This article introduces the use of low power continuous wave frequency modulated radar for medical applications, specifically for remote monitoring of vital signs in patients. Gigahertz frequency radar measures the electromagnetic wave signal reflected from the surface of a human body and from tissue boundaries. Time series analysis of the measured signal provides simultaneous information on range, size, and reflective properties of multiple targets in the field of view of the radar. This information is used to extract the respiratory and cardiac rates of the patient in real time. The results from several preliminary human subject experiments are provided. The heart and respiration rate frequencies extracted from the radar signal match those measured independently for all the experiments, including a case when additional targets are simultaneously resolved in the field of view and a case when only the patient's extremity is visible to the radar antennas. Micropower continuous wave FM radar is a reliable, robust, inexpensive, and harmless tool for real-time monitoring of the cardiac and respiratory rates. Additionally, it opens a range of new and exciting opportunities in diagnostic and critical care medicine. Differences between the presented approach and other types of radars used for biomedical applications are discussed.

Applications of high-frequency radar

NASA Astrophysics Data System (ADS)

Headrick, J. M.; Thomason, J. F.

1998-07-01

Efforts to extend radar range by an order of magnitude with use of the ionosphere as a virtual mirror started after the end of World War II. A number of HF radar programs were pursued, with long-range nuclear burst and missile launch detection demonstrated by 1956. Successful east coast radar aircraft detect and track tests extending across the Atlantic were conducted by 1961. The major obstacles to success, the large target-to-clutter ratio and low signal-to-noise ratio, were overcome with matched filter Doppler processing. To search the areas that a 2000 nautical mile (3700 km) radar can reach, very complex and high dynamic range processing is required. The spectacular advances in digital processing technology have made truly wide-area surveillance possible. Use of the surface attached wave over the oceans can enable HF radar to obtain modest extension of range beyond the horizon. The decameter wavelengths used by both skywave and surface wave radars require large physical antenna apertures, but they have unique capabilities for air and surface targets, many of which are of resonant scattering dimensions. Resonant scattering from the ocean permits sea state and direction estimation. Military and commercial applications of HF radar are in their infancy.

A statistical model for radar images of agricultural scenes

NASA Technical Reports Server (NTRS)

Frost, V. S.; Shanmugan, K. S.; Holtzman, J. C.; Stiles, J. A.

1982-01-01

The presently derived and validated statistical model for radar images containing many different homogeneous fields predicts the probability density functions of radar images of entire agricultural scenes, thereby allowing histograms of large scenes composed of a variety of crops to be described. Seasat-A SAR images of agricultural scenes are accurately predicted by the model on the basis of three assumptions: each field has the same SNR, all target classes cover approximately the same area, and the true reflectivity characterizing each individual target class is a uniformly distributed random variable. The model is expected to be useful in the design of data processing algorithms and for scene analysis using radar images.

Construction and testing of a Scanning Laser Radar (SLR), phase 2

NASA Technical Reports Server (NTRS)

Flom, T.; Coombes, H. D.

1971-01-01

The scanning laser radar overall system is described. Block diagrams and photographs of the hardware are included with the system description. Detailed descriptions of all the subsystems that make up the scanning laser radar system are included. Block diagrams, photographs, and detailed optical and electronic schematics are used to help describe such subsystem hardware as the laser, beam steerer, receiver optics and detector, control and processing electronics, visual data displays, and the equipment used on the target. Tests were performed on the scanning laser radar to determine its acquisition and tracking performance and to determine its range and angle accuracies while tracking a moving target. The tests and test results are described.

Multifrequency OFDM SAR in Presence of Deception Jamming

NASA Astrophysics Data System (ADS)

Schuerger, Jonathan; Garmatyuk, Dmitriy

2010-12-01

Orthogonal frequency division multiplexing (OFDM) is considered in this paper from the perspective of usage in imaging radar scenarios with deception jamming. OFDM radar signals are inherently multifrequency waveforms, composed of a number of subbands which are orthogonal to each other. While being employed extensively in communications, OFDM has not found comparatively wide use in radar, and, particularly, in synthetic aperture radar (SAR) applications. In this paper, we aim to show the advantages of OFDM-coded radar signals with random subband composition when used in deception jamming scenarios. Two approaches to create a radar signal by the jammer are considered: instantaneous frequency (IF) estimator and digital-RF-memory- (DRFM-) based reproducer. In both cases, the jammer aims to create a copy of a valid target image via resending the radar signal at prescribed time intervals. Jammer signals are derived and used in SAR simulations with three types of signal models: OFDM, linear frequency modulated (LFM), and frequency-hopped (FH). Presented results include simulated peak side lobe (PSL) and peak cross-correlation values for random OFDM signals, as well as simulated SAR imagery with IF and DRFM jammers'-induced false targets.

Detection and identification of human targets in radar data

NASA Astrophysics Data System (ADS)

Gürbüz, Sevgi Z.; Melvin, William L.; Williams, Douglas B.

2007-04-01

Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.

Radar studies related to the earth resources program. [remote sensing programs

NASA Technical Reports Server (NTRS)

Holtzman, J.

1972-01-01

The radar systems research discussed is directed toward achieving successful application of radar to remote sensing problems in such areas as geology, hydrology, agriculture, geography, forestry, and oceanography. Topics discussed include imaging radar and evaluation of its modification, study of digital processing for synthetic aperture system, digital simulation of synthetic aperture system, averaging techniques studies, ultrasonic modeling of panchromatic system, panchromatic radar/radar spectrometer development, measuring octave-bandwidth response of selected targets, scatterometer system analysis, and a model Fresnel-zone processor for synthetic aperture imagery.

Approach to explosive hazard detection using sensor fusion and multiple kernel learning with downward-looking GPR and EMI sensor data

NASA Astrophysics Data System (ADS)

Pinar, Anthony; Masarik, Matthew; Havens, Timothy C.; Burns, Joseph; Thelen, Brian; Becker, John

2015-05-01

This paper explores the effectiveness of an anomaly detection algorithm for downward-looking ground penetrating radar (GPR) and electromagnetic inductance (EMI) data. Threat detection with GPR is challenged by high responses to non-target/clutter objects, leading to a large number of false alarms (FAs), and since the responses of target and clutter signatures are so similar, classifier design is not trivial. We suggest a method based on a Run Packing (RP) algorithm to fuse GPR and EMI data into a composite confidence map to improve detection as measured by the area-under-ROC (NAUC) metric. We examine the value of a multiple kernel learning (MKL) support vector machine (SVM) classifier using image features such as histogram of oriented gradients (HOG), local binary patterns (LBP), and local statistics. Experimental results on government furnished data show that use of our proposed fusion and classification methods improves the NAUC when compared with the results from individual sensors and a single kernel SVM classifier.

Quantitative Analysis of Radar Returns from Insects

NASA Technical Reports Server (NTRS)

Riley, J. R.

1979-01-01

When a number of flying insects is low enough to permit their resolution as individual radar targets, quantitative estimates of their aerial density are developed. Accurate measurements of heading distribution using a rotating polarization radar to enhance the wingbeat frequency method of identification are presented.

Doppler radar sensor positioning in a fall detection system.

PubMed

Liu, Liang; Popescu, Mihail; Ho, K C; Skubic, Marjorie; Rantz, Marilyn

2012-01-01

Falling is a common health problem for more than a third of the United States population over 65. We are currently developing a Doppler radar based fall detection system that already has showed promising results. In this paper, we study the sensor positioning in the environment with respect to the subject. We investigate three sensor positions, floor, wall and ceiling of the room, in two experimental configurations. Within each system configuration, subjects performed falls towards or across the radar sensors. We collected 90 falls and 341 non falls for the first configuration and 126 falls and 817 non falls for the second one. Radar signature classification was performed using a SVM classifier. Fall detection performance was evaluated using the area under the ROC curves (AUCs) for each sensor deployment. We found that a fall is more likely to be detected if the subject is falling toward or away from the sensor and a ceiling Doppler radar is more reliable for fall detection than a wall mounted one.

Phased-array radar for airborne systems

NASA Astrophysics Data System (ADS)

Tahim, Raghbir S.; Foshee, James J.; Chang, Kai

2003-09-01

Phased array antenna systems, which support high pulse rates and high transmit power, are well suited for radar and large-scale surveillance. Sensors and communication systems can function as the eyes and ears for ballistic missile defense applications, providing early warning of attack, target detection and identification, target tracking, and countermeasure decision. In such applications, active array radar systems that contain solid-state transmitter sources and low-noise preamplifiers for transmission and reception are preferred over the conventional radar antennas, because the phased array radar offers the advantages of power management and efficiency, reliability, signal reception, beam steering target detection. The current phased array radar designs are very large, complex and expensive and less efficient because of high RF losses in the phase control circuits used for beam scan. Several thousands of phase shifters and drivers may be required for a single system thus making the system very complex and expensive. This paper describes the phased array radar system based on high power T/R modules, wide-band radiating planar antenna elements and very low loss wide-band phase control circuits (requiring reduced power levels) for beam scan. The phase shifter design is based on micro-strip feed lines perturbed by the proximity of voltage controlled piezoelectric transducer (PET). Measured results have shown an added insertion loss of less than 1 dB for a phase shift of 450 degrees from 2 to 20 GHz. The new wideband phased array radar design provides significant reduction in size cost and weight. Compared to the conventional phased array systems, the cost saving is more than 15 to 1.

Detection and recognition of targets by using signal polarization properties

NASA Astrophysics Data System (ADS)

Ponomaryov, Volodymyr I.; Peralta-Fabi, Ricardo; Popov, Anatoly V.; Babakov, Mikhail F.

1999-08-01

The quality of radar target recognition can be enhanced by exploiting its polarization signatures. A specialized X-band polarimetric radar was used for target recognition in experimental investigations. The following polarization characteristics connected to the object geometrical properties were investigated: the amplitudes of the polarization matrix elements; an anisotropy coefficient; depolarization coefficient; asymmetry coefficient; the energy of a backscattering signal; object shape factor. A large quantity of polarimetric radar data was measured and processed to form a database of different object and different weather conditions. The histograms of polarization signatures were approximated by a Nakagami distribution, then used for real- time target recognition. The Neyman-Pearson criterion was used for the target detection, and the criterion of the maximum of a posterior probability was used for recognition problem. Some results of experimental verification of pattern recognition and detection of objects with different electrophysical and geometrical characteristics urban in clutter are presented in this paper.

Generalized Wideband Harmonic Imaging of Nonlinearly Loaded Scatterers: Theory, Analysis, and Application for Forward-Looking Radar Target Detection

DTIC Science & Technology

2014-09-01

signal) operations; it is general enough so that it can accommodate high - power (large-signal) sensing as well—which may be needed to detect targets... Generalized Wideband Harmonic Imaging of Nonlinearly Loaded Scatterers: Theory, Analysis, and Application for Forward-Looking Radar Target...Research Laboratory Adelphi, MD 20783-1138 ARL-TR-7121 September 2014 Generalized Wideband Harmonic Imaging of Nonlinearly Loaded

Possible methods for distinguishing icebergs from ships by aerial remote sensing

NASA Technical Reports Server (NTRS)

Howes, W. L.

1979-01-01

The simplest methods for aerial remote sensing which are least affected by atmospheric opacities are summarized. Radar is preferred for targets off the flight path, and microwave radiometry for targets along the flight path. Radar methods are classified by ability to resolve targets. Techniques which do not require target resolution are preferred. Among these techniques, polarization methods appear most promising, specifically those which differentiate the expected relatively greater depolarization by icebergs from that by ships or which detect doubly-reversed circular polarization.

Simulation of a weather radar display for over-water airborne radar approaches

NASA Technical Reports Server (NTRS)

Clary, G. R.

1983-01-01

Airborne radar approach (ARA) concepts are being investigated as a part of NASA's Rotorcraft All-Weather Operations Research Program on advanced guidance and navigation methods. This research is being conducted using both piloted simulations and flight test evaluations. For the piloted simulations, a mathematical model of the airborne radar was developed for over-water ARAs to offshore platforms. This simulated flight scenario requires radar simulation of point targets, such as oil rigs and ships, distributed sea clutter, and transponder beacon replies. Radar theory, weather radar characteristics, and empirical data derived from in-flight radar photographs are combined to model a civil weather/mapping radar typical of those used in offshore rotorcraft operations. The resulting radar simulation is realistic and provides the needed simulation capability for ongoing ARA research.

Coherent Doppler Laser Radar: Technology Development and Applications

NASA Technical Reports Server (NTRS)

Kavaya, Michael J.; Arnold, James E. (Technical Monitor)

2000-01-01

NASA's Marshall Space Flight Center has been investigating, developing, and applying coherent Doppler laser radar technology for over 30 years. These efforts have included the first wind measurement in 1967, the first airborne flights in 1972, the first airborne wind field mapping in 1981, and the first measurement of hurricane eyewall winds in 1998. A parallel effort at MSFC since 1982 has been the study, modeling and technology development for a space-based global wind measurement system. These endeavors to date have resulted in compact, robust, eyesafe lidars at 2 micron wavelength based on solid-state laser technology; in a factor of 6 volume reduction in near diffraction limited, space-qualifiable telescopes; in sophisticated airborne scanners with full platform motion subtraction; in local oscillator lasers capable of rapid tuning of 25 GHz for removal of relative laser radar to target velocities over a 25 km/s range; in performance prediction theory and simulations that have been validated experimentally; and in extensive field campaign experience. We have also begun efforts to dramatically improve the fundamental photon efficiency of the laser radar, to demonstrate advanced lower mass laser radar telescopes and scanners; to develop laser and laser radar system alignment maintenance technologies; and to greatly improve the electrical efficiency, cooling technique, and robustness of the pulsed laser. This coherent Doppler laser radar technology is suitable for high resolution, high accuracy wind mapping; for aerosol and cloud measurement; for Differential Absorption Lidar (DIAL) measurements of atmospheric and trace gases; for hard target range and velocity measurement; and for hard target vibration spectra measurement. It is also suitable for a number of aircraft operations applications such as clear air turbulence (CAT) detection; dangerous wind shear (microburst) detection; airspeed, angle of attack, and sideslip measurement; and fuel savings through headwind minimization. In addition to the airborne and space platforms, a coherent Doppler laser radar system in an unmanned aerial vehicle (UAV) could provide battlefield weather and target identification.

Geomorphology Classification of Shandong Province Based on Digital Elevation Model in the 1 Arc-second Format of Shuttle Radar Topography Mission Data

NASA Astrophysics Data System (ADS)

Fu, Jundong; Zhang, Guangcheng; Wang, Lei; Xia, Nuan

2018-01-01

Based on gigital elevation model in the 1 arc-second format of shuttle radar topography mission data, using the window analysis and mean change point analysis of geographic information system (GIS) technology, programmed with python modules this, automatically extracted and calculated geomorphic elements of Shandong province. The best access to quantitatively study area relief amplitude of statistical area. According to Chinese landscape classification standard, the landscape type in Shandong province was divided into 8 types: low altitude plain, medium altitude plain, low altitude platform, medium altitude platform, low altitude hills, medium altitude hills, low relief mountain, medium relief mountain and the percentages of Shandong province’s total area are as follows: 12.72%, 0.01%, 36.38%, 0.24%, 17.26%, 15.64%, 11.1%, 6.65%. The results of landforms are basically the same as the overall terrain of Shandong Province, Shandong province’s total area, and the study can quantitatively and scientifically provide reference for the classification of landforms in Shandong province.

Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M.; Dean, M. E.; Knowlton, D. J.; Latty, R. S.

1982-01-01

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

Remote sensing based on hyperspectral data analysis

NASA Astrophysics Data System (ADS)

Sharifahmadian, Ershad

In remote sensing, accurate identification of far objects, especially concealed objects is difficult. In this study, to improve object detection from a distance, the hyperspecral imaging and wideband technology are employed with the emphasis on wideband radar. As the wideband data includes a broad range of frequencies, it can reveal information about both the surface of the object and its content. Two main contributions are made in this study: 1) Developing concept of return loss for target detection: Unlike typical radar detection methods which uses radar cross section to detect an object, it is possible to enhance the process of detection and identification of concealed targets using the wideband radar based on the electromagnetic characteristics --conductivity, permeability, permittivity, and return loss-- of materials. During the identification process, collected wideband data is evaluated with information from wideband signature library which has already been built. In fact, several classes (e.g. metal, wood, etc.) and subclasses (ex. metals with high conductivity) have been defined based on their electromagnetic characteristics. Materials in a scene are then classified based on these classes. As an example, materials with high electrical conductivity can be conveniently detected. In fact, increasing relative conductivity leads to a reduction in the return loss. Therefore, metals with high conductivity (ex. copper) shows stronger radar reflections compared with metals with low conductivity (ex. stainless steel). Thus, it is possible to appropriately discriminate copper from stainless steel. 2) Target recognition techniques: To detect and identify targets, several techniques have been proposed, in particular the Multi-Spectral Wideband Radar Image (MSWRI) which is able to localize and identify concealed targets. The MSWRI is based on the theory of robust capon beamformer. During identification process, information from wideband signature library is utilized. The WB signature library includes such parameters as conductivity, permeability, permittivity, and return loss at different frequencies for possible materials related to a target. In the MSWRI approach, identification procedure is performed by calculating the RLs at different selected frequencies. Based on similarity of the calculated RLs and RL from WB signature library, targets are detected and identified. Based on the simulation and experimental results, it is concluded that the MSWRI technique is a promising approach for standoff target detection.

Various Effects of Embedded Intrapulse Communications on Pulsed Radar

DTIC Science & Technology

2017-06-01

specific type of interference that may be encountered by radar; however, this introductory information should suffice to illustrate to the reader why...chapter we seek to not merely understand the overall statistical performance of the radar with embedded intrapulse communications but rather to evaluate...Theory Probability of detection, discussed in Chapter 4, assesses the statistical probability of a radar accurately identifying a target given a

Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery.

PubMed

Sarkar, Anjan; Banerjee, Anjan; Banerjee, Nilanjan; Brahma, Siddhartha; Kartikeyan, B; Chakraborty, Manab; Majumder, K L

2005-05-01

This work deals with multisensor data fusion to obtain landcover classification. The role of feature-level fusion using the Dempster-Shafer rule and that of data-level fusion in the MRF context is studied in this paper to obtain an optimally segmented image. Subsequently, segments are validated and classification accuracy for the test data is evaluated. Two examples of data fusion of optical images and a synthetic aperture radar image are presented, each set having been acquired on different dates. Classification accuracies of the technique proposed are compared with those of some recent techniques in literature for the same image data.

Laser one-dimensional range profile and the laser two-dimensional range profile of cylinders

NASA Astrophysics Data System (ADS)

Gong, Yanjun; Wang, Mingjun; Gong, Lei

2015-10-01

Laser one-dimensional range profile, that is scattering power from pulse laser scattering of target, is a radar imaging technology. The laser two-dimensional range profile is two-dimensional scattering imaging of pulse laser of target. Laser one-dimensional range profile and laser two-dimensional range profile are called laser range profile(LRP). The laser range profile can reflect the characteristics of the target shape and surface material. These techniques were motivated by applications of laser radar to target discrimination in ballistic missile defense. The radar equation of pulse laser is given in this paper. This paper demonstrates the analytical model of laser range profile of cylinder based on the radar equation of the pulse laser. Simulations results of laser one-dimensional range profiles of some cylinders are given. Laser range profiles of cylinder, whose surface material with diffuse lambertian reflectance, is given in this paper. Laser range profiles of different pulse width of cylinder are given in this paper. The influences of geometric parameters, pulse width, attitude on the range profiles are analyzed.

MW 08-multi-beam air and surface surveillance radar

NASA Astrophysics Data System (ADS)

1989-09-01

Signal of the Netherlands has developed and is marketing the MW 08, a 3-D radar to be used for short to medium range surveillance, target acquisition, and tracking. MW 08 is a fully automated detecting and tracking radar. It is designed to counter threats from aircraft and low flying antiship missiles. It can also deal with the high level missile threat. MW 08 operates in the 5 cm band using one antenna for both transmitting and receiving. The antenna is an array, consisting of 8 stripline antennas. The received radar energy is processed by 8 receiver channels. These channels come together in the beam forming network, in which 8 virtual beams are formed. From this beam pattern, 6 beams are used for the elevation coverage of 0-70 degrees. MW 08's output signals of the beam former are further handled by FFT and plot processors for target speed information, clutter rejection, and jamming suppression. A general purpose computer handles target track initiation, and tracking. Tracking data are transferred to the command and control systems with 3-D target information for fastest possible lockon.

Automatic Focusing for a 675 GHz Imaging Radar with Target Standoff Distances from 14 to 34 Meters

NASA Technical Reports Server (NTRS)

Tang, Adrian; Cooper, Ken B.; Dengler, Robert J.; Llombart, Nuria; Siegel, Peter H.

2013-01-01

This paper dicusses the issue of limited focal depth for high-resolution imaging radar operating over a wide range of standoff distances. We describe a technique for automatically focusing a THz imaging radar system using translational optics combined with range estimation based on a reduced chirp bandwidth setting. The demonstarted focusing algorithm estimates the correct focal depth for desired targets in the field of view at unknown standoffs and in the presence of clutter to provide good imagery at 14 to 30 meters of standoff.

Fpga based L-band pulse doppler radar design and implementation

NASA Astrophysics Data System (ADS)

Savci, Kubilay

As its name implies RADAR (Radio Detection and Ranging) is an electromagnetic sensor used for detection and locating targets from their return signals. Radar systems propagate electromagnetic energy, from the antenna which is in part intercepted by an object. Objects reradiate a portion of energy which is captured by the radar receiver. The received signal is then processed for information extraction. Radar systems are widely used for surveillance, air security, navigation, weather hazard detection, as well as remote sensing applications. In this work, an FPGA based L-band Pulse Doppler radar prototype, which is used for target detection, localization and velocity calculation has been built and a general-purpose Pulse Doppler radar processor has been developed. This radar is a ground based stationary monopulse radar, which transmits a short pulse with a certain pulse repetition frequency (PRF). Return signals from the target are processed and information about their location and velocity is extracted. Discrete components are used for the transmitter and receiver chain. The hardware solution is based on Xilinx Virtex-6 ML605 FPGA board, responsible for the control of the radar system and the digital signal processing of the received signal, which involves Constant False Alarm Rate (CFAR) detection and Pulse Doppler processing. The algorithm is implemented in MATLAB/SIMULINK using the Xilinx System Generator for DSP tool. The field programmable gate arrays (FPGA) implementation of the radar system provides the flexibility of changing parameters such as the PRF and pulse length therefore it can be used with different radar configurations as well. A VHDL design has been developed for 1Gbit Ethernet connection to transfer digitized return signal and detection results to PC. An A-Scope software has been developed with C# programming language to display time domain radar signals and detection results on PC. Data are processed both in FPGA chip and on PC. FPGA uses fixed point arithmetic operations as it is fast and facilitates source requirement as it consumes less hardware than floating point arithmetic operations. The software uses floating point arithmetic operations, which ensure precision in processing at the expense of speed. The functionality of the radar system has been tested for experimental validation in the field with a moving car and the validation of submodules are tested with synthetic data simulated on MATLAB.

Combined use of SAR and optical data for environmental assessments around refugee camps in semiarid landscapes

NASA Astrophysics Data System (ADS)

Braun, A.; Hochschild, V.

2015-04-01

Over 15 million people were officially considered as refugees in the year 2012 and another 28 million as internally displaced people (IDPs). Natural disasters, climatic and environmental changes, violent regional conflicts and population growth force people to migrate in all parts of this world. This trend is likely to continue in the near future, as political instabilities increase and land degradation progresses. EO4HumEn aims at developing operational services to support humanitarian operations during crisis situations by means of dedicated geo-spatial information products derived from Earth observation and GIS data. The goal is to develop robust, automated methods of image analysis routines for population estimation, identification of potential groundwater extraction sites and monitoring the environmental impact of refugee/IDP camps. This study investigates the combination of satellite SAR data with optical sensors and elevation information for the assessment of the environmental conditions around refugee camps. In order to estimate their impact on land degradation, land cover classifications are required which target dynamic landscapes. We performed a land use / land cover classification based on a random forest algorithm and 39 input prediction rasters based on Landsat 8 data and additional layers generated from radar texture and elevation information. The overall accuracy was 92.9 %, while optical data had the highest impact on the final classification. By analysing all combinations of the three input datasets we additionally estimated their impact on single classification outcomes and land cover classes.

Preliminary results of the comparative study between EO-1/Hyperion and ALOS/PALSAR

NASA Astrophysics Data System (ADS)

Koizumi, E.; Furuta, R.; Yamamoto, A.

2011-12-01

[Introduction]Hyper-spectral remote sensing images have been used for land-cover classification due to their high spectral resolutions. Synthetic Aperture Radar (SAR) remote sensing data are also useful to probe surface condition because radar image reflects surface geometry, although there are not so many reports about the land-cover detection with combination use of both hyper-spectral data and SAR data. Among SAR sensors, L-band SAR is thought to be useful tool to find physical properties because its comparatively long wave length can through small objects on surface. We are comparing the result of land cover classification and/or physical values from hyper-spectral and L-band SAR data to find the relationship between these two quite different sensors and to confirm the possibility of the combined analysis of hyper-spectral and L-band SAR data, and in this presentation we will report the preliminary result of this study. There are only few sources of both hyper-spectral and L-band SAR data from the space in this time, however, several space organizations plan to launch new satellites on which hyper-spectral or L-band SAR equipments are mounted in next few years. So, the importance of the combined analysis will increase more than ever. [Target Area]We are performing and planning analyses on the following areas in this study. (a)South of Cairo, Nile river area, Egypt, for sand, sandstone, limestone, river, crops. (b)Mount Sakurajima, Japan, for igneous rock and other related geological property. [Methods and Results]EO-1 Hyperion data are analyzed in this study as hyper-spectral data. The Hyperion equipment has 242 channels but some of them include full noise or have no data. We selected channels for analysis by checking each channel, and select about 150 channels (depend on the area). Before analysis, the atmospheric correction of ATCOR-3 was applied for the selected channels. The corrected data were analyzed by unsupervised classification or principal component analysis (PCA). We also did the unsupervised classification with the several components from PCA. According to the analysis results, several classifications can be extracted for each category (vegetation, sand and rocks, and water). One of the interesting results is that there are a few classes for sand as those of other categories, and these classes seem to reflect artificial and natural surface changes that are some result of excavation or scratching. ALOS PALSAR data are analyzed as L-band SAR data. We selected the Dual Polarization data for each target area. The data were converted to backscattered images, and then calculated some image statistic values. The topographic information also calculates with SAR interferometry technique as reference. Comparing the Hyperion classification results with the result of the calculation of statistic values from PALSAR, there are some areas where relativities seem to be confirmed. To confirm the combined analysis between hyper-spectral and L-band SAR data to detect and classify the surface material, further studies are still required. We will continue to investigate more efficient analytic methods and to examine other functions like the adopted channels, the number of class in classification, the kind of statistic information, and so on, to refine the method.

Road-Aided Ground Slowly Moving Target 2D Motion Estimation for Single-Channel Synthetic Aperture Radar.

PubMed

Wang, Zhirui; Xu, Jia; Huang, Zuzhen; Zhang, Xudong; Xia, Xiang-Gen; Long, Teng; Bao, Qian

2016-03-16

To detect and estimate ground slowly moving targets in airborne single-channel synthetic aperture radar (SAR), a road-aided ground moving target indication (GMTI) algorithm is proposed in this paper. First, the road area is extracted from a focused SAR image based on radar vision. Second, after stationary clutter suppression in the range-Doppler domain, a moving target is detected and located in the image domain via the watershed method. The target's position on the road as well as its radial velocity can be determined according to the target's offset distance and traffic rules. Furthermore, the target's azimuth velocity is estimated based on the road slope obtained via polynomial fitting. Compared with the traditional algorithms, the proposed method can effectively cope with slowly moving targets partly submerged in a stationary clutter spectrum. In addition, the proposed method can be easily extended to a multi-channel system to further improve the performance of clutter suppression and motion estimation. Finally, the results of numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm.

Contribution of Small-Scale Correlated Fluctuations of Microstructural Properties of a Spatially Extended Geophysical Target Under the Assessment of Radar Backscatter

NASA Technical Reports Server (NTRS)

Yurchak, Boris S.

2010-01-01

The study of the collective effects of radar scattering from an aggregation of discrete scatterers randomly distributed in a space is important for better understanding the origin of the backscatter from spatially extended geophysical targets (SEGT). We consider the microstructure irregularities of a SEGT as the essential factor that affect radar backscatter. To evaluate their contribution this study uses the "slice" approach: particles close to the front of incident radar wave are considered to reflect incident electromagnetic wave coherently. The radar equation for a SEGT is derived. The equation includes contributions to the total backscatter from correlated small-scale fluctuations of the slice's reflectivity. The correlation contribution changes in accordance with an earlier proposed idea by Smith (1964) based on physical consideration. The slice approach applied allows parameterizing the features of the SEGT's inhomogeneities.

A wavefront reconstruction method for 3-D cylindrical subsurface radar imaging.

PubMed

Flores-Tapia, Daniel; Thomas, Gabriel; Pistorius, Stephen

2008-10-01

In recent years, the use of radar technology has been proposed in a wide range of subsurface imaging applications. Traditionally, linear scan trajectories are used to acquire data in most subsurface radar applications. However, novel applications, such as breast microwave imaging and wood inspection, require the use of nonlinear scan trajectories in order to adjust to the geometry of the scanned area. This paper proposes a novel reconstruction algorithm for subsurface radar data acquired along cylindrical scan trajectories. The spectrum of the collected data is processed in order to locate the spatial origin of the target reflections and remove the spreading of the target reflections which results from the different signal travel times along the scan trajectory. The proposed algorithm was successfully tested using experimental data collected from phantoms that mimic high contrast subsurface radar scenarios, yielding promising results. Practical considerations such as spatial resolution and sampling constraints are discussed and illustrated as well.

Correction of amplitude-phase distortion for polarimetric active radar calibrator

NASA Astrophysics Data System (ADS)

Lin, Jianzhi; Li, Weixing; Zhang, Yue; Chen, Zengping

2015-01-01

The polarimetric active radar calibrator (PARC) is extensively used as an external test target for system distortion compensation and polarimetric calibration for the high-resolution polarimetric radar. However, the signal undergoes distortion in the PARC, affecting the effectiveness of the compensation and the calibration. The system distortion compensation resulting from the distortion of the amplitude and phase in the PARC was analyzed based on the "method of paired echoes." Then the correction method was proposed, which separated the ideal signals from the distorted signals. Experiments were carried on real radar data, and the experimental results were in good agreement with the theoretical analysis. After the correction, the PARC can be better used as an external test target for the system distortion compensation.

Radar based autonomous sensor module

NASA Astrophysics Data System (ADS)

Styles, Tim

2016-10-01

Most surveillance systems combine camera sensors with other detection sensors that trigger an alert to a human operator when an object is detected. The detection sensors typically require careful installation and configuration for each application and there is a significant burden on the operator to react to each alert by viewing camera video feeds. A demonstration system known as Sensing for Asset Protection with Integrated Electronic Networked Technology (SAPIENT) has been developed to address these issues using Autonomous Sensor Modules (ASM) and a central High Level Decision Making Module (HLDMM) that can fuse the detections from multiple sensors. This paper describes the 24 GHz radar based ASM, which provides an all-weather, low power and license exempt solution to the problem of wide area surveillance. The radar module autonomously configures itself in response to tasks provided by the HLDMM, steering the transmit beam and setting range resolution and power levels for optimum performance. The results show the detection and classification performance for pedestrians and vehicles in an area of interest, which can be modified by the HLDMM without physical adjustment. The module uses range-Doppler processing for reliable detection of moving objects and combines Radar Cross Section and micro-Doppler characteristics for object classification. Objects are classified as pedestrian or vehicle, with vehicle sub classes based on size. Detections are reported only if the object is detected in a task coverage area and it is classified as an object of interest. The system was shown in a perimeter protection scenario using multiple radar ASMs, laser scanners, thermal cameras and visible band cameras. This combination of sensors enabled the HLDMM to generate reliable alerts with improved discrimination of objects and behaviours of interest.

Calibration of quadpolarization SAR data using backscatter statistics

NASA Technical Reports Server (NTRS)

Klein, Jeffrey D.

1989-01-01

A new technique is described for calibration of complex multipolarization SAR imagery. Scatterer reciprocity and lack of correlation between like- and cross-polarized radar echoes for natural targets are used to remove cross-polarized contamination in the radar data channels without the use of known ground targets. If known targets are available, all data channels can be calibrated relative to one another and absolutely as well. The method is verified with airborne SAR data.

Location detection and tracking of moving targets by a 2D IR-UWB radar system.

PubMed

Nguyen, Van-Han; Pyun, Jae-Young

2015-03-19

In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking.

Terrain detection and classification using single polarization SAR

DOEpatents

Chow, James G.; Koch, Mark W.

2016-01-19

The various technologies presented herein relate to identifying manmade and/or natural features in a radar image. Two radar images (e.g., single polarization SAR images) can be captured for a common scene. The first image is captured at a first instance and the second image is captured at a second instance, whereby the duration between the captures are of sufficient time such that temporal decorrelation occurs for natural surfaces in the scene, and only manmade surfaces, e.g., a road, produce correlated pixels. A LCCD image comprising the correlated and decorrelated pixels can be generated from the two radar images. A median image can be generated from a plurality of radar images, whereby any features in the median image can be identified. A superpixel operation can be performed on the LCCD image and the median image, thereby enabling a feature(s) in the LCCD image to be classified.

Development Of Polarimetric Decomposition Techniques For Indian Forest Resource Assessment Using Radar Imaging Satellite (Risat-1) Images

NASA Astrophysics Data System (ADS)

Sridhar, J.

2015-12-01

The focus of this work is to examine polarimetric decomposition techniques primarily focussed on Pauli decomposition and Sphere Di-Plane Helix (SDH) decomposition for forest resource assessment. The data processing methods adopted are Pre-processing (Geometric correction and Radiometric calibration), Speckle Reduction, Image Decomposition and Image Classification. Initially to classify forest regions, unsupervised classification was applied to determine different unknown classes. It was observed K-means clustering method gave better results in comparison with ISO Data method.Using the algorithm developed for Radar Tools, the code for decomposition and classification techniques were applied in Interactive Data Language (IDL) and was applied to RISAT-1 image of Mysore-Mandya region of Karnataka, India. This region is chosen for studying forest vegetation and consists of agricultural lands, water and hilly regions. Polarimetric SAR data possess a high potential for classification of earth surface.After applying the decomposition techniques, classification was done by selecting region of interests andpost-classification the over-all accuracy was observed to be higher in the SDH decomposed image, as it operates on individual pixels on a coherent basis and utilises the complete intrinsic coherent nature of polarimetric SAR data. Thereby, making SDH decomposition particularly suited for analysis of high-resolution SAR data. The Pauli Decomposition represents all the polarimetric information in a single SAR image however interpretation of the resulting image is difficult. The SDH decomposition technique seems to produce better results and interpretation as compared to Pauli Decomposition however more quantification and further analysis are being done in this area of research. The comparison of Polarimetric decomposition techniques and evolutionary classification techniques will be the scope of this work.

Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data

NASA Astrophysics Data System (ADS)

Jiao, Xianfeng; Kovacs, John M.; Shang, Jiali; McNairn, Heather; Walters, Dan; Ma, Baoluo; Geng, Xiaoyuan

2014-10-01

The aim of this paper is to assess the accuracy of an object-oriented classification of polarimetric Synthetic Aperture Radar (PolSAR) data to map and monitor crops using 19 RADARSAT-2 fine beam polarimetric (FQ) images of an agricultural area in North-eastern Ontario, Canada. Polarimetric images and field data were acquired during the 2011 and 2012 growing seasons. The classification and field data collection focused on the main crop types grown in the region, which include: wheat, oat, soybean, canola and forage. The polarimetric parameters were extracted with PolSAR analysis using both the Cloude-Pottier and Freeman-Durden decompositions. The object-oriented classification, with a single date of PolSAR data, was able to classify all five crop types with an accuracy of 95% and Kappa of 0.93; a 6% improvement in comparison with linear-polarization only classification. However, the time of acquisition is crucial. The larger biomass crops of canola and soybean were most accurately mapped, whereas the identification of oat and wheat were more variable. The multi-temporal data using the Cloude-Pottier decomposition parameters provided the best classification accuracy compared to the linear polarizations and the Freeman-Durden decomposition parameters. In general, the object-oriented classifications were able to accurately map crop types by reducing the noise inherent in the SAR data. Furthermore, using the crop classification maps we were able to monitor crop growth stage based on a trend analysis of the radar response. Based on field data from canola crops, there was a strong relationship between the phenological growth stage based on the BBCH scale, and the HV backscatter and entropy.

Analysis of a digital RF memory in a signal-delay application

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

Jelinek, D.A.

1992-03-01

Laboratory simulation of the approach of a radar fuze towards a target is an important factor in our ability to accurately measure the radar`s performance. This simulation is achieved, in part, by dynamically delaying and attenuating the radar`s transmitted pulse and sending the result back to the radar`s receiver. Historically, the device used to perform the dynamic delay has been a limiting factor in the evaluation of a radar`s performance and characteristics. A new device has been proposed that appears to have more capability than previous dynamic delay devices. This device is the digital RF memory. This report presents themore » results of an analysis of a digital RF memory used in a signal-delay application. 2 refs.« less

A low-cost through-the-wall FMCW radar for stand-off operation and activity detection

NASA Astrophysics Data System (ADS)

Chetty, Kevin; Chen, Qingchao; Ritchie, Matthew; Woodbridge, Karl

2017-05-01

In this paper we present a new through-wall (TW) FMCW radar system. The architecture of the radar enables both high sensitivity and range resolutions of <1.5 m. Moreover, the radar employs moving target indication (MTI) signal processing to remove the problematic primary wall reflection, allowing higher signal-to- noise and signal-to-interference ratios, which can be traded-off for increased operational stand-off. The TW radar operates at 5.8 GHz with a 200 MHz bandwidth. Its dual-frequency design minimises interference from signal leakage, and permits a baseband output after deramping which is digitized using an inexpensive 24-bit off-the-shelf sound card. The system is therefore an order of magnitude lower in cost than competitor ultrawideband (UWB) TW systems. The high sensitivity afforded by this wide dynamic range has allowed us to develop a wall removal technique whereby high-order digital filters provide a flexible means of MTI filtering based on the phases of the returned echoes. Experimental data demonstrates through-wall detection of individuals and groups of people in various scenarios. Target positions were located to within +/-1.25 m in range, allowing us distinguish between two closely separated targets. Furthermore, at 8.5 m standoff, our wall removal technique can recover target responses that would have otherwise been masked by the primary wall reflection, thus increasing the stand-off capability of the radar. Using phase processing, our experimental data also reveals a clear difference in the micro-Doppler signatures across various types of everyday actions

Compound Radar Approach for Breast Imaging.

PubMed

Byrne, Dallan; Sarafianou, Mantalena; Craddock, Ian J

2017-01-01

Multistatic radar apertures record scattering at a number of receivers when the target is illuminated by a single transmitter, providing more scattering information than its monostatic counterpart per transmission angle. This paper considers the well-known problem of detecting tumor targets within breast phantoms using multistatic radar. To accurately image potentially cancerous targets size within the breast, a significant number of multistatic channels are required in order to adequately calibrate-out unwanted skin reflections, increase the immunity to clutter, and increase the dynamic range of a breast radar imaging system. However, increasing the density of antennas within a physical array is inevitably limited by the geometry of the antenna elements designed to operate with biological tissues at microwave frequencies. A novel compound imaging approach is presented to overcome these physical constraints and improve the imaging capabilities of a multistatic radar imaging modality for breast scanning applications. The number of transmit-receive (TX-RX) paths available for imaging are increased by performing a number of breast scans with varying array positions. A skin calibration method is presented to reduce the influence of skin reflections from each channel. Calibrated signals are applied to receive a beamforming method, compounding the data from each scan to produce a microwave radar breast profile. The proposed imaging method is evaluated with experimental data obtained from constructed phantoms of varying complexity, skin contour asymmetries, and challenging tumor positions and sizes. For each imaging scenario outlined in this study, the proposed compound imaging technique improves skin calibration, clearly detects small targets, and substantially reduces the level of undesirable clutter within the profile.

GPR Imaging for Deeply Buried Objects: A Comparative Study Based on FDTD Models and Field Experiments

NASA Technical Reports Server (NTRS)

Tilley, roger; Dowla, Farid; Nekoogar, Faranak; Sadjadpour, Hamid

2012-01-01

Conventional use of Ground Penetrating Radar (GPR) is hampered by variations in background environmental conditions, such as water content in soil, resulting in poor repeatability of results over long periods of time when the radar pulse characteristics are kept the same. Target objects types might include voids, tunnels, unexploded ordinance, etc. The long-term objective of this work is to develop methods that would extend the use of GPR under various environmental and soil conditions provided an optimal set of radar parameters (such as frequency, bandwidth, and sensor configuration) are adaptively employed based on the ground conditions. Towards that objective, developing Finite Difference Time Domain (FDTD) GPR models, verified by experimental results, would allow us to develop analytical and experimental techniques to control radar parameters to obtain consistent GPR images with changing ground conditions. Reported here is an attempt at developing 20 and 3D FDTD models of buried targets verified by two different radar systems capable of operating over different soil conditions. Experimental radar data employed were from a custom designed high-frequency (200 MHz) multi-static sensor platform capable of producing 3-D images, and longer wavelength (25 MHz) COTS radar (Pulse EKKO 100) capable of producing 2-D images. Our results indicate different types of radar can produce consistent images.

Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy

NASA Astrophysics Data System (ADS)

Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

2017-08-01

Distributed radar network systems have been shown to have many unique features. Due to their advantage of signal and spatial diversities, radar networks are attractive for target detection. In practice, the netted radars in radar networks are supposed to maximize their transmit power to achieve better detection performance, which may be in contradiction with low probability of intercept (LPI). Therefore, this paper investigates the problem of adaptive power allocation for radar networks in a cooperative game-theoretic framework such that the LPI performance can be improved. Taking into consideration both the transmit power constraints and the minimum signal to interference plus noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game based on LPI is formulated, whose objective is to minimize the total transmit power by optimizing the power allocation in radar networks. First, a novel SINR-based network utility function is defined and utilized as a metric to evaluate power allocation. Then, with the well-designed network utility function, the existence and uniqueness of the Nash bargaining solution are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Numerical simulations and theoretic analysis are provided to evaluate the effectiveness of the proposed algorithm.

Using Radar, Lidar, and Radiometer measurements to Classify Cloud Type and Study Middle-Level Cloud Properties

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

Wang, Zhien

2010-06-29

The project is mainly focused on the characterization of cloud macrophysical and microphysical properties, especially for mixed-phased clouds and middle level ice clouds by combining radar, lidar, and radiometer measurements available from the ACRF sites. First, an advanced mixed-phase cloud retrieval algorithm will be developed to cover all mixed-phase clouds observed at the ACRF NSA site. The algorithm will be applied to the ACRF NSA observations to generate a long-term arctic mixed-phase cloud product for model validations and arctic mixed-phase cloud processes studies. To improve the representation of arctic mixed-phase clouds in GCMs, an advanced understanding of mixed-phase cloud processesmore » is needed. By combining retrieved mixed-phase cloud microphysical properties with in situ data and large-scale meteorological data, the project aim to better understand the generations of ice crystals in supercooled water clouds, the maintenance mechanisms of the arctic mixed-phase clouds, and their connections with large-scale dynamics. The project will try to develop a new retrieval algorithm to study more complex mixed-phase clouds observed at the ACRF SGP site. Compared with optically thin ice clouds, optically thick middle level ice clouds are less studied because of limited available tools. The project will develop a new two wavelength radar technique for optically thick ice cloud study at SGP site by combining the MMCR with the W-band radar measurements. With this new algorithm, the SGP site will have a better capability to study all ice clouds. Another area of the proposal is to generate long-term cloud type classification product for the multiple ACRF sites. The cloud type classification product will not only facilitates the generation of the integrated cloud product by applying different retrieval algorithms to different types of clouds operationally, but will also support other research to better understand cloud properties and to validate model simulations. The ultimate goal is to improve our cloud classification algorithm into a VAP.« less

Development of the Soil Moisture Active Passive (SMAP) radiometer derived landscape freeze/thaw product

NASA Astrophysics Data System (ADS)

Colliander, A.; Xu, X.; Dunbar, R. S.; Derksen, C.; Kim, Y.; Kimball, J. S.

2016-12-01

A baseline SMAP mission objective was to determine the land surface binary freeze/thaw (FT) state for northern (>45°N) regions with 80% spatial classification accuracy at 3 km resolution and 2-day average intervals. These requirements were initially achieved from the SMAP radar until the sensor failed in July 2015. The FT algorithm is now transitioning to using SMAP radiometer inputs. The main compromises of this change are a coarse (36 km) radiometer footprint, enhanced noise and potential FT signal degradation from seasonal vegetation biomass, soil moisture and surface inundation changes. The new daily passive FT product (L3_FT_P) is based on the same seasonal threshold algorithm as the radar derived product (L3_FT_A): instantaneous SMAP measurements are compared to reference signatures acquired during seasonal frozen and thawed states. Instead of radar inputs, the normalized polarization ratio (NPR) is calculated from SMAP radiometer measurements. The L3_FT_P algorithm is applied using NPR inputs, whereby NPR decreases and increases are associated with respective landscape freezing and thawing. A lower NPR under frozen conditions is due to smaller V-pol brightness temperature increases and larger H-pol increases. Using in situ measurements from core validation sites, the temporal behavior of backscatter and NPR measurements were evaluated during the spring 2015 radar and radiometer overlap period. The transition from frozen to thawed states produced a NPR response similar in timing and magnitude to the radar response, resulting in similar freeze to thaw seasonal transition dates. While the post-thaw radar backscatter consistently remained at elevated values relative to the frozen state, the NPR drifted downwards following the main thaw transition (due to de-polarization of the scene), which may introduce false freeze classification errors. Both radar and radiometer results tended to lead observed soil thawing due to strong sensitivity of the microwave retrievals to wet snow. Continued analysis of SMAP radiometer measurements will help to identify different landscape components of the SMAP freeze-thaw temporal signal.

Quad-polarized synthetic aperture radar and multispectral data classification using classification and regression tree and support vector machine-based data fusion system

NASA Astrophysics Data System (ADS)

Bigdeli, Behnaz; Pahlavani, Parham

2017-01-01

Interpretation of synthetic aperture radar (SAR) data processing is difficult because the geometry and spectral range of SAR are different from optical imagery. Consequently, SAR imaging can be a complementary data to multispectral (MS) optical remote sensing techniques because it does not depend on solar illumination and weather conditions. This study presents a multisensor fusion of SAR and MS data based on the use of classification and regression tree (CART) and support vector machine (SVM) through a decision fusion system. First, different feature extraction strategies were applied on SAR and MS data to produce more spectral and textural information. To overcome the redundancy and correlation between features, an intrinsic dimension estimation method based on noise-whitened Harsanyi, Farrand, and Chang determines the proper dimension of the features. Then, principal component analysis and independent component analysis were utilized on stacked feature space of two data. Afterward, SVM and CART classified each reduced feature space. Finally, a fusion strategy was utilized to fuse the classification results. To show the effectiveness of the proposed methodology, single classification on each data was compared to the obtained results. A coregistered Radarsat-2 and WorldView-2 data set from San Francisco, USA, was available to examine the effectiveness of the proposed method. The results show that combinations of SAR data with optical sensor based on the proposed methodology improve the classification results for most of the classes. The proposed fusion method provided approximately 93.24% and 95.44% for two different areas of the data.

5. Photocopy of photograph showing target tracking radar from 'Procedures ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. Photocopy of photograph showing target tracking radar from 'Procedures and Drills for the NIKE Hercules Missile Battery,' Department of the Army Field Manual, FM-44-82 from Institute for Military History, Carlisle Barracks, Carlisle, PA, 1959 - NIKE Missile Battery PR-79, East Windsor Road south of State Route 101, Foster, Providence County, RI

Fusion of AIRSAR and TM Data for Parameter Classification and Estimation in Dense and Hilly Forests

NASA Technical Reports Server (NTRS)

Moghaddam, Mahta; Dungan, J. L.; Coughlan, J. C.

2000-01-01

The expanded remotely sensed data space consisting of coincident radar backscatter and optical reflectance data provides for a more complete description of the Earth surface. This is especially useful where many parameters are needed to describe a certain scene, such as in the presence of dense and complex-structured vegetation or where there is considerable underlying topography. The goal of this paper is to use a combination of radar and optical data to develop a methodology for parameter classification for dense and hilly forests, and further, class-specific parameter estimation. The area to be used in this study is the H. J. Andrews Forest in Oregon, one of the Long-Term Ecological Research (LTER) sites in the US. This area consists of various dense old-growth conifer stands, and contains significant topographic relief. The Andrews forest has been the subject of many ecological studies over several decades, resulting in an abundance of ground measurements. Recently, biomass and leaf-area index (LAI) values for approximately 30 reference stands have also become available which span a large range of those parameters. The remote sensing data types to be used are the C-, L-, and P-band polarimetric radar data from the JPL airborne SAR (AIRSAR), the C-band single-polarization data from the JPL topographic SAR (TOPSAR), and the Thematic Mapper (TM) data from Landsat, all acquired in late April 1998. The total number of useful independent data channels from the AIRSAR is 15 (three frequencies, each with three unique polarizations and amplitude and phase of the like-polarized correlation), from the TOPSAR is 2 (amplitude and phase of the interferometric correlation), and from the TM is 6 (the thermal band is not used). The range pixel spacing of the AIRSAR is 3.3m for C- and L-bands and 6.6m for P-band. The TOPSAR pixel spacing is 10m, and the TM pixel size is 30m. To achieve parameter classification, first a number of parameters are defined which are of interest to ecologists for forest process modeling. These parameters include total biomass, leaf biomass, LAI, and tree height. The remote sensing data from radar and TM are used to formulate a multivariate analysis problem given the ground measurements of the parameters. Each class of each parameter is defined by a probability density function (pdf), the spread of which defines the range of that class. High classification accuracy results from situations in which little overlap occurs between pdfs. Classification results provide the basis for the future work of class-specific parameter estimation using radar and optical data. This work was performed in part by the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, and in part by the NASA Ames Research Center, Moffett Field, CA, both under contract from the National Aeronautics and Space Administration.

Passive synthetic aperture radar imaging of ground moving targets

NASA Astrophysics Data System (ADS)

Wacks, Steven; Yazici, Birsen

2012-05-01

In this paper we present a method for imaging ground moving targets using passive synthetic aperture radar. A passive radar imaging system uses small, mobile receivers that do not radiate any energy. For these reasons, passive imaging systems result in signicant cost, manufacturing, and stealth advantages. The received signals are obtained by multiple airborne receivers collecting scattered waves due to illuminating sources of opportunity such as commercial television, radio, and cell phone towers. We describe a novel forward model and a corresponding ltered-backprojection type image reconstruction method combined with entropy optimization. Our method determines the location and velocity of multiple targets moving at dierent velocities. Furthermore, it can accommodate arbitrary imaging geometries. we present numerical simulations to verify the imaging method.

New observations of Bolivian wind streaks by JPL Airborne SAR: Preliminary results

NASA Technical Reports Server (NTRS)

Blumberg, Dan G.; Greeley, Ronald

1995-01-01

In 1993 NASA's Jet Propulsion Laboratory Airborne Synthetic Aperture Radar system (AIRSAR) was deployed to South America to collect multi-parameter radar data over pre-selected targets. Among the sites targeted was a series of wind streaks located in the Altiplano of Bolivia. The objective of this investigation is to study the effect of wavelength, polarization, and incidence angle on the visibility of wind streaks in radar data. Because this is a preliminary evaluation of the recently acquired data we will focus on one scene and, thus, only on the effects of wavelength and polarization. Wind streaks provide information on the near-surface prevailing winds and on the abundance of winderodible material, such as sand. The potential for a free-flyer radar system that could provide global radar images in multiple wavelengths, polarizations, and incidence angles requires definition of system parameters for mission planning. Furthermore, thousands of wind streaks were mapped from Magellan radar images of Venus; their interpretation requires an understanding of the interaction of radar with wind streaks and the surrounding terrain. Our experiment was conducted on wind streaks in the Altiplano of Bolivia to address these issues.

High resolution frequency to time domain transformations applied to the stepped carrier MRIS measurements

NASA Technical Reports Server (NTRS)

Ardalan, Sasan H.

1992-01-01

Two narrow-band radar systems are developed for high resolution target range estimation in inhomogeneous media. They are reformulations of two presently existing systems such that high resolution target range estimates may be achieved despite the use of narrow bandwidth radar pulses. A double sideband suppressed carrier radar technique originally derived in 1962, and later abandoned due to its inability to accurately measure target range in the presence of an interfering reflection, is rederived to incorporate the presence of an interfering reflection. The new derivation shows that the interfering reflection causes a period perturbation in the measured phase response. A high resolution spectral estimation technique is used to extract the period of this perturbation leading to accurate target range estimates independent of the signal-to-interference ratio. A non-linear optimal signal processing algorithm is derived for a frequency-stepped continuous wave radar system. The resolution enhancement offered by optimal signal processing of the data over the conventional Fourier Transform technique is clearly demonstrated using measured radar data. A method for modeling plane wave propagation in inhomogeneous media based on transmission line theory is derived and studied. Several simulation results including measurement of non-uniform electron plasma densities that develop near the heat tiles of a space re-entry vehicle are presented which verify the validity of the model.

Ultrawideband radar; Proceedings of the Meeting, Los Angeles, CA, Jan. 22, 23, 1992

NASA Astrophysics Data System (ADS)

Lahaie, Ivan J.

1992-05-01

The present conference discusses a canonical representation of the radar range equation in the time domain, two-way beam patterns fron ultrawideband arrays, modeling of ultrawideband sea clutter, the analysis of time-domain ultrawideband radar signals, a frequency-agile ultrawideband microwave source, and the performance of ultrawideband antennas. Also discussed are the diffraction of ultrawideband radar pulses, sea-clutter measurements with an ultrawideband X-band radar having variable resolution, results from a VHF-impulse SAR, an ultrawideband differential radar, the development of 2D target images from ultrawideband radar systems, ultrawideband generators, and the radiated waveform of a monolithic photoconductive GaAs pulser. (For individual items see A93-28202 to A93-28223)

Solid-state coherent laser radar wind shear measuring systems

NASA Technical Reports Server (NTRS)

Huffaker, R. Milton

1992-01-01

Coherent Technologies, Inc. (CTI) was established in 1984 to engage in the development of coherent laser radar systems and subsystems with applications in atmospheric remote sensing, and in target tracking, ranging and imaging. CTI focuses its capabilities in three major areas: (1) theoretical performance and design of coherent laser radar system; (2) development of coherent laser radar systems for government agencies such as DoD and NASA; and (3) development of coherent laser radar systems for commercial markets. The topics addressed are: (1) 1.06 micron solid-state coherent laser radar system; (2) wind measurement using 1.06 micron system; and flashlamp-pumped 2.09 micron solid-state coherent laser radar system.

Identification of sea ice types in spaceborne synthetic aperture radar data

NASA Technical Reports Server (NTRS)

Kwok, Ronald; Rignot, Eric; Holt, Benjamin; Onstott, R.

1992-01-01

This study presents an approach for identification of sea ice types in spaceborne SAR image data. The unsupervised classification approach involves cluster analysis for segmentation of the image data followed by cluster labeling based on previously defined look-up tables containing the expected backscatter signatures of different ice types measured by a land-based scatterometer. Extensive scatterometer observations and experience accumulated in field campaigns during the last 10 yr were used to construct these look-up tables. The classification approach, its expected performance, the dependence of this performance on radar system performance, and expected ice scattering characteristics are discussed. Results using both aircraft and simulated ERS-1 SAR data are presented and compared to limited field ice property measurements and coincident passive microwave imagery. The importance of an integrated postlaunch program for the validation and improvement of this approach is discussed.

A system for verifying models and classification maps by extraction of information from a variety of data sources

NASA Technical Reports Server (NTRS)

Norikane, L.; Freeman, A.; Way, J.; Okonek, S.; Casey, R.

1992-01-01

Recent updates to a geographical information system (GIS) called VICAR (Video Image Communication and Retrieval)/IBIS are described. The system is designed to handle data from many different formats (vector, raster, tabular) and many different sources (models, radar images, ground truth surveys, optical images). All the data are referenced to a single georeference plane, and average or typical values for parameters defined within a polygonal region are stored in a tabular file, called an info file. The info file format allows tracking of data in time, maintenance of links between component data sets and the georeference image, conversion of pixel values to `actual' values (e.g., radar cross-section, luminance, temperature), graph plotting, data manipulation, generation of training vectors for classification algorithms, and comparison between actual measurements and model predictions (with ground truth data as input).

External calibration of polarimetric radar images using distributed targets

NASA Technical Reports Server (NTRS)

Yueh, Simon H.; Nghiem, S. V.; Kwok, R.

1992-01-01

A new technique is presented for calibrating polarimetric synthetic aperture radar (SAR) images using only the responses from natural distributed targets. The model for polarimetric radars is assumed to be X = cRST where X is the measured scattering matrix corresponding to the target scattering matrix S distorted by the system matrices T and R (in general T does not equal R(sup t)). To allow for the polarimetric calibration using only distributed targets and corner reflectors, van Zyl assumed a reciprocal polarimetric radar model with T = R(sup t); when applied for JPL SAR data, a heuristic symmetrization procedure is used by POLCAL to compensate the phase difference between the measured HV and VH responses and then take the average of both. This heuristic approach causes some non-removable cross-polarization responses for corner reflectors, which can be avoided by a rigorous symmetrization method based on reciprocity. After the radar is made reciprocal, a new algorithm based on the responses from distributed targets with reflection symmetry is developed to estimate the cross-talk parameters. The new algorithm never experiences problems in convergence and is also found to converge faster than the existing routines implemented for POLCAL. When the new technique is implemented for the JPL polarimetric data, symmetrization and cross-talk removal are performed on a line-by-line (azimuth) basis. After the cross-talks are removed from the entire image, phase and amplitude calibrations are carried out by selecting distributed targets either with azimuthal symmetry along the looking direction or with some well-known volume and surface scattering mechanisms to estimate the relative phases and amplitude responses of the horizontal and vertical channels.

Crop classification using multidate/multifrequency radar data. [Colby, Kansas

NASA Technical Reports Server (NTRS)

Ulaby, F. T. (Principal Investigator); Shanmugam, K. S.; Narayanan, V.; Dobson, C.

1981-01-01

Both C- and L-band radar data acquired over a test site near Colby, Kansas during the summer of 1978 were used to identify three types of vegetation cover and bare soil. The effects of frequency, polarization, and the look angle on the overall accuracy of recognizing the four types of ground cover were analyzed. In addition, multidate data were used to study the improvement in recognition accuracy possible with the addition of temporal information. The soil moisture conditions had changed considerably during the temporal sequence of the data; hence, the effects of soil moisture on the ability to discriminate between cover types were also analyzed. The results provide useful information needed for selecting the parameters of a radar system for monitoring crops.

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.

Low-Cost ASDE Evaluation Report: Raytheon Marine (Phase I) Radar at MKE (ARPA M345O/18CPX-19), Volume I.

DOT National Transportation Integrated Search

1996-07-31

The FAA has identified the Airport Surface Detection Equipment as a radar system that aids air traffic controllers in low visibility conditions to detect surface radar targets and sequence aircraft movement on active runways. Though 35 major U.S. air...

Radar, target and ranging

NASA Astrophysics Data System (ADS)

1984-09-01

This Test Operations Procedure (TOP) provides conventional test methods employing conventional test instrumentation for testing conventional radars. Single tests and subtests designed to test radar components, transmitters, receivers, antennas, etc., and system performance are conducted with single item instruments such as meters, generators, attenuators, counters, oscillators, plotters, etc., and with adequate land areas for conducting field tests.

Remotely sensing the German Wadden Sea-a new approach to address national and international environmental legislation.

PubMed

Müller, Gabriele; Stelzer, Kerstin; Smollich, Susan; Gade, Martin; Adolph, Winny; Melchionna, Sabrina; Kemme, Linnea; Geißler, Jasmin; Millat, Gerald; Reimers, Hans-Christian; Kohlus, Jörn; Eskildsen, Kai

2016-10-01

The Wadden Sea along the North Sea coasts of Denmark, Germany, and the Netherlands is the largest unbroken system of intertidal sand and mud flats in the world. Its habitats are highly productive and harbour high standing stocks and densities of benthic species, well adapted to the demanding environmental conditions. Therefore, the Wadden Sea is one of the most important areas for migratory birds in the world and thus protected by national and international legislation, which amongst others requires extensive monitoring. Due to the inaccessibility of major areas of the Wadden Sea, a classification approach based on optical and radar remote sensing has been developed to support environmental monitoring programmes. In this study, the general classification framework as well as two specific monitoring cases, mussel beds and seagrass meadows, are presented. The classification of mussel beds profits highly from inclusion of radar data due to their rough surface and achieves agreements of up to 79 % with areal data from the regular monitoring programme. Classification of seagrass meadows reaches even higher agreements with monitoring data (up to 100 %) and furthermore captures seagrass densities as low as 10 %. The main classification results are information on area and location of individual habitats. These are needed to fulfil environmental legislation requirements. One of the major advantages of this approach is the large areal coverage with individual satellite images, allowing simultaneous assessment of both accessible and inaccessible areas and thus providing a more complete overall picture.

Planetary Radar

NASA Technical Reports Server (NTRS)

Neish, Catherine D.; Carter, Lynn M.

2015-01-01

This chapter describes the principles of planetary radar, and the primary scientific discoveries that have been made using this technique. The chapter starts by describing the different types of radar systems and how they are used to acquire images and accurate topography of planetary surfaces and probe their subsurface structure. It then explains how these products can be used to understand the properties of the target being investigated. Several examples of discoveries made with planetary radar are then summarized, covering solar system objects from Mercury to Saturn. Finally, opportunities for future discoveries in planetary radar are outlined and discussed.

Assessment of Ultra-Wideband (UWB) Technology

DTIC Science & Technology

1990-07-13

community deal with these issues completely. (B) Detectability of the Radar (LPI). To make a radar’s signal more difficult to intercept, radar designers ...by an appropriately designed intercept receiver. (C) Detection of Relocatable Targets. A capability of interest to both strategic and tactical forces...that an impulse radar with a center frequency of a few hundred Megahertz may well be the best way to implement such a system. These design efforts and

PO calculation for reduction in radar cross section of hypersonic targets using RAM

NASA Astrophysics Data System (ADS)

Liu, Song-hua; Guo, Li-xin; Pan, Wei-tao; Chen, Wei; Xiao, Yi-fan

2018-06-01

The radar cross section (RCS) reduction of hypersonic targets by radar absorbing materials (RAM) coating under different reentry cases is analyzed in the C and X bands frequency range normally used for radar detection. The physical optics method is extended to both the inhomogeneous plasma sheath and RAM layer present simultaneously. The simulation results show that the absorbing coating can reduce the RCS of the plasma cloaking system and its effectiveness is related to the maximum plasma frequency. Moreover, the amount of the RCS decrease, its maxima, and the corresponding optimal RAM thickness depend on the non-uniformity and parameters of the plasma sheath. In addition, the backward RCS of the flight vehicle shrouded by plasma shielding and man-made absorber is calculated and compared to the bare cone.

Multi-pixel high-resolution three-dimensional imaging radar

NASA Technical Reports Server (NTRS)

Cooper, Ken B. (Inventor); Dengler, Robert J. (Inventor); Siegel, Peter H. (Inventor); Chattopadhyay, Goutam (Inventor); Ward, John S. (Inventor); Juan, Nuria Llombart (Inventor); Bryllert, Tomas E. (Inventor); Mehdi, Imran (Inventor); Tarsala, Jan A. (Inventor)

2012-01-01

A three-dimensional imaging radar operating at high frequency e.g., 670 GHz radar using low phase-noise synthesizers and a fast chirper to generate a frequency-modulated continuous-wave (FMCW) waveform, is disclosed that operates with a multiplexed beam to obtain range information simultaneously on multiple pixels of a target. A source transmit beam may be divided by a hybrid coupler into multiple transmit beams multiplexed together and directed to be reflected off a target and return as a single receive beam which is demultiplexed and processed to reveal range information of separate pixels of the target associated with each transmit beam simultaneously. The multiple transmit beams may be developed with appropriate optics to be temporally and spatially differentiated before being directed to the target. Temporal differentiation corresponds to a different intermediate frequencies separating the range information of the multiple pixels. Collinear transmit beams having differentiated polarizations may also be implemented.

Photonically enabled Ka-band radar and infrared sensor subscale testbed

NASA Astrophysics Data System (ADS)

Lohr, Michele B.; Sova, Raymond M.; Funk, Kevin B.; Airola, Marc B.; Dennis, Michael L.; Pavek, Richard E.; Hollenbeck, Jennifer S.; Garrison, Sean K.; Conard, Steven J.; Terry, David H.

2014-10-01

A subscale radio frequency (RF) and infrared (IR) testbed using novel RF-photonics techniques for generating radar waveforms is currently under development at The Johns Hopkins University Applied Physics Laboratory (JHU/APL) to study target scenarios in a laboratory setting. The linearity of Maxwell's equations allows the use of millimeter wavelengths and scaled-down target models to emulate full-scale RF scene effects. Coupled with passive IR and visible sensors, target motions and heating, and a processing and algorithm development environment, this testbed provides a means to flexibly and cost-effectively generate and analyze multi-modal data for a variety of applications, including verification of digital model hypotheses, investigation of correlated phenomenology, and aiding system capabilities assessment. In this work, concept feasibility is demonstrated for simultaneous RF, IR, and visible sensor measurements of heated, precessing, conical targets and of a calibration cylinder. Initial proof-of-principle results are shown of the Ka-band subscale radar, which models S-band for 1/10th scale targets, using stretch processing and Xpatch models.

A novel approach to simulate chest wall micro-motion for bio-radar life detection purpose

NASA Astrophysics Data System (ADS)

An, Qiang; Li, Zhao; Liang, Fulai; Chen, Fuming; Wang, Jianqi

2016-10-01

Volunteers are often recruited to serve as the detection targets during the research process of bio-radar life detection technology, in which the experiment results are highly susceptible to the physical status of different individuals (shape, posture, etc.). In order to objectively evaluate the radar system performance and life detection algorithms, a standard detection target is urgently needed. The paper first proposed a parameter quantitatively controllable system to simulate the chest wall micro-motion caused mainly by breathing and heart beating. Then, the paper continued to analyze the material and size selection of the scattering body mounted on the simulation system from the perspective of back scattering energy. The computational electromagnetic method was employed to determine the exact scattering body. Finally, on-site experiments were carried out to verify the reliability of the simulation platform utilizing an IR UWB bioradar. Experimental result shows that the proposed system can simulate a real human target from three aspects: respiration frequency, amplitude and body surface scattering energy. Thus, it can be utilized as a substitute for a human target in radar based non-contact life detection research in various scenarios.

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

Model-based approach to the detection and classification of mines in sidescan sonar.

PubMed

Reed, Scott; Petillot, Yvan; Bell, Judith

2004-01-10

This paper presents a model-based approach to mine detection and classification by use of sidescan sonar. Advances in autonomous underwater vehicle technology have increased the interest in automatic target recognition systems in an effort to automate a process that is currently carried out by a human operator. Current automated systems generally require training and thus produce poor results when the test data set is different from the training set. This has led to research into unsupervised systems, which are able to cope with the large variability in conditions and terrains seen in sidescan imagery. The system presented in this paper first detects possible minelike objects using a Markov random field model, which operates well on noisy images, such as sidescan, and allows a priori information to be included through the use of priors. The highlight and shadow regions of the object are then extracted with a cooperating statistical snake, which assumes these regions are statistically separate from the background. Finally, a classification decision is made using Dempster-Shafer theory, where the extracted features are compared with synthetic realizations generated with a sidescan sonar simulator model. Results for the entire process are shown on real sidescan sonar data. Similarities between the sidescan sonar and synthetic aperture radar (SAR) imaging processes ensure that the approach outlined here could be made applied to SAR image analysis.

Incorporation of operator knowledge for improved HMDS GPR classification

NASA Astrophysics Data System (ADS)

Kennedy, Levi; McClelland, Jessee R.; Walters, Joshua R.

2012-06-01

The Husky Mine Detection System (HMDS) detects and alerts operators to potential threats observed in groundpenetrating RADAR (GPR) data. In the current system architecture, the classifiers have been trained using available data from multiple training sites. Changes in target types, clutter types, and operational conditions may result in statistical differences between the training data and the testing data for the underlying features used by the classifier, potentially resulting in an increased false alarm rate or a lower probability of detection for the system. In the current mode of operation, the automated detection system alerts the human operator when a target-like object is detected. The operator then uses data visualization software, contextual information, and human intuition to decide whether the alarm presented is an actual target or a false alarm. When the statistics of the training data and the testing data are mismatched, the automated detection system can overwhelm the analyst with an excessive number of false alarms. This is evident in the performance of and the data collected from deployed systems. This work demonstrates that analyst feedback can be successfully used to re-train a classifier to account for variable testing data statistics not originally captured in the initial training data.

Maximum angular accuracy of pulsed laser radar in photocounting limit.

PubMed

Elbaum, M; Diament, P; King, M; Edelson, W

1977-07-01

To estimate the angular position of targets with pulsed laser radars, their images may be sensed with a fourquadrant noncoherent detector and the image photocounting distribution processed to obtain the angular estimates. The limits imposed on the accuracy of angular estimation by signal and background radiation shot noise, dark current noise, and target cross-section fluctuations are calculated. Maximum likelihood estimates of angular positions are derived for optically rough and specular targets and their performances compared with theoretical lower bounds.

High-resolution inverse synthetic aperture radar imaging for large rotation angle targets based on segmented processing algorithm

NASA Astrophysics Data System (ADS)

Chen, Hao; Zhang, Xinggan; Bai, Yechao; Tang, Lan

2017-01-01

In inverse synthetic aperture radar (ISAR) imaging, the migration through resolution cells (MTRCs) will occur when the rotation angle of the moving target is large, thereby degrading image resolution. To solve this problem, an ISAR imaging method based on segmented preprocessing is proposed. In this method, the echoes of large rotating target are divided into several small segments, and every segment can generate a low-resolution image without MTRCs. Then, each low-resolution image is rotated back to the original position. After image registration and phase compensation, a high-resolution image can be obtained. Simulation and real experiments show that the proposed algorithm can deal with the radar system with different range and cross-range resolutions and significantly compensate the MTRCs.

Homeland Security: Unmanned Aerial Vehicles and Border Surveillance

DTIC Science & Technology

2010-07-08

outfit the Predator B with a synthetic aperture radar (SAR) system17 and a moving target indicator (MTI) radar. Adding SAR and MTI to the Predator B’s...Predator Squadrons,” Inside the Air Force, June 7, 2002. 17 For more information about Synthetic Aperture Radar, see http://www.sandia.gov/radar...contributed to the seizing of more than 22,000 pounds of marijuana and the apprehension of 5,000 illegal immigrants,” others disagree.24 “Unmanned aircraft

Long microwave delay fiber-optic link for radar testing

NASA Astrophysics Data System (ADS)

Newberg, I. L.; Gee, C. M.; Thurmond, G. D.; Yen, H. W.

1990-05-01

A long fiberoptic delay line is used as a radar repeater to improve radar testing capabilities. The first known generation of 152 microsec delayed ideal target at X-band (10 GHz) frequencies having the phase stability and signal-to-noise ratio (SNR) needed for testing modern high-resolution Doppler radars is demonstrated with a 31.6-km experimental externally modulated fiberoptic link with a distributed-feedback (DFB) laser. The test application, link configuration, and link testing are discussed.

Joint Waveform Optimization and Adaptive Processing for Random-Phase Radar Signals

DTIC Science & Technology

2014-01-01

extended targets,” IEEE Journal of Selected Topics in Signal Processing, vol. 1, no. 1, pp. 42– 55, June 2007. [2] S. Sen and A. Nehorai, “ OFDM mimo ...radar compared to traditional waveforms. I. INTRODUCTION There has been much recent interest in waveform design for multiple-input, multiple-output ( MIMO ...amplitude. When the resolution capability of the MIMO radar system is of interest, the transmit waveform can be designed to sharpen the radar ambiguity

Antenna Allocation in MIMO Radar with Widely Separated Antennas for Multi-Target Detection

PubMed Central

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-01-01

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes. PMID:25350505

Antenna allocation in MIMO radar with widely separated antennas for multi-target detection.

PubMed

Gao, Hao; Wang, Jian; Jiang, Chunxiao; Zhang, Xudong

2014-10-27

In this paper, we explore a new resource called multi-target diversity to optimize the performance of multiple input multiple output (MIMO) radar with widely separated antennas for detecting multiple targets. In particular, we allocate antennas of the MIMO radar to probe different targets simultaneously in a flexible manner based on the performance metric of relative entropy. Two antenna allocation schemes are proposed. In the first scheme, each antenna is allocated to illuminate a proper target over the entire illumination time, so that the detection performance of each target is guaranteed. The problem is formulated as a minimum makespan scheduling problem in the combinatorial optimization framework. Antenna allocation is implemented through a branch-and-bound algorithm and an enhanced factor 2 algorithm. In the second scheme, called antenna-time allocation, each antenna is allocated to illuminate different targets with different illumination time. Both antenna allocation and time allocation are optimized based on illumination probabilities. Over a large range of transmitted power, target fluctuations and target numbers, both of the proposed antenna allocation schemes outperform the scheme without antenna allocation. Moreover, the antenna-time allocation scheme achieves a more robust detection performance than branch-and-bound algorithm and the enhanced factor 2 algorithm when the target number changes.

Gmti Motion Compensation

DOEpatents

Doerry, Armin W.

2004-07-20

Movement of a GMTI radar during a coherent processing interval over which a set of radar pulses are processed may cause defocusing of a range-Doppler map in the video signal. This problem may be compensated by varying waveform or sampling parameters of each pulse to compensate for distortions caused by variations in viewing angles from the radar to the target.

Electric and magnetic target polarization in quantum radar

NASA Astrophysics Data System (ADS)

Brandsema, Matthew J.; Narayanan, Ram M.; Lanzagorta, Marco

2017-05-01

In this paper, we discuss the effect that photon polarization has on the quantum radar cross section (QRCS) during the special case scenario of when the target is enveloped in either a uniform electric field or magnetic field and all of its atomic electric/magnetic dipole moments become aligned (target polarization). This target polarization causes the coupling between the photon and the matter to change and alter the scattering characteristics of the target. Most notably, it causes scattering to be very near zero at a specified angle. We also investigate the relationship between electric and magnetic types of coupling and find that the electric contribution dominates the QRCS response.

Transponder data processing methods and systems

DOEpatents

Axline, Robert M.

2003-06-10

This invention is a radar/tag system where pulses from a radar cause a tag (or transponder) to respond to the radar. The radar, along with its conventional pulse transmissions, sends a reference signal to the tag. The tag recovers the reference signal and uses it to shift the center frequency of the received radar pulse to a different frequency. This shift causes the frequencies of the tag response pulses to be disjoint from those of the transmit pulse. In this way, radar clutter can be eliminated from the tag responses. The radar predicts, to within a small Doppler offset, the center frequency of tag response pulses. The radar can create synthetic-aperture-radar-like images and moving-target-indicator-radar-like maps containing the signature of the tag against a background of thermal noise and greatly attenuated radar clutter. The radar can geolocate the tag precisely and accurately (to within better than one meter of error). The tag can encode status and environmental data onto its response pulses, and the radar can receive and decode this information.

Performance test and verification of an off-the-shelf automated avian radar tracking system.

PubMed

May, Roel; Steinheim, Yngve; Kvaløy, Pål; Vang, Roald; Hanssen, Frank

2017-08-01

Microwave radar is an important tool for observation of birds in flight and represents a tremendous increase in observation capability in terms of amount of surveillance space that can be covered at relatively low cost. Based on off-the-shelf radar hardware, automated radar tracking systems have been developed for monitoring avian movements. However, radar used as an observation instrument in biological research has its limitations that are important to be aware of when analyzing recorded radar data. This article describes a method for exploring the detection capabilities of a dedicated short-range avian radar system used inside the operational Smøla wind-power plant. The purpose of the testing described was to find the maximum detection range for various sized birds, while controlling for the effects of flight tortuosity, flight orientation relative to the radar and ground clutter. The method was to use a dedicated test target in form of a remotely controlled unmanned aerial vehicle (UAV) with calibrated radar cross section (RCS), which enabled the design of virtually any test flight pattern within the area of interest. The UAV had a detection probability of 0.5 within a range of 2,340 m from the radar. The detection performance obtained by the RCS-calibrated test target (-11 dBm 2 , 0.08 m 2 RCS) was then extrapolated to find the corresponding performance of differently sized birds. Detection range depends on system sensitivity, the environment within which the radar is placed and the spatial distribution of birds. The avian radar under study enables continuous monitoring of bird activity within a maximum range up to 2 km dependent on the size of the birds in question. While small bird species may be detected up to 0.5-1 km, larger species may be detected up to 1.5-2 km distance from the radar.

See-through Detection and 3D Reconstruction Using Terahertz Leaky-Wave Radar Based on Sparse Signal Processing

NASA Astrophysics Data System (ADS)

Murata, Koji; Murano, Kosuke; Watanabe, Issei; Kasamatsu, Akifumi; Tanaka, Toshiyuki; Monnai, Yasuaki

2018-02-01

We experimentally demonstrate see-through detection and 3D reconstruction using terahertz leaky-wave radar based on sparse signal processing. The application of terahertz waves to radar has received increasing attention in recent years for its potential to high-resolution and see-through detection. Among others, the implementation using a leaky-wave antenna is promising for compact system integration with beam steering capability based on frequency sweep. However, the use of a leaky-wave antenna poses a challenge on signal processing. Since a leaky-wave antenna combines the entire signal captured by each part of the aperture into a single output, the conventional array signal processing assuming access to a respective antenna element is not applicable. In this paper, we apply an iterative recovery algorithm "CoSaMP" to signals acquired with terahertz leaky-wave radar for clutter mitigation and aperture synthesis. We firstly demonstrate see-through detection of target location even when the radar is covered with an opaque screen, and therefore, the radar signal is disturbed by clutter. Furthermore, leveraging the robustness of the algorithm against noise, we also demonstrate 3D reconstruction of distributed targets by synthesizing signals collected from different orientations. The proposed approach will contribute to the smart implementation of terahertz leaky-wave radar.

Radar signature generation for feature-aided tracking research

NASA Astrophysics Data System (ADS)

Piatt, Teri L.; Sherwood, John U.; Musick, Stanton H.

2005-05-01

Accurately associating sensor kinematic reports to known tracks, new tracks, or clutter is one of the greatest obstacles to effective track estimation. Feature-aiding is one technology that is emerging to address this problem, and it is expected that adding target features will aid report association by enhancing track accuracy and lengthening track life. The Sensor's Directorate of the Air Force Research Laboratory is sponsoring a challenge problem called Feature-Aided Tracking of Stop-move Objects (FATSO). The long-range goal of this research is to provide a full suite of public data and software to encourage researchers from government, industry, and academia to participate in radar-based feature-aided tracking research. The FATSO program is currently releasing a vehicle database coupled to a radar signature generator. The completed FATSO system will incorporate this database/generator into a Monte Carlo simulation environment for evaluating multiplatform/multitarget tracking scenarios. The currently released data and software contains the following: eight target models, including a tank, ammo hauler, and self-propelled artillery vehicles; and a radar signature generator capable of producing SAR and HRR signatures of all eight modeled targets in almost any configuration or articulation. In addition, the signature generator creates Z-buffer data, label map data, and radar cross-section prediction and allows the user to add noise to an image while varying sensor-target geometry (roll, pitch, yaw, squint). Future capabilities of this signature generator, such as scene models and EO signatures as well as details of the complete FATSO testbed, are outlined.

Crop identification from radar imagery of the Huntington County, Indiana test site

NASA Technical Reports Server (NTRS)

Batlivala, P. P.; Ulaby, F. T. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Like polarization was successful in discriminating corn and soybeans; however, pasture and woods were consistently confused as soybeans and corn, respectively. The probability of correct classification was about 65%. The cross polarization component (highest for woods and lowest for pasture) helped in separating the woods from corn, and pasture from soybeans, and when used with the like polarization component, the probability of correct classification increased to 74%.

Monostatic Radar Cross Section Estimation of Missile Shaped Object Using Physical Optics Method

NASA Astrophysics Data System (ADS)

Sasi Bhushana Rao, G.; Nambari, Swathi; Kota, Srikanth; Ranga Rao, K. S.

2017-08-01

Stealth Technology manages many signatures for a target in which most radar systems use radar cross section (RCS) for discriminating targets and classifying them with regard to Stealth. During a war target’s RCS has to be very small to make target invisible to enemy radar. In this study, Radar Cross Section of perfectly conducting objects like cylinder, truncated cone (frustum) and circular flat plate is estimated with respect to parameters like size, frequency and aspect angle. Due to the difficulties in exactly predicting the RCS, approximate methods become the alternative. Majority of approximate methods are valid in optical region and where optical region has its own strengths and weaknesses. Therefore, the analysis given in this study is purely based on far field monostatic RCS measurements in the optical region. Computation is done using Physical Optics (PO) method for determining RCS of simple models. In this study not only the RCS of simple models but also missile shaped and rocket shaped models obtained from the cascaded objects with backscatter has been computed using Matlab simulation. Rectangular plots are obtained for RCS in dbsm versus aspect angle for simple and missile shaped objects using Matlab simulation. Treatment of RCS, in this study is based on Narrow Band.

Target Glint Suppression Technology.

DTIC Science & Technology

1980-09-01

report is organized into two principal sections. Section 2 addresses the impact of target effects on the noncoherent detection problem associated with...zero pulse-to-pulse correlation. Results are presented for a scanning search radar which is assumed to noncoherently integrate N pulses. Generally...speaking, detection performance is shown to be a maximum when the pulse-to-pulse correlation is a minimum. As a result noncoherent search radars should

Signal Processing for Radar Target Tracking and Identification

DTIC Science & Technology

1996-12-01

Computes the likelihood for various potential jump moves. 12. matrix_mult.m: Parallel implementation of linear algebra ... Elementary Lineary Algebra with Applications, John Wiley k Sons, Inc., New York, 1987. [9] A. K. Bhattacharyya, and D. L. Sengupta, Radar Cross...Miller, ’Target Tracking and Recognition Using Jump-Diffusion Processes," ARO’s 11th Army Conf. on Applied Mathemat- ics and Computing, June 8-11

Design of an FMCW radar baseband signal processing system for automotive application.

PubMed

Lin, Jau-Jr; Li, Yuan-Ping; Hsu, Wei-Chiang; Lee, Ta-Sung

2016-01-01

For a typical FMCW automotive radar system, a new design of baseband signal processing architecture and algorithms is proposed to overcome the ghost targets and overlapping problems in the multi-target detection scenario. To satisfy the short measurement time constraint without increasing the RF front-end loading, a three-segment waveform with different slopes is utilized. By introducing a new pairing mechanism and a spatial filter design algorithm, the proposed detection architecture not only provides high accuracy and reliability, but also requires low pairing time and computational loading. This proposed baseband signal processing architecture and algorithms balance the performance and complexity, and are suitable to be implemented in a real automotive radar system. Field measurement results demonstrate that the proposed automotive radar signal processing system can perform well in a realistic application scenario.

46 CFR 10.109 - Classification of endorsements.

Code of Federal Regulations, 2013 CFR

2013-10-01

...) Professional nurse; (41) Marine physician assistant; (42) Hospital corpsman; and (43) Radar observer. (b) The... engineer (limited-near-coastal); (22) First assistant engineer; (23) Second assistant engineer; (24) Third assistant engineer; (25) Assistant engineer (limited); (26) Designated duty engineer (DDE); (27) Chief...

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

PubMed

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

Handling target obscuration through Markov chain observations

NASA Astrophysics Data System (ADS)

Kouritzin, Michael A.; Wu, Biao

2008-04-01

Target Obscuration, including foliage or building obscuration of ground targets and landscape or horizon obscuration of airborne targets, plagues many real world filtering problems. In particular, ground moving target identification Doppler radar, mounted on a surveillance aircraft or unattended airborne vehicle, is used to detect motion consistent with targets of interest. However, these targets try to obscure themselves (at least partially) by, for example, traveling along the edge of a forest or around buildings. This has the effect of creating random blockages in the Doppler radar image that move dynamically and somewhat randomly through this image. Herein, we address tracking problems with target obscuration by building memory into the observations, eschewing the usual corrupted, distorted partial measurement assumptions of filtering in favor of dynamic Markov chain assumptions. In particular, we assume the observations are a Markov chain whose transition probabilities depend upon the signal. The state of the observation Markov chain attempts to depict the current obscuration and the Markov chain dynamics are used to handle the evolution of the partially obscured radar image. Modifications of the classical filtering equations that allow observation memory (in the form of a Markov chain) are given. We use particle filters to estimate the position of the moving targets. Moreover, positive proof-of-concept simulations are included.

Non-Cooperative Air Target Identification Using Radar (l’Identification radar des cibles aeriennes non cooperatives)

DTIC Science & Technology

1998-11-01

are already operational in the radar domain , e.g. in airborne radars. NATO fighter aircraft are equipped with transponder systems answering on...Mise en forme et 6talonnage des donn6es SER moyenne pour un domaine de fr6quence (bande passante du code utilis6) et un secteur Ce module extrait les...cooperatives) Papers presented at the Symposium of the RTO Systems Concepts and Integration Panel (SCI) held in Mannheim, Germany, 22-24 April 1998. 1

Ultrawideband radar echoes of land mine targets measured at oblique incidence using a 250-kW impulse radar system

NASA Astrophysics Data System (ADS)

Chant, Ian J.; Staines, Geoff

1997-07-01

United Nations Peacekeeping forces around the world need to transport food, personnel and medical supplies through disputed regions were land mines are in active use as road blocks and terror weapons. A method of fast, effective land mine detection is needed to combat this threat to road transport. The technique must operate from a vehicle travelling at a reasonable velocity and give warning far enough ahead for the vehicle to stop in time to avoid the land mine. There is particular interest in detecting low- metallic content land mines. One possible solutionis the use of ultra-wide-band (UWB) radar. The Australian Defence Department is investigating the feasibility of using UWB radar for land mine detection from a vehicle. A 3 GHz UWB system has been used to collect target response from a series of inert land mines and mine-like objects placed on the ground and buried in the ground. The targets measured were a subset of those in the target set described in Wong et al. with the addition of inert land mines corresponding to some of the surrogate targets in this set. The results are encouraging for the detection of metallic land mines and the larger non-metallic land mines. Smaller low-metallic- content anti-personnel land mines are less likely to be detected.

Detection of Marine Radar Targets

NASA Astrophysics Data System (ADS)

Briggs, John N.

A radar must detect targets before it can display them. Yet manufacturers' data sheets rarely tell us what the products will detect at what range. Many of the bigger radars are Type Approved so we consult the relevant IMO performance standard A 477 (XII). Paraphrasing Section 3.1 of the draft forthcoming revision (NAV 41/6): under normal propagation conditions with the scanner at height of 15 m, in the absence of clutter, the radar is required to give clear indication of an object such as a navigational buoy having a radar cross section area (RCS) of 10 m2 at 2 n.m. and, as examples, coastlines whose ground rises to 60/6 m at ranges of 20/7 n.m., a ship of 5000 tons at any aspect at 7 n.m. and a small vessel 10 m long at 3 n.m.This helps, but suppose we must pick up a 5 m2 buoy at g km? What happens in clutter? Should we prefer S- or X-band? To answer such questions we use equations which define the performance of surveillance radars, but the textbooks and specialist papers containing them often generalize with aeronautical and defence topics, making life difficult for the nonspecialist.This paper attempts a concise and self-contained engineering account of all main factors affecting detection of passive and active targets on civil marine and vessel traffic service (VTS) radars. We develop a set of equations for X- and S-band (3 and 10 cm, centred on 9400 and 3000 MHz respectively), suited for spreadsheet calculation.Sufficient theory is sketched in to indicate where results should be valid. Some simplifications of conventional treatments have been identified.

SAR target recognition using behaviour library of different shapes in different incidence angles and polarisations

NASA Astrophysics Data System (ADS)

Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas

2018-05-01

Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.

Oil detection in a coastal marsh with polarimetric Synthetic Aperture Radar (SAR)

USGS Publications Warehouse

Ramsey, Elijah W.; Rangoonwala, Amina; Suzuoki, Yukihiro; Jones, Cathleen E.

2011-01-01

The National Aeronautics and Space Administration's airborne Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) was deployed in June 2010 in response to the Deepwater Horizon oil spill in the Gulf of Mexico. UAVSAR is a fully polarimetric L-band Synthetic Aperture Radar (SAR) sensor for obtaining data at high spatial resolutions. Starting a month prior to the UAVSAR collections, visual observations confirmed oil impacts along shorelines within northeastern Barataria Bay waters in eastern coastal Louisiana. UAVSAR data along several flight lines over Barataria Bay were collected on 23 June 2010, including the repeat flight line for which data were collected in June 2009. Our analysis of calibrated single-look complex data for these flight lines shows that structural damage of shoreline marsh accompanied by oil occurrence manifested as anomalous features not evident in pre-spill data. Freeman-Durden (FD) and Cloude-Pottier (CP) decompositions of the polarimetric data and Wishart classifications seeded with the FD and CP classes also highlighted these nearshore features as a change in dominant scattering mechanism. All decompositions and classifications also identify a class of interior marshes that reproduce the spatially extensive changes in backscatter indicated by the pre- and post-spill comparison of multi-polarization radar backscatter data. FD and CP decompositions reveal that those changes indicate a transform of dominant scatter from primarily surface or volumetric to double or even bounce. Given supportive evidence that oil-polluted waters penetrated into the interior marshes, it is reasonable that these backscatter changes correspond with oil exposure; however, multiple factors prevent unambiguous determination of whether UAVSAR detected oil in interior marshes.

Advanced Research into Moving Target Imaging Using Multistatic Radar

DTIC Science & Technology

2009-12-01

1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188...11 C. TEO BENG KOON WILLIAM’S WORK..................................................12 III. DATA ANALYSIS... principles of electromagnetic and radar theory rely on the Maxwell’s equations. Radar theory is a practical expansion of the fundamental theory of

Performance of 40- to 50-year-old subjects on a radar monitoring task : the effects of wearing bifocal glasses and interpolated rest periods on target detection time.

DOT National Transportation Integrated Search

1982-04-01

The present study examines the effects of wearing bifocal glasses and interpolated rest periods on the performance of 40- to 50-year-old subjects on a radar monitoring task. The visual display was designed to resemble an air traffic control radar dis...

A novel data-driven learning method for radar target detection in nonstationary environments

DOE PAGES

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

2016-04-12

Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

Design and Processing of a Novel Chaos-Based Stepped Frequency Synthesized Wideband Radar Signal.

PubMed

Zeng, Tao; Chang, Shaoqiang; Fan, Huayu; Liu, Quanhua

2018-03-26

The linear stepped frequency and linear frequency shift keying (FSK) signal has been widely used in radar systems. However, such linear modulation signals suffer from the range-Doppler coupling that degrades radar multi-target resolution. Moreover, the fixed frequency-hopping or frequency-coded sequence can be easily predicted by the interception receiver in the electronic countermeasures (ECM) environments, which limits radar anti-jamming performance. In addition, the single FSK modulation reduces the radar low probability of intercept (LPI) performance, for it cannot achieve a large time-bandwidth product. To solve such problems, we propose a novel chaos-based stepped frequency (CSF) synthesized wideband signal in this paper. The signal introduces chaotic frequency hopping between the coherent stepped frequency pulses, and adopts a chaotic frequency shift keying (CFSK) and phase shift keying (PSK) composited coded modulation in a subpulse, called CSF-CFSK/PSK. Correspondingly, the processing method for the signal has been proposed. According to our theoretical analyses and the simulations, the proposed signal and processing method achieve better multi-target resolution and LPI performance. Furthermore, flexible modulation is able to increase the robustness against identification of the interception receiver and improve the anti-jamming performance of the radar.

Towards decadal time series of Arctic and Antarctic sea ice thickness from radar altimetry

NASA Astrophysics Data System (ADS)

Hendricks, S.; Rinne, E. J.; Paul, S.; Ricker, R.; Skourup, H.; Kern, S.; Sandven, S.

2016-12-01

The CryoSat-2 mission has demonstrated the value of radar altimetry to assess the interannual variability and short-term trends of Arctic sea ice over the existing observational record of 6 winter seasons. CryoSat-2 is a particular successful mission for sea ice mass balance assessment due to its novel radar altimeter concept and orbit configuration, but radar altimetry data is available since 1993 from the ERS-1/2 and Envisat missions. Combining these datasets promises a decadal climate data record of sea ice thickness, but inter-mission biases must be taken into account due to the evolution of radar altimeters and the impact of changing sea ice conditions on retrieval algorithm parametrizations. The ESA Climate Change Initiative on Sea Ice aims to extent the list of data records for Essential Climate Variables (ECV's) with a consistent time series of sea ice thickness from available radar altimeter data. We report on the progress of the algorithm development and choices for auxiliary data sets for sea ice thickness retrieval in the Arctic and Antarctic Oceans. Particular challenges are the classification of surface types and freeboard retrieval based on radar waveforms with significantly varying footprint sizes. In addition, auxiliary data sets, e.g. for snow depth, are far less developed in the Antarctic and we will discuss the expected skill of the sea ice thickness ECV's in both hemispheres.

Method and Apparatus for Reading Two Dimensional Identification Symbols Using Radar Techniques

NASA Technical Reports Server (NTRS)

Schramm, Harry F., Jr. (Inventor); Roxby, Donald L. (Inventor)

2003-01-01

A method and apparatus are provided for sensing two-dimensional identification marks provided on a substrate or embedded within a substrate below a surface of the substrate. Micropower impulse radar is used to transmit a high risetime, short duration pulse to a focussed radar target area of the substrate having the two dimensional identification marks. The method further includes the steps of listening for radar echoes returned from the identification marks during a short listening period window occurring a predetermined time after transmission of the radar pulse. If radar echoes are detected, an image processing step is carried out. If no radar echoes are detected, the method further includes sequentially transmitting further high risetime, short duration pulses, and listening for radar echoes from each of said further pulses after different elapsed times for each of the further pulses until radar echoes are detected. When radar echoes are detected, data based on the detected echoes is processed to produce an image of the identification marks.

MAC Europe 1991 campaign: AIRSAR/AVIRIS data integration for agricultural test site classification

NASA Technical Reports Server (NTRS)

Sangiovanni, S.; Buongiorno, M. F.; Ferrarini, M.; Fiumara, A.

1993-01-01

During summer 1991, multi-sensor data were acquired over the Italian test site 'Otrepo Pavese', an agricultural flat area in Northern Italy. This area has been the Telespazio pilot test site for experimental activities related to agriculture applications. The aim of the investigation described in the following paper is to assess the amount of information contained in the AIRSAR (Airborne Synthetic Aperture Radar) and AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) data, and to evaluate classification results obtained from each sensor data separately and from the combined dataset. All classifications are examined by means of the resulting confusion matrices and Khat coefficients. Improvements of the classification results obtained by using the integrated dataset are finally evaluated.

Description and availability of airborne Doppler radar data

NASA Technical Reports Server (NTRS)

Harrah, S. D.; Bracalente, E. M.; Schaffner, P. R.; Baxa, E. G.

1993-01-01

An airborne, forward-looking, pulse, Doppler radar has been developed in conjunction with the joint FAA/NASA Wind Shear Program. This radar represents a first in an emerging technology. The radar was developed to assess the applicability of an airborne radar to detect low altitude hazardous wind shears for civil aviation applications. Such a radar must be capable of looking down into the ground clutter environment and extracting wind estimates from relatively low reflectivity weather targets. These weather targets often have reflectivities several orders of magnitude lower than the surrounding ground clutter. The NASA radar design incorporates numerous technological and engineering achievements in order to accomplish this task. The basic R/T unit evolved from a standard Collins 708 weather radar, which supports specific pulse widths of 1-7 microns and Pulse Repetition Frequencies (PRF) of less than 1-10 kHz. It was modified to allow for the output of the first IF signal, which fed a NASA developed receiver/detector subsystem. The NASA receiver incorporated a distributed, high-speed digital attenuator, producing a range bin to range bin automatic gain control system with 65 dB of dynamic range. Using group speed information supplied by the aircraft's navigation system, the radar signal is frequency demodulated back to base band (zero Doppler relative to stationary ground). The In-phase & Quadrature-phase (I/Q) components of the measured voltage signal are then digitized by a 12-bit A-D converter (producing an additional 36 dB of dynamic range). The raw I/Q signal for each range bin is then recorded (along with the current radar & aircraft state parameters) by a high-speed Kodak tape recorder.

Remote sensing of surface currents with single shipborne high-frequency surface wave radar

NASA Astrophysics Data System (ADS)

Wang, Zhongbao; Xie, Junhao; Ji, Zhenyuan; Quan, Taifan

2016-01-01

High-frequency surface wave radar (HFSWR) is a useful technology for remote sensing of surface currents. It usually requires two (or more) stations spaced apart to create a two-dimensional (2D) current vector field. However, this method can only obtain the measurements within the overlapping coverage, which wastes most of the data from only one radar observation. Furthermore, it increases observation's costs significantly. To reduce the number of required radars and increase the ocean area that can be measured, this paper proposes an economical methodology for remote sensing of the 2D surface current vector field using single shipborne HFSWR. The methodology contains two parts: (1) a real space-time multiple signal classification (MUSIC) based on sparse representation and unitary transformation techniques is developed for measuring the radial currents from the spreading first-order spectra, and (2) the stream function method is introduced to obtain the 2D surface current vector field. Some important conclusions are drawn, and simulations are included to validate the correctness of them.

Polarization Smoothing Generalized MUSIC Algorithm with Polarization Sensitive Array for Low Angle Estimation.

PubMed

Tan, Jun; Nie, Zaiping

2018-05-12

Direction of Arrival (DOA) estimation of low-altitude targets is difficult due to the multipath coherent interference from the ground reflection image of the targets, especially for very high frequency (VHF) radars, which have antennae that are severely restricted in terms of aperture and height. The polarization smoothing generalized multiple signal classification (MUSIC) algorithm, which combines polarization smoothing and generalized MUSIC algorithm for polarization sensitive arrays (PSAs), was proposed to solve this problem in this paper. Firstly, the polarization smoothing pre-processing was exploited to eliminate the coherence between the direct and the specular signals. Secondly, we constructed the generalized MUSIC algorithm for low angle estimation. Finally, based on the geometry information of the symmetry multipath model, the proposed algorithm was introduced to convert the two-dimensional searching into one-dimensional searching, thus reducing the computational burden. Numerical results were provided to verify the effectiveness of the proposed method, showing that the proposed algorithm has significantly improved angle estimation performance in the low-angle area compared with the available methods, especially when the grazing angle is near zero.

SIRE: a MIMO radar for landmine/IED detection

NASA Astrophysics Data System (ADS)

Ojowu, Ode; Wu, Yue; Li, Jian; Nguyen, Lam

2013-05-01

Multiple-input multiple-output (MIMO) radar systems have been shown to have significant performance improvements over their single-input multiple-output (SIMO) counterparts. For transmit and receive elements that are collocated, the waveform diversity afforded by this radar is exploited for performance improvements. These improvements include but are not limited to improved target detection, improved parameter identifiability and better resolvability. In this paper, we present the Synchronous Impulse Reconstruction Radar (SIRE) Ultra-wideband (UWB) radar designed by the Army Research Lab (ARL) for landmine and improvised explosive device (IED) detection as a 2 by 16 MIMO radar (with collocated antennas). Its improvement over its SIMO counterpart in terms of beampattern/cross range resolution are discussed and demonstrated using simulated data herein. The limitations of this radar for Radio Frequency Interference (RFI) suppression are also discussed in this paper. A relaxation method (RELAX) combined with averaging of multiple realizations of the measured data is presented for RFI suppression; results show no noticeable target signature distortion after suppression. In this paper, the back-projection (delay and sum) data independent method is used for generating SAR images. A side-lobe minimization technique called recursive side-lobe minimization (RSM) is also discussed for reducing side-lobes in this data independent approach. We introduce a data-dependent sparsity based spectral estimation technique called Sparse Learning via Iterative Minimization (SLIM) as well as a data-dependent CLEAN approach for generating SAR images for the SIRE radar. These data-adaptive techniques show improvement in side-lobe reduction and resolution for simulated data for the SIRE radar.

Artifacts in Radar Imaging of Moving Targets

DTIC Science & Technology

2012-09-01

CA, USA, 2007. [11] B. Borden, Radar imaging of airborne targets: A primer for Applied mathematicians and Physicists . New York, NY: Taylor and... Project (0704–0188) Washington DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 21 September 2012 3. REPORT TYPE AND DATES COVERED...CW Continuous Wave DAC Digital to Analog Convertor DFT Discrete Fourier Transform FBP Filtered Back Projection FFT Fast Fourier Transform GPS

Use of an Extended Kalman Filter

DTIC Science & Technology

1990-09-01

navigation radars available anywhere in the market. Those belonging to the FURUNO company are the most popular . This radar will be used on the present...Smugglers", Popular Communications, June 1990 4. Kourkoulis, D., Bearings Only Target Tracking-Maneuvering Target, Master’s Thesis, Naval Postgraduate...CA. 93943-5002 3. Jefatura de Educacion 1 Comandancia General de la Armada Av. Wollmer, San Bernardino CP.1011 Caracas, Venezuela. 4. Escuela Superior

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

Candy, J. V.

Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate.more » In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.« less

Impact of frequency and polarization diversity on a terahertz radar's imaging performance

NASA Astrophysics Data System (ADS)

Cooper, Ken B.; Dengler, Robert J.; Llombart, Nuria

2011-05-01

The Jet Propulsion Laboratory's 675 GHz, 25 m standoff imaging radar can achieve >1 Hz real time frame rates over 40x40 cm fields of view for rapid detection of person-borne concealed weapons. In its normal mode of operation, the radar generates imagery based solely on the time-of-flight, or range, between the radar and target. With good clothing penetration at 675 GHz, a hidden object will be detectable as an anomaly in the range-to-surface profile of a subject. Here we report on results of two modifications in the radar system that were made to asses its performance using somewhat different detection approaches. First, the radar's operating frequency and bandwidth were cut in half, to 340 GHz and 13 GHz, where there potential system advantages include superior transmit power and clothing penetration, as well as a lower cost of components. In this case, we found that the twofold reduction in range and cross-range resolution sharply limited the quality of through-clothes imagery, although some improvement is observed for detection of large targets concealed by very thick clothing. The second radar modification tested involved operation in a fully polarimetric mode, where enhanced image contrast might occur between surfaces with different material or geometric characteristics. Results from these tests indicated that random speckle dominates polarimetric power imagery, making it an unattractive approach for contrast improvement. Taken together, the experiments described here underscore the primary importance of high resolution imaging in THz radar applications for concealed weapons detection.

All-digital radar architecture

NASA Astrophysics Data System (ADS)

Molchanov, Pavlo A.

2014-10-01

All digital radar architecture requires exclude mechanical scan system. The phase antenna array is necessarily large because the array elements must be co-located with very precise dimensions and will need high accuracy phase processing system for aggregate and distribute T/R modules data to/from antenna elements. Even phase array cannot provide wide field of view. New nature inspired all digital radar architecture proposed. The fly's eye consists of multiple angularly spaced sensors giving the fly simultaneously thee wide-area visual coverage it needs to detect and avoid the threats around him. Fly eye radar antenna array consist multiple directional antennas loose distributed along perimeter of ground vehicle or aircraft and coupled with receiving/transmitting front end modules connected by digital interface to central processor. Non-steering antenna array allows creating all-digital radar with extreme flexible architecture. Fly eye radar architecture provides wide possibility of digital modulation and different waveform generation. Simultaneous correlation and integration of thousands signals per second from each point of surveillance area allows not only detecting of low level signals ((low profile targets), but help to recognize and classify signals (targets) by using diversity signals, polarization modulation and intelligent processing. Proposed all digital radar architecture with distributed directional antenna array can provide a 3D space vector to the jammer by verification direction of arrival for signals sources and as result jam/spoof protection not only for radar systems, but for communication systems and any navigation constellation system, for both encrypted or unencrypted signals, for not limited number or close positioned jammers.

A radar survey of M- and X-class asteroids

NASA Astrophysics Data System (ADS)

Shepard, Michael K.; Clark, Beth Ellen; Nolan, Michael C.; Howell, Ellen S.; Magri, Christopher; Giorgini, Jon D.; Benner, Lance A. M.; Ostro, Steven J.; Harris, Alan W.; Warner, Brian; Pray, Donald; Pravec, Petr; Fauerbach, Michael; Bennett, Thomas; Klotz, Alain; Behrend, Raoul; Correia, Horacio; Coloma, Josep; Casulli, Silvano; Rivkin, Andrew

2008-05-01

We observed ten M- and X-class main-belt asteroids with the Arecibo Observatory's S-band (12.6 cm) radar. The X-class asteroids were targeted based on their albedos or other properties which suggested they might be M-class. This work brings the total number of main-belt M-class asteroids observed with radar to 14. We find that three of these asteroids have rotation rates significantly different from what was previously reported. Based on their high radar albedo, we find that only four of the fourteen—16 Psyche, 216 Kleopatra, 758 Mancunia, and 785 Zwetana—are almost certainly metallic. 129 Antigone has a moderately high radar albedo and we suggest it may be a CH/CB/Bencubbinite parent body. Three other asteroids, 97 Klotho, 224 Oceana, and 796 Sarita have radar albedos significantly higher than the average main belt asteroid and we cannot rule out a significant metal content for them. Five of our target asteroids, 16 Psyche, 129 Antigone, 135 Hertha, 758 Mancunia, and 785 Zwetana, show variations in their radar albedo with rotation. We can rule out shape and composition in most cases, leaving variations in thickness, porosity, or surface roughness of the regolith to be the most likely causes. With the exception of 129 Antigone, we find no hydrated M-class asteroids (W-class; Rivkin, A.S., Howell, E.S., Lebofsky, L.A., Clark, B.E., Britt, D.T., 2000. Icarus 145, 351-368) to have high radar albedos.

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept

PubMed Central

Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-01-01

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme. PMID:29186850

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept.

PubMed

Shi, Chenguang; Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-11-25

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme.

Integrated Optic Signal Processors for Wideband Radar Systems.

DTIC Science & Technology

1980-05-01

md Identify by block number) Modules The general objecti1e-6ithis research oxogram-is to explore the potential of integrated acoustooptic’tec lol...and D activities. The major objectives of this research are to (Continued on ex Pae’ D ’’OR 1473k EDITION OF I NOV S5 IS OUSOLtTE 71 . ~- " SET~Y...CLASSIFICATION OF THIS PAGE (When bae Entered) SECURITY CLASSIFICATION OF THIS PAGE(When Data ihtered) carry out research on integrated acoustooptic

Column Network Study for a Planar Array Used with an Unattended Radar

DTIC Science & Technology

1980-06-01

This will assist us In maintaining a current mailing list. Do not return this copy. Retain or destroy. UNCLASSIFIED SECURITY CLASSIFICATION OF THIS...0.nt from Controlling Office) IS. SECURITY CLASS. (o1 this report) SaetVŕ ’UDNCLASSIFIED IS.. DECL ASSI FIC ATI ON,’OWN GRADING t, / -/ ./N N...installation costs are being studied. "(Coni’d) DD I1JANp73 1473k EDITION OF I NOV 65 IS OBSOLETE UNCLASSIFIED SECURITY CLASSIFICATION OF THIS PAGE (When

Resolution versus speckle relative to geologic interpretability of spaceborne radar images - A survey of user preference

NASA Technical Reports Server (NTRS)

Ford, J. P.

1982-01-01

A survey conducted to evaluate user preference for resolution versus speckle relative to the geologic interpretability of spaceborne radar images is discussed. Thirteen different resolution/looks combinations are simulated from Seasat synthetic-aperture radar data of each of three test sites. The SAR images were distributed with questionnaires for analysis to 85 earth scientists. The relative discriminability of geologic targets at each test site for each simulation of resolution and speckle on the images is determined on the basis of a survey of the evaluations. A large majority of the analysts respond that for most targets a two-look image at the highest simulated resolution is best. For a constant data rate, a higher resolution is more important for target discrimination than a higher number of looks. It is noted that sand dunes require more looks than other geologic targets. At all resolutions, multiple-look images are preferred over the corresponding single-look image. In general, the number of multiple looks that is optimal for discriminating geologic targets is inversely related to the simulated resolution.

Results from the Maine 1992 foliage penetration experiment

NASA Astrophysics Data System (ADS)

Toups, Michael F.; Ayasli, Serpil

1993-11-01

In order to investigate the detection of targets which are hidden by foliage, an experiment was designed which utilized a forest region located near Portage, Maine. The experiment was designed to address four issues. First, the properties of the backscatter or clutter which competes with the desired target were investigated. Second, the foliage induced attenuation that is experienced by the radar energy traversing the foliage were measured. Third, the ability of a synthetic aperture radar system to focus on a target obscured by foliage was investigated. Fourth, target signatures of foliage obscured and unobscured targets were measured. The forest region was investigated using two different airborne synthetic aperture radar (SAR) systems. A UHF wide-band SAR operated by SRI International was used as well as a L-, C-, and X-band SAR installed on a P-3 aircraft operated by the U.S. Navy. The SRI system was used to collect data over 16 square kilometers with repeat passes for verification of system performance. The P-3 system was used to collect over 50 square kilometers of data at three different depression angles with several repeat passes.

Detection technique of targets for missile defense system

NASA Astrophysics Data System (ADS)

Guo, Hua-ling; Deng, Jia-hao; Cai, Ke-rong

2009-11-01

Ballistic missile defense system (BMDS) is a weapon system for intercepting enemy ballistic missiles. It includes ballistic-missile warning system, target discrimination system, anti-ballistic-missile guidance systems, and command-control communication system. Infrared imaging detection and laser imaging detection are widely used in BMDS for surveillance, target detection, target tracking, and target discrimination. Based on a comprehensive review of the application of target-detection techniques in the missile defense system, including infrared focal plane arrays (IRFPA), ground-based radar detection technology, 3-dimensional imaging laser radar with a photon counting avalanche photodiode (APD) arrays and microchip laser, this paper focuses on the infrared and laser imaging detection techniques in missile defense system, as well as the trends for their future development.

Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case.

PubMed

Ao, Dongyang; Li, Yuanhao; Hu, Cheng; Tian, Weiming

2017-12-22

The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

Modified linear predictive coding approach for moving target tracking by Doppler radar

NASA Astrophysics Data System (ADS)

Ding, Yipeng; Lin, Xiaoyi; Sun, Ke-Hui; Xu, Xue-Mei; Liu, Xi-Yao

2016-07-01

Doppler radar is a cost-effective tool for moving target tracking, which can support a large range of civilian and military applications. A modified linear predictive coding (LPC) approach is proposed to increase the target localization accuracy of the Doppler radar. Based on the time-frequency analysis of the received echo, the proposed approach first real-time estimates the noise statistical parameters and constructs an adaptive filter to intelligently suppress the noise interference. Then, a linear predictive model is applied to extend the available data, which can help improve the resolution of the target localization result. Compared with the traditional LPC method, which empirically decides the extension data length, the proposed approach develops an error array to evaluate the prediction accuracy and thus, adjust the optimum extension data length intelligently. Finally, the prediction error array is superimposed with the predictor output to correct the prediction error. A series of experiments are conducted to illustrate the validity and performance of the proposed techniques.

Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

PubMed Central

Ao, Dongyang; Hu, Cheng; Tian, Weiming

2017-01-01

The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures. PMID:29271917

Classification and modeling of human activities using empirical mode decomposition with S-band and millimeter-wave micro-Doppler radars

NASA Astrophysics Data System (ADS)

Fairchild, Dustin P.; Narayanan, Ram M.

2012-06-01

The ability to identify human movements can be an important tool in many different applications such as surveillance, military combat situations, search and rescue operations, and patient monitoring in hospitals. This information can provide soldiers, security personnel, and search and rescue workers with critical knowledge that can be used to potentially save lives and/or avoid a dangerous situation. Most research involving human activity recognition is focused on using the Short-Time Fourier Transform (STFT) as a method of analyzing the micro-Doppler signatures. Because of the time-frequency resolution limitations of the STFT and because Fourier transform-based methods are not well-suited for use with non-stationary and nonlinear signals, we have chosen a different approach. Empirical Mode Decomposition (EMD) has been shown to be a valuable time-frequency method for processing non-stationary and nonlinear data such as micro-Doppler signatures and EMD readily provides a feature vector that can be utilized for classification. For classification, the method of a Support Vector Machine (SVMs) was chosen. SVMs have been widely used as a method of pattern recognition due to their ability to generalize well and also because of their moderately simple implementation. In this paper, we discuss the ability of these methods to accurately identify human movements based on their micro-Doppler signatures obtained from S-band and millimeter-wave radar systems. Comparisons will also be made based on experimental results from each of these radar systems. Furthermore, we will present simulations of micro-Doppler movements for stationary subjects that will enable us to compare our experimental Doppler data to what we would expect from an "ideal" movement.

Air-to-air radar flight testing

NASA Astrophysics Data System (ADS)

Scott, Randall E.

1988-06-01

This volume in the AGARD Flight Test Techniques Series describes flight test techniques, flight test instrumentation, ground simulation, data reduction and analysis methods used to determine the performance characteristics of a modern air-to-air (a/a) radar system. Following a general coverage of specification requirements, test plans, support requirements, development and operational testing, and management information systems, the report goes into more detailed flight test techniques covering a/a radar capabilities of: detection, manual acquisition, automatic acquisition, tracking a single target, and detection and tracking of multiple targets. There follows a section on additional flight test considerations such as electromagnetic compatibility, electronic countermeasures, displays and controls, degraded and backup modes, radome effects, environmental considerations, and use of testbeds. Other sections cover ground simulation, flight test instrumentation, and data reduction and analysis. The final sections deal with reporting and a discussion of considerations for the future and how they may affect radar flight testing.

Radar Studies in the Solar System

NASA Technical Reports Server (NTRS)

Shapiro, Irwin I.

1996-01-01

We aid in a study of the solar system by means of ground-based radar. We have concentrated on (1) developing the ephemerides needed to acquire radar data at Arecibo Observatory and (2) analyzing the resultant data to: test fundamental laws of gravitation; determine the size, shape, topography, and spin vectors of the targets; and study the surface properties of these objects, through their scattering law and polarization characteristics.

Studies on Radar and Non-radar Sensor Networks

DTIC Science & Technology

2006-06-15

the following sections. ubiquitous and persistent sensor sources such as "* Organic sensors (e.g., radar, electro- optic and infrared, III. SITUATION...repetition frequency (PRF). Under these circumstances, target RSN, but in noncoherent systems as well. The latter scenario is more challenging as...signal propagation models. Section III and IV analyzes coherent andseletio an Ga ssin u equl me n trge mo els In [3] noncoherent detection

Doppler-Only Synthetic Aperture Radar

DTIC Science & Technology

2006-12-01

5 B. TARGET RECOGNITION TECHNIQUES .................................................6 1. Cooperative Targets...6 3. Techniques ............................................................................................6 C. TARGET RECOGNITION...3. Implementation of High Range Resolution Techniques .................12 F. TWO-DIMENSIONAL IMAGING

Object recognition of ladar with support vector machine

NASA Astrophysics Data System (ADS)

Sun, Jian-Feng; Li, Qi; Wang, Qi

2005-01-01

Intensity, range and Doppler images can be obtained by using laser radar. Laser radar can detect much more object information than other detecting sensor, such as passive infrared imaging and synthetic aperture radar (SAR), so it is well suited as the sensor of object recognition. Traditional method of laser radar object recognition is extracting target features, which can be influenced by noise. In this paper, a laser radar recognition method-Support Vector Machine is introduced. Support Vector Machine (SVM) is a new hotspot of recognition research after neural network. It has well performance on digital written and face recognition. Two series experiments about SVM designed for preprocessing and non-preprocessing samples are performed by real laser radar images, and the experiments results are compared.

Space Radar Image of Manaus, Brazil

NASA Technical Reports Server (NTRS)

1999-01-01

These two images were created using data from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR). On the left is a false-color image of Manaus, Brazil acquired April 12, 1994, onboard space shuttle Endeavour. In the center of this image is the Solimoes River just west of Manaus before it combines with the Rio Negro to form the Amazon River. The scene is around 8 by 8 kilometers (5 by 5 miles) with north toward the top. The radar image was produced in L-band where red areas correspond to high backscatter at HH polarization, while green areas exhibit high backscatter at HV polarization. Blue areas show low backscatter at VV polarization. The image on the right is a classification map showing the extent of flooding beneath the forest canopy. The classification map was developed by SIR-C/X-SAR science team members at the University of California,Santa Barbara. The map uses the L-HH, L-HV, and L-VV images to classify the radar image into six categories: Red flooded forest Green unflooded tropical rain forest Blue open water, Amazon river Yellow unflooded fields, some floating grasses Gray flooded shrubs Black floating and flooded grasses Data like these help scientists evaluate flood damage on a global scale. Floods are highly episodic and much of the area inundated is often tree-covered. Spaceborne Imaging Radar-C and X-Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory. X-SAR was developed by the Dornier and Alenia Spazio companies for the German space agency, Deutsche Agentur fuer Raumfahrtangelegenheiten (DARA), and the Italian space agency, Agenzia Spaziale Italiana (ASI), with the Deutsche Forschungsanstalt fuer Luft und Raumfahrt e.v. (DLR), the major partner in science, operations and data processing of X-SAR.

Sleep stage classification by non-contact vital signs indices using Doppler radar sensors.

PubMed

Kagawa, Masayuki; Suzumura, Kazuki; Matsui, Takemi

2016-08-01

Disturbed sleep has become more common in recent years. To improve the quality of sleep, undergoing sleep observation has gained interest as a means to resolve possible problems. In this paper, we evaluate a non-restrictive and non-contact method for classifying real-time sleep stages and report on its potential applications. The proposed system measures heart rate (HR), heart rate variability (HRV), body movements, and respiratory signals of a sleeping person using two 24-GHz microwave radars placed beneath the mattress. We introduce a method that dynamically selects the window width of the moving average filter to extract the pulse waves from the radar output signals. The Pearson correlation coefficient between two HR measurements derived from the radars overnight, and the reference polysomnography was the average of 88.3% and the correlation coefficient for HRV parameters was the average of 71.2%. For identifying wake and sleep periods, the body-movement index reached sensitivity of 76.0%, and a specificity of 77.0% with 10 participants. Low-frequency (LF) components of HRV and the LF/HF ratio had a high degree of contribution and differed significantly across the three sleep stages (REM, LIGHT, and DEEP; p <; 0.01). In contrast, high-frequency (HF) components of HRV were not significantly different across the three sleep stages (p > 0.05). We applied a canonical discriminant analysis to identify wake or sleep periods and to classify the three sleep stages with leave-one-out cross validation. Classification accuracy was 66.4% for simply identifying wake and sleep, 57.1% for three stages (wake, REM, and NREM) and 34% for four stages (wake, REM, LIGHT, and DEEP). This is a novel system for measuring HRs, HRV, body movements, and respiratory intervals and for measuring high sensitivity pulse waves using two radar signals. It simplifies measurement of sleep stages and may be employed at nursing care facilities or by the general public to improve sleep quality.

Earthquake Building Damage Mapping Based on Feature Analyzing Method from Synthetic Aperture Radar Data

NASA Astrophysics Data System (ADS)

An, L.; Zhang, J.; Gong, L.

2018-04-01

Playing an important role in gathering information of social infrastructure damage, Synthetic Aperture Radar (SAR) remote sensing is a useful tool for monitoring earthquake disasters. With the wide application of this technique, a standard method, comparing post-seismic to pre-seismic data, become common. However, multi-temporal SAR processes, are not always achievable. To develop a post-seismic data only method for building damage detection, is of great importance. In this paper, the authors are now initiating experimental investigation to establish an object-based feature analysing classification method for building damage recognition.

Tracking techniques for space shuttle rendezvous

NASA Technical Reports Server (NTRS)

1975-01-01

The space shuttle rendezvous radar has a requirement to track cooperative and non-cooperative targets. For this reason the Lunar Module (LM) Rendezvous Radar was modified to incorporate the capability of tracking a non-cooperative target. The modifications are discussed. All modifications except those relating to frequency diversity were completed, and system tests were performed to confirm proper performance in the non-cooperative mode. Frequency diversity was added to the radar and to the special test equipment, and then system tests were performed. This last set of tests included re-running the tests of the non-cooperative mode without frequency diversity, followed by tests with frequency diversity and tests of operation in the original cooperative mode.

An Efficient Estimator for Moving Target Localization Using Multi-Station Dual-Frequency Radars.

PubMed

Huang, Jiyan; Zhang, Ying; Luo, Shan

2017-12-15

Localization of a moving target in a dual-frequency radars system has now gained considerable attention. The noncoherent localization approach based on a least squares (LS) estimator has been addressed in the literature. Compared with the LS method, a novel localization method based on a two-step weighted least squares estimator is proposed to increase positioning accuracy for a multi-station dual-frequency radars system in this paper. The effects of signal noise ratio and the number of samples on the performance of range estimation are also analyzed in the paper. Furthermore, both the theoretical variance and Cramer-Rao lower bound (CRLB) are derived. The simulation results verified the proposed method.

An Efficient Estimator for Moving Target Localization Using Multi-Station Dual-Frequency Radars

PubMed Central

Zhang, Ying; Luo, Shan

2017-01-01

Localization of a moving target in a dual-frequency radars system has now gained considerable attention. The noncoherent localization approach based on a least squares (LS) estimator has been addressed in the literature. Compared with the LS method, a novel localization method based on a two-step weighted least squares estimator is proposed to increase positioning accuracy for a multi-station dual-frequency radars system in this paper. The effects of signal noise ratio and the number of samples on the performance of range estimation are also analyzed in the paper. Furthermore, both the theoretical variance and Cramer–Rao lower bound (CRLB) are derived. The simulation results verified the proposed method. PMID:29244727

Portable concealed weapon detection using millimeter-wave FMCW radar imaging

NASA Astrophysics Data System (ADS)

Johnson, Michael A.; Chang, Yu-Wen

2001-02-01

Unobtrusive detection of concealed weapons on persons or in abandoned bags would provide law enforcement a powerful tool to focus resources and increase traffic throughput in high- risk situations. We have developed a fast image scanning 94 GHz radar system that is suitable for portable operation and remote viewing of radar data. This system includes a novel fast image-scanning antenna that allows for the acquisition of medium resolution 3D millimeter wave images of stationary targets with frame times on order of one second. The 3D radar data allows for potential isolation of concealed weapons from body and environmental clutter such as nearby furniture or other people. The radar is an active system so image quality is not affected indoors, emitted power is however very low so there are no health concerns for operator or targets. The low power operation is still sufficient to penetrate heavy clothing or material. Small system size allows for easy transport and rapid deployment of the system as well as an easy migration path to future hand held systems.

Radar modulation classification using time-frequency representation and nonlinear regression

NASA Astrophysics Data System (ADS)

De Luigi, Christophe; Arques, Pierre-Yves; Lopez, Jean-Marc; Moreau, Eric

1999-09-01

In naval electronic environment, pulses emitted by radars are collected by ESM receivers. For most of them the intrapulse signal is modulated by a particular law. To help the classical identification process, a classification and estimation of this modulation law is applied on the intrapulse signal measurements. To estimate with a good accuracy the time-varying frequency of a signal corrupted by an additive noise, one method has been chosen. This method consists on the Wigner distribution calculation, the instantaneous frequency is then estimated by the peak location of the distribution. Bias and variance of the estimator are performed by computed simulations. In a estimated sequence of frequencies, we assume the presence of false and good estimated ones, the hypothesis of Gaussian distribution is made on the errors. A robust non linear regression method, based on the Levenberg-Marquardt algorithm, is thus applied on these estimated frequencies using a Maximum Likelihood Estimator. The performances of the method are tested by using varied modulation laws and different signal to noise ratios.

Comparisons of neural networks to standard techniques for image classification and correlation

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1994-01-01

Neural network techniques for multispectral image classification and spatial pattern detection are compared to the standard techniques of maximum-likelihood classification and spatial correlation. The neural network produced a more accurate classification than maximum-likelihood of a Landsat scene of Tucson, Arizona. Some of the errors in the maximum-likelihood classification are illustrated using decision region and class probability density plots. As expected, the main drawback to the neural network method is the long time required for the training stage. The network was trained using several different hidden layer sizes to optimize both the classification accuracy and training speed, and it was found that one node per class was optimal. The performance improved when 3x3 local windows of image data were entered into the net. This modification introduces texture into the classification without explicit calculation of a texture measure. Larger windows were successfully used for the detection of spatial features in Landsat and Magellan synthetic aperture radar imagery.

A HWIL test facility of infrared imaging laser radar using direct signal injection

NASA Astrophysics Data System (ADS)

Wang, Qian; Lu, Wei; Wang, Chunhui; Wang, Qi

2005-01-01

Laser radar has been widely used these years and the hardware-in-the-loop (HWIL) testing of laser radar become important because of its low cost and high fidelity compare with On-the-Fly testing and whole digital simulation separately. Scene generation and projection two key technologies of hardware-in-the-loop testing of laser radar and is a complicated problem because the 3D images result from time delay. The scene generation process begins with the definition of the target geometry and reflectivity and range. The real-time 3D scene generation computer is a PC based hardware and the 3D target models were modeled using 3dsMAX. The scene generation software was written in C and OpenGL and is executed to extract the Z-buffer from the bit planes to main memory as range image. These pixels contain each target position x, y, z and its respective intensity and range value. Expensive optical injection technologies of scene projection such as LDP array, VCSEL array, DMD and associated scene generation is ongoing. But the optical scene projection is complicated and always unaffordable. In this paper a cheaper test facility was described that uses direct electronic injection to provide rang images for laser radar testing. The electronic delay and pulse shaping circuits inject the scenes directly into the seeker's signal processing unit.

Initial processing and analysis of forward- and side-looking data from the Spectrally Agile Frequency-Incrementing Reconfigurable (SAFIRE) radar

NASA Astrophysics Data System (ADS)

Ranney, Kenneth; Phelan, Brian; Sherbondy, Kelly; Kirose, Getachew; Smith, Gregory; Clark, John; Harrison, Arthur; Ressler, Marc; Nguyen, Lam; Narayanan, Ram

2017-05-01

A new, versatile, UHF/L band, ultrawideband (UWB), vehicle-mounted radar system developed at the U.S. Army Research Laboratory (ARL) has recently been exercised at an arid U.S. test site. The unique switching scheme implemented to record data from all receive channels is described, along with the current calibration procedure. Radar and global positioning system (GPS) data collected in both forwardand side-looking configurations are processed, and synthetic aperture radar (SAR) images are formed. Results are presented for various target emplacement scenarios.

Radar investigation of asteroids

NASA Astrophysics Data System (ADS)

Ostro, S. J.

1984-07-01

The initial radar observations of the mainbelt asteroids 9 Metis, 27 Euterpe, and 60 Echo are examined. For each target, data are taken simultaneously in the same sense of circular polarization as transmitted as well as in the opposite (OC) sense. Estimates of the radar cross sections provide estimates of the circular polarization ratio, and the normalized OC radar cross section. The circular polarization ratio, is comparable to values measured for other large S type asteroids and for a few much smaller, Earth approaching objects, most of the echo is due to single reflection backscattering from smooth surface elements.

Radar investigation of asteroids

NASA Technical Reports Server (NTRS)

Ostro, S. J.

1984-01-01

The initial radar observations of the mainbelt asteroids 9 Metis, 27 Euterpe, and 60 Echo are examined. For each target, data are taken simultaneously in the same sense of circular polarization as transmitted as well as in the opposite (OC) sense. Estimates of the radar cross sections provide estimates of the circular polarization ratio, and the normalized OC radar cross section. The circular polarization ratio, is comparable to values measured for other large S type asteroids and for a few much smaller, Earth approaching objects, most of the echo is due to single reflection backscattering from smooth surface elements.

Simulation of laser radar tooling ball measurements: focus dependence

NASA Astrophysics Data System (ADS)

Smith, Daniel G.; Slotwinski, Anthony; Hedges, Thomas

2015-10-01

The Nikon Metrology Laser Radar system focuses a beam from a fiber to a target object and receives the light scattered from the target through the same fiber. The system can, among other things, make highly accurate measurements of the position of a tooling ball by locating the angular position of peak signal quality, which is related to the fiber coupling efficiency. This article explores the relationship between fiber coupling efficiency and focus condition.

Review of Current Aided/Automatic Target Acquisition Technology for Military Target Acquisition Tasks

DTIC Science & Technology

2011-07-01

radar [e.g., synthetic aperture radar (SAR)]. EO/IR includes multi- and hyperspectral imaging. Signal processing of data from nonimaging sensors, such...enhanced recognition ability. Other nonimage -based techniques, such as category theory,45 hierarchical systems,46 and gradient index flow,47 are possible...the battle- field. There is a plethora of imaging and nonimaging sensors on the battlefield that are being networked together for trans- mission of

Multitarget detection algorithm for automotive FMCW radar

NASA Astrophysics Data System (ADS)

Hyun, Eugin; Oh, Woo-Jin; Lee, Jong-Hun

2012-06-01

Today, 77 GHz FMCW (Frequency Modulation Continuous Wave) radar has strong advantages of range and velocity detection for automotive applications. However, FMCW radar brings out ghost targets and missed targets in multi-target situations. In this paper, in order to resolve these limitations, we propose an effective pairing algorithm, which consists of two steps. In the proposed method, a waveform with different slopes in two periods is used. In the 1st pairing processing, all combinations of range and velocity are obtained in each of two wave periods. In the 2nd pairing step, using the results of the 1st pairing processing, fine range and velocity are detected. In that case, we propose the range-velocity windowing technique in order to compensate for the non-ideal beat-frequency characteristic that arises due to the non-linearity of the RF module. Based on experimental results, the performance of the proposed algorithm is improved compared with that of the typical method.

Complex phase error and motion estimation in synthetic aperture radar imaging

NASA Astrophysics Data System (ADS)

Soumekh, M.; Yang, H.

1991-06-01

Attention is given to a SAR wave equation-based system model that accurately represents the interaction of the impinging radar signal with the target to be imaged. The model is used to estimate the complex phase error across the synthesized aperture from the measured corrupted SAR data by combining the two wave equation models governing the collected SAR data at two temporal frequencies of the radar signal. The SAR system model shows that the motion of an object in a static scene results in coupled Doppler shifts in both the temporal frequency domain and the spatial frequency domain of the synthetic aperture. The velocity of the moving object is estimated through these two Doppler shifts. It is shown that once the dynamic target's velocity is known, its reconstruction can be formulated via a squint-mode SAR geometry with parameters that depend upon the dynamic target's velocity.

Wavelet Filter Banks for Super-Resolution SAR Imaging

NASA Technical Reports Server (NTRS)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

New inverse synthetic aperture radar algorithm for translational motion compensation

NASA Astrophysics Data System (ADS)

Bocker, Richard P.; Henderson, Thomas B.; Jones, Scott A.; Frieden, B. R.

1991-10-01

Inverse synthetic aperture radar (ISAR) is an imaging technique that shows real promise in classifying airborne targets in real time under all weather conditions. Over the past few years a large body of ISAR data has been collected and considerable effort has been expended to develop algorithms to form high-resolution images from this data. One important goal of workers in this field is to develop software that will do the best job of imaging under the widest range of conditions. The success of classifying targets using ISAR is predicated upon forming highly focused radar images of these targets. Efforts to develop highly focused imaging computer software have been challenging, mainly because the imaging depends on and is affected by the motion of the target, which in general is not precisely known. Specifically, the target generally has both rotational motion about some axis and translational motion as a whole with respect to the radar. The slant-range translational motion kinematic quantities must be first accurately estimated from the data and compensated before the image can be focused. Following slant-range motion compensation, the image is further focused by determining and correcting for target rotation. The use of the burst derivative measure is proposed as a means to improve the computational efficiency of currently used ISAR algorithms. The use of this measure in motion compensation ISAR algorithms for estimating the slant-range translational motion kinematic quantities of an uncooperative target is described. Preliminary tests have been performed on simulated as well as actual ISAR data using both a Sun 4 workstation and a parallel processing transputer array. Results indicate that the burst derivative measure gives significant improvement in processing speed over the traditional entropy measure now employed.

Use of radar QPE for the derivation of Intensity-Duration-Frequency curves in a range of climatic regimes

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2015-12-01

Intensity-Duration-Frequency (IDF) curves are widely used in flood risk management because they provide an easy link between the characteristics of a rainfall event and the probability of its occurrence. Weather radars provide distributed rainfall estimates with high spatial and temporal resolutions and overcome the scarce representativeness of point-based rainfall for regions characterized by large gradients in rainfall climatology. This work explores the use of radar quantitative precipitation estimation (QPE) for the identification of IDF curves over a region with steep climatic transitions (Israel) using a unique radar data record (23 yr) and combined physical and empirical adjustment of the radar data. IDF relationships were derived by fitting a generalized extreme value distribution to the annual maximum series for durations of 20 min, 1 h and 4 h. Arid, semi-arid and Mediterranean climates were explored using 14 study cases. IDF curves derived from the study rain gauges were compared to those derived from radar and from nearby rain gauges characterized by similar climatology, taking into account the uncertainty linked with the fitting technique. Radar annual maxima and IDF curves were generally overestimated but in 70% of the cases (60% for a 100 yr return period), they lay within the rain gauge IDF confidence intervals. Overestimation tended to increase with return period, and this effect was enhanced in arid climates. This was mainly associated with radar estimation uncertainty, even if other effects, such as rain gauge temporal resolution, cannot be neglected. Climatological classification remained meaningful for the analysis of rainfall extremes and radar was able to discern climatology from rainfall frequency analysis.

Snow Radar Derived Surface Elevations and Snow Depths Multi-Year Time Series over Greenland Sea-Ice During IceBridge Campaigns

NASA Astrophysics Data System (ADS)

Perkovic-Martin, D.; Johnson, M. P.; Holt, B.; Panzer, B.; Leuschen, C.

2012-12-01

This paper presents estimates of snow depth over sea ice from the 2009 through 2011 NASA Operation IceBridge [1] spring campaigns over Greenland and the Arctic Ocean, derived from Kansas University's wideband Snow Radar [2] over annually repeated sea-ice transects. We compare the estimates of the top surface interface heights between NASA's Atmospheric Topographic Mapper (ATM) [3] and the Snow Radar. We follow this by comparison of multi-year snow depth records over repeated sea-ice transects to derive snow depth changes over the area. For the purpose of this paper our analysis will concentrate on flights over North/South basin transects off Greenland, which are the closest overlapping tracks over this time period. The Snow Radar backscatter returns allow for surface and interface layer types to be differentiated between snow, ice, land and water using a tracking and classification algorithm developed and discussed in the paper. The classification is possible due to different scattering properties of surfaces and volumes at the radar's operating frequencies (2-6.5 GHz), as well as the geometries in which they are viewed by the radar. These properties allow the returns to be classified by a set of features that can be used to identify the type of the surface or interfaces preset in each vertical profile. We applied a Support Vector Machine (SVM) learning algorithm [4] to the Snow Radar data to classify each detected interface into one of four types. The SVM algorithm was trained on radar echograms whose interfaces were visually classified and verified against coincident aircraft data obtained by CAMBOT [5] and DMS [6] imaging sensors as well as the scanning ATM lidar. Once the interface locations were detected for each vertical profile we derived a range to each interface that was used to estimate the heights above the WGS84 ellipsoid for direct comparisons with ATM. Snow Radar measurements were calibrated against ATM data over areas free of snow cover and over GPS land surveyed areas of Thule and Sondrestrom air bases. The radar measurements were compared against the ATM and the GPS measurements that were located in the estimated radar footprints, which resulted in an overall error of ~ 0.3 m between the radar and ATM. The agreement between ATM and GPS survey is within +/- 0.1 m. References: [1] http://www.nasa.gov/mission_pages/icebridge/ [2] Panzer, B. et. al, "An ultra-wideband, microwave radar for measuring snow thickness on sea ice and mapping near-surface internal layers in polar firn," Submitted to J. of Glaciology Instr. and Tech., July 23, 2012. [3] Krabill, William B. 2009 and 2011, updated current year. IceBridge ATM L1B Qfit Elevation and Return Strength. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. [4] Chih-Chung Chang and Chih-Jen Lin. "Libsvm: a library for support vector machines", ACM Transactions on Intelligent Systems and Technology, 2:2:27:1-27:27, 2011. [5] Krabill, William B. 2009 and 2011, updated current year. IceBridge CAMBOT L1B Geolocated Images, [2009-04-25, 2011-04-15]. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media. [6] Dominguez, Roseanne. 2011, updated current year. IceBridge DMS L1B Geolocated and Orthorectified Images. Boulder, Colorado USA: National Snow and Ice Data Center. Digital media

Modeling and Simulation Architecture for Studying Doppler-Based Radar with Complex Environments

DTIC Science & Technology

2009-03-26

structures can interfere with a radar’s ability to detect moving aircraft because radar returns from turbines are comparable to those from slow flying...Netherlands Organisation for Applied Scientific Research . 13 EM Electromagnetic . . . . . . . . . . . . . . . . . . . . . . . 14 MTI Moving Target Indicator...ensure the turbine won’t interact with the radar. However, (2.3) doesn’t account for terrain masking or shadowing. If there is a tall object or terrain

Imaging terahertz radar for security applications

NASA Astrophysics Data System (ADS)

Semenov, Alexei; Richter, Heiko; Böttger, Ute; Hübers, Heinz-Wilhelm

2008-04-01

Detection of concealed threats is a key issue in public security. In short range applications, passive imagers operating at millimeter wavelengths fulfill this task. However, for larger distances, they will suffer from limited spatial resolution. We will describe the design and performance of 0.8-THz imaging radar that is capable to detect concealed objects at a distance of more than 20 meter. The radar highlights the target with the built-in cw transmitter and analyses the returned signal making use of a heterodyne receiver with a single superconducting hot-electron bolometric mixer. With an integration time of 0.3 sec, the receiver distinguishes a temperature difference of 2 K at the 20 m distance. Both the transmitter and the receiver use the same modified Gregorian telescope consisting from two offset elliptic mirrors. The primary mirror defines limits the lateral resolution of the radar to 2 cm at 20 m distance. At this distance, the field of view of the radar has the diameter 0.5 m. It is sampled with a high-speed conical scanner that allows for a frame time less than 5 sec. The transmitter delivers to the target power with a density less than ten microwatt per squared centimeter, which is harmless for human beings. The radar implements a sensor fusion technique that greatly improves the ability to identify concealed objects.

A Wavelet Polarization Decomposition Net Model for Polarimetric SAR Image Classification

NASA Astrophysics Data System (ADS)

He, Chu; Ou, Dan; Yang, Teng; Wu, Kun; Liao, Mingsheng; Chen, Erxue

2014-11-01

In this paper, a deep model based on wavelet texture has been proposed for Polarimetric Synthetic Aperture Radar (PolSAR) image classification inspired by recent successful deep learning method. Our model is supposed to learn powerful and informative representations to improve the generalization ability for the complex scene classification tasks. Given the influence of speckle noise in Polarimetric SAR image, wavelet polarization decomposition is applied first to obtain basic and discriminative texture features which are then embedded into a Deep Neural Network (DNN) in order to compose multi-layer higher representations. We demonstrate that the model can produce a powerful representation which can capture some untraceable information from Polarimetric SAR images and show a promising achievement in comparison with other traditional SAR image classification methods for the SAR image dataset.

Effect of H-wave polarization on laser radar detection of partially convex targets in random media.

PubMed

El-Ocla, Hosam

2010-07-01

A study on the performance of laser radar cross section (LRCS) of conducting targets with large sizes is investigated numerically in free space and random media. The LRCS is calculated using a boundary value method with beam wave incidence and H-wave polarization. Considered are those elements that contribute to the LRCS problem including random medium strength, target configuration, and beam width. The effect of the creeping waves, stimulated by H-polarization, on the LRCS behavior is manifested. Targets taking large sizes of up to five wavelengths are sufficiently larger than the beam width and are sufficient for considering fairly complex targets. Scatterers are assumed to have analytical partially convex contours with inflection points.

A distributed transmit beamforming synchronization strategy for multi-element radar systems

NASA Astrophysics Data System (ADS)

Xiao, Manlin; Li, Xingwen; Xu, Jikang

2017-02-01

The distributed transmit beamforming has recently been discussed as an energy-effective technique in wireless communication systems. A common ground of various techniques is that the destination node transmits a beacon signal or feedback to assist source nodes to synchronize signals. However, this approach is not appropriate for a radar system since the destination is a non-cooperative target of an unknown location. In our paper, we propose a novel synchronization strategy for a distributed multiple-element beamfoming radar system. Source nodes estimate parameters of beacon signals transmitted from others to get their local synchronization information. The channel information of the phase propagation delay is transmitted to nodes via the reflected beacon signals as well. Next, each node generates appropriate parameters to form a beamforming signal at the target. Transmit beamforming signals of all nodes will combine coherently at the target compensating for different propagation delay. We analyse the influence of the local oscillation accuracy and the parameter estimation errors on the performance of the proposed synchronization scheme. The results of numerical simulations illustrate that this synchronization scheme is effective to enable the transmit beamforming in a distributed multi-element radar system.

Hardware test program for evaluation of baseline range/range rate sensor concept

NASA Technical Reports Server (NTRS)

Pernic, E.

1985-01-01

The test program Phase II effort provides additional design information in terms of range and range rate (R/R) sensor performance when observing and tracking a typical spacecraft target. The target used in the test program was a one-third scale model of the Hubble Space Telescope (HST) available at the MSFC test site where the tests were performed. A modified Bendix millimeter wave radar served as the R/R sensor test bed for evaluation of range and range rate tracking performance, and generation of radar signature characteristics of the spacecraft target. A summary of program test results and conclusions are presented along with detailed description of the Bendix test bed radar with accompaning instrumentation. The MSFC test site and facilities are described. The test procedures used to establish background levels, and the calibration procedures used in the range accuracy tests and RCS (radar cross section) signature measurements, are presented and a condensed version of the daily log kept during the 5 September through 17 September test period is also presented. The test program results are given starting with the RCS signature measurements, then continuing with range measurement accuracy test results and finally the range and range rate tracking accuracy test results.

Data fusion approach to threat assessment for radar resources management

NASA Astrophysics Data System (ADS)

Komorniczak, Wojciech; Pietrasinski, Jerzy; Solaiman, Basel

2002-03-01

The paper deals with the problem of the multifunction radar resources management. The problem consists of target/tasks ranking and tasks scheduling. The paper is focused on the target ranking, with the data fusion approach. The data from the radar (object's velocity, range, altitude, direction etc.), IFF system (Identification Friend or Foe) and ESM system (Electronic Support Measures - information concerning threat's electro - magnetic activities) is used to decide of the importance assignment for each detected target. The main problem consists of the multiplicity of various types of the input information. The information from the radar is of the probabilistic or ambiguous imperfection type and the IFF information is of evidential type. To take the advantage of these information sources the advanced data fusion system is necessary. The system should deal with the following situations: fusion of the evidential and fuzzy information, fusion of the evidential information and a'priori information. The paper describes the system which fuses the fuzzy and the evidential information without previous change to the same type of information. It is also described the proposal of using of the dynamic fuzzy qualifiers. The paper shows the results of the preliminary system's tests.

Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia

NASA Astrophysics Data System (ADS)

Midekisa, Alemayehu; Senay, Gabriel B.; Wimberly, Michael C.

2014-11-01

Malaria is a major global public health problem, particularly in Sub-Saharan Africa. The spatial heterogeneity of malaria can be affected by factors such as hydrological processes, physiography, and land cover patterns. Tropical wetlands, for example, are important hydrological features that can serve as mosquito breeding habitats. Mapping and monitoring of wetlands using satellite remote sensing can thus help to target interventions aimed at reducing malaria transmission. The objective of this study was to map wetlands and other major land cover types in the Amhara region of Ethiopia and to analyze district-level associations of malaria and wetlands across the region. We evaluated three random forests classification models using remotely sensed topographic and spectral data based on Shuttle Radar Topographic Mission (SRTM) and Landsat TM/ETM+ imagery, respectively. The model that integrated data from both sensors yielded more accurate land cover classification than single-sensor models. The resulting map of wetlands and other major land cover classes had an overall accuracy of 93.5%. Topographic indices and subpixel level fractional cover indices contributed most strongly to the land cover classification. Further, we found strong spatial associations of percent area of wetlands with malaria cases at the district level across the dry, wet, and fall seasons. Overall, our study provided the most extensive map of wetlands for the Amhara region and documented spatiotemporal associations of wetlands and malaria risk at a broad regional level. These findings can assist public health personnel in developing strategies to effectively control and eliminate malaria in the region.

Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia

USGS Publications Warehouse

Midekisa, Alemayehu; Senay, Gabriel; Wimberly, Michael C.

2014-01-01

Malaria is a major global public health problem, particularly in Sub-Saharan Africa. The spatial heterogeneity of malaria can be affected by factors such as hydrological processes, physiography, and land cover patterns. Tropical wetlands, for example, are important hydrological features that can serve as mosquito breeding habitats. Mapping and monitoring of wetlands using satellite remote sensing can thus help to target interventions aimed at reducing malaria transmission. The objective of this study was to map wetlands and other major land cover types in the Amhara region of Ethiopia and to analyze district-level associations of malaria and wetlands across the region. We evaluated three random forests classification models using remotely sensed topographic and spectral data based on Shuttle Radar Topographic Mission (SRTM) and Landsat TM/ETM+ imagery, respectively. The model that integrated data from both sensors yielded more accurate land cover classification than single-sensor models. The resulting map of wetlands and other major land cover classes had an overall accuracy of 93.5%. Topographic indices and subpixel level fractional cover indices contributed most strongly to the land cover classification. Further, we found strong spatial associations of percent area of wetlands with malaria cases at the district level across the dry, wet, and fall seasons. Overall, our study provided the most extensive map of wetlands for the Amhara region and documented spatiotemporal associations of wetlands and malaria risk at a broad regional level. These findings can assist public health personnel in developing strategies to effectively control and eliminate malaria in the region.

Radar research on thunderstorms and lightning

NASA Technical Reports Server (NTRS)

Rust, W. D.; Doviak, R. J.

1982-01-01

Applications of Doppler radar to detection of storm hazards are reviewed. Normal radar sweeps reveal data on reflectivity fields of rain drops, ionized lightning paths, and irregularities in humidity and temperature. Doppler radar permits identification of the targets' speed toward or away from the transmitter through interpretation of the shifts in the microwave frequency. Wind velocity fields can be characterized in three dimensions by the use of two radar units, with a Nyquist limit on the highest wind speeds that may be recorded. Comparisons with models numerically derived from Doppler radar data show substantial agreement in storm formation predictions based on information gathered before the storm. Examples are provided of tornado observations with expanded Nyquist limits, gust fronts, turbulence, lightning and storm structures. Obtaining vertical velocities from reflectivity spectra is discussed.

New software methods in radar ornithology using WSR-88D weather data and potential application to monitoring effects of climate change on bird migration

USGS Publications Warehouse

Mead, Reginald; Paxton, John; Sojda, Richard S.; Swayne, David A.; Yang, Wanhong; Voinov, A.A.; Rizzoli, A.; Filatova, T.

2010-01-01

Radar ornithology has provided tools for studying the movement of birds, especially related to migration. Researchers have presented qualitative evidence suggesting that birds, or at least migration events, can be identified using large broad scale radars such as the WSR-88D used in the NEXRAD weather surveillance system. This is potentially a boon for ornithologists because such data cover a large portion of the United States, are constantly being produced, are freely available, and have been archived since the early 1990s. A major obstacle to this research, however, has been that identifying birds in NEXRAD data has required a trained technician to manually inspect a graphically rendered radar sweep. A single site completes one volume scan every five to ten minutes, producing over 52,000 volume scans in one year. This is an immense amount of data, and manual classification is infeasible. We have developed a system that identifies biological echoes using machine learning techniques. This approach begins with training data using scans that have been classified by experts, or uses bird data collected in the field. The data are preprocessed to ensure quality and to emphasize relevant features. A classifier is then trained using this data and cross validation is used to measure performance. We compared neural networks, naive Bayes, and k-nearest neighbor classifiers. Empirical evidence is provided showing that this system can achieve classification accuracies in the 80th to 90th percentile. We propose to apply these methods to studying bird migration phenology and how it is affected by climate variability and change over multiple temporal scales.

External calibration of polarimetric radars using point and distributed targets

NASA Technical Reports Server (NTRS)

Yueh, S. H.; Kong, J. A.; Shin, R. T.

1991-01-01

Polarimetric calibration algorithms using combinations of point targets and reciprocal distributed targets are developed. From the reciprocity relations of distributed targets, and equivalent point target response is derived. Then the problem of polarimetric calibration using two point targets and one distributed target reduces to that using three point targets, which has been previously solved. For calibration using one point target and one reciprocal distributed target, two cases are analyzed with the point target being a trihedral reflector or a polarimetric active radar calibrator (PARC). For both cases, the general solutions of the system distortion matrices are written as a product of a particular solution and a matrix with one free parameter. For the trihedral-reflector case, this free parameter is determined by assuming azimuthal symmetry for the distributed target. For the PARC case, knowledge of one ratio of two covariance matrix elements of the distributed target is required to solve for the free parameter. Numerical results are simulated to demonstrate the usefulness of the developed algorithms.

External calibration of polarimetric radars using point and distributed targets

NASA Astrophysics Data System (ADS)

Yueh, S. H.; Kong, J. A.; Shin, R. T.

1991-08-01

Polarimetric calibration algorithms using combinations of point targets and reciprocal distributed targets are developed. From the reciprocity relations of distributed targets, and equivalent point target response is derived. Then the problem of polarimetric calibration using two point targets and one distributed target reduces to that using three point targets, which has been previously solved. For calibration using one point target and one reciprocal distributed target, two cases are analyzed with the point target being a trihedral reflector or a polarimetric active radar calibrator (PARC). For both cases, the general solutions of the system distortion matrices are written as a product of a particular solution and a matrix with one free parameter. For the trihedral-reflector case, this free parameter is determined by assuming azimuthal symmetry for the distributed target. For the PARC case, knowledge of one ratio of two covariance matrix elements of the distributed target is required to solve for the free parameter. Numerical results are simulated to demonstrate the usefulness of the developed algorithms.

AGARD Flight Test Techniques Series. Volume 7. Air-to-Air Radar Flight Testing

DTIC Science & Technology

1988-06-01

enters the beam ), a different tilt angle should be used. The emphasis on setting the tilt angle may require a non - standard high accuracy tilt angle...is: the time from pilot designation on a non -maneuvering target to the time that the system achieves target range, range rate and angle tracking...minimal attenuation, distortion, or boresight Shift effects on the radar beam . Thus, radome design for airborne application io largely a process of

The Air Force Needs to Improve Cost-Effectiveness and Availability of the Joint Surveillance Target Attack Radar System (Redacted)

DTIC Science & Technology

2016-11-01

Target Attack Radar System Objective We determined whether the Air Force made cost-effective purchases on the performance-based logistics contract to... contract to Northrop Grumman Corporation to provide Total System Support Responsibility services to sustain 16 E-8C JSTARS aircraft. These services...customer support. The Total System Support Responsibility contract is valued at $7 billion, with a 6-year base period and 16 annual contract option

Signature analysis of ballistic missile warhead with micro-nutation in terahertz band

NASA Astrophysics Data System (ADS)

Li, Ming; Jiang, Yue-song

2013-08-01

In recent years, the micro-Doppler effect has been proposed as a new technique for signature analysis and extraction of radar targets. The ballistic missile is known as a typical radar target and has been paid many attentions for the complexities of its motions in current researches. The trajectory of a ballistic missile can be generally divided into three stages: boost phase, midcourse phase and terminal phase. The midcourse phase is the most important phase for radar target recognition and interception. In this stage, the warhead forms a typical micro-motion called micro-nutation which consists of three basic micro-motions: spinning, coning and wiggle. This paper addresses the issue of signature analysis of ballistic missile warhead in terahertz band via discussing the micro-Doppler effect. We establish a simplified model (cone-shaped) for the missile warhead followed by the micro-motion models including of spinning, coning and wiggle. Based on the basic formulas of these typical micro-motions, we first derive the theoretical formula of micro-nutation which is the main micro-motion of the missile warhead. Then, we calculate the micro-Doppler frequency in both X band and terahertz band via these micro-Doppler formulas. The simulations are given to show the superiority of our proposed method for the recognition and detection of radar micro targets in terahertz band.

Single-Side Two-Location Spotlight Imaging for Building Based on MIMO Through-Wall-Radar.

PubMed

Jia, Yong; Zhong, Xiaoling; Liu, Jiangang; Guo, Yong

2016-09-07

Through-wall-radar imaging is of interest for mapping the wall layout of buildings and for the detection of stationary targets within buildings. In this paper, we present an easy single-side two-location spotlight imaging method for both wall layout mapping and stationary target detection by utilizing multiple-input multiple-output (MIMO) through-wall-radar. Rather than imaging for building walls directly, the images of all building corners are generated to speculate wall layout indirectly by successively deploying the MIMO through-wall-radar at two appropriate locations on only one side of the building and then carrying out spotlight imaging with two different squint-views. In addition to the ease of implementation, the single-side two-location squint-view detection also has two other advantages for stationary target imaging. The first one is the fewer multi-path ghosts, and the second one is the smaller region of side-lobe interferences from the corner images in comparison to the wall images. Based on Computer Simulation Technology (CST) electromagnetic simulation software, we provide multiple sets of validation results where multiple binary panorama images with clear images of all corners and stationary targets are obtained by combining two single-location images with the use of incoherent additive fusion and two-dimensional cell-averaging constant-false-alarm-rate (2D CA-CFAR) detection.

Application of radar for automotive collision avoidance. Volume 1: Technical report

NASA Technical Reports Server (NTRS)

Lichtenberg, C. L. (Editor)

1987-01-01

The purpose of this project was research and development of an automobile collision avoidance radar system. The major finding was that the application of radar to the automobile collision avoidance problem deserves continued research even though the specific approach investigated in this effort did not perform adequately in its angle measurement capability. Additional findings were that: (1) preliminary performance requirements of a candidate radar system are not unreasonable; (2) the number and severity of traffic accidents could be reduced by using a collision avoidance radar system which observes a fairly wide (at least + or - 10 deg) field of view ahead of the vehicle; (3) the health radiation hazards of a probable radar design are not significant even when a large number of radar-equipped vehicles are considered; (4) effects of inclement weather on radar operation can be accommodated in most cases; (5) the phase monopulse radar technique as implemented demonstrated inferior angle measurement performance which warrants the recommendation of investigating alternative radar techniques; and (6) extended target and multipath effects, which presumably distort the amplitude and phase distribution across the antenna aperture, are responsible for the observed inadequate phase monopulse radar performance.

Micro-Doppler Ambiguity Resolution for Wideband Terahertz Radar Using Intra-Pulse Interference

PubMed Central

Yang, Qi; Qin, Yuliang; Deng, Bin; Wang, Hongqiang; You, Peng

2017-01-01

Micro-Doppler, induced by micro-motion of targets, is an important characteristic of target recognition once extracted via parameter estimation methods. However, micro-Doppler is usually too significant to result in ambiguity in the terahertz band because of its relatively high carrier frequency. Thus, a micro-Doppler ambiguity resolution method for wideband terahertz radar using intra-pulse interference is proposed in this paper. The micro-Doppler can be reduced several dozen times its true value to avoid ambiguity through intra-pulse interference processing. The effectiveness of this method is proved by experiments based on a 0.22 THz wideband radar system, and its high estimation precision and excellent noise immunity are verified by Monte Carlo simulation. PMID:28468257

Performance limits for exo-clutter Ground Moving Target Indicator (GMTI) radar.

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

Doerry, Armin Walter

2010-09-01

The performance of a Ground Moving Target Indicator (GMTI) radar system depends on a variety of factors, many which are interdependent in some manner. It is often difficult to 'get your arms around' the problem of ascertaining achievable performance limits, and yet those limits exist and are dictated by physics. This report identifies and explores those limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall GMTI radar system. While the information herein is not new to the literature, its collection into amore » single report hopes to offer some value in reducing the 'seek time'.« less

Micro-Doppler Ambiguity Resolution for Wideband Terahertz Radar Using Intra-Pulse Interference.

PubMed

Yang, Qi; Qin, Yuliang; Deng, Bin; Wang, Hongqiang; You, Peng

2017-04-29

Micro-Doppler, induced by micro-motion of targets, is an important characteristic of target recognition once extracted via parameter estimation methods. However, micro-Doppler is usually too significant to result in ambiguity in the terahertz band because of its relatively high carrier frequency. Thus, a micro-Doppler ambiguity resolution method for wideband terahertz radar using intra-pulse interference is proposed in this paper. The micro-Doppler can be reduced several dozen times its true value to avoid ambiguity through intra-pulse interference processing. The effectiveness of this method is proved by experiments based on a 0.22 THz wideband radar system, and its high estimation precision and excellent noise immunity are verified by Monte Carlo simulation.

Amplification of radar and lidar signatures using quantum sensors

NASA Astrophysics Data System (ADS)

Lanzagorta, Marco

2013-05-01

One of the major scientific thrusts from recent years has been to try to harness quantum phenomena to dramat­ ically increase the performance of a wide variety of classical devices. These advances in quantum information science have had a considerable impact on the development of photonic-based quantum sensors. Even though quantum radar and quantum lidar remain theoretical proposals, preliminary results suggest that these sensors have the potential of becoming disruptive technologies able to revolutionize reconnaissance systems. In this paper we will discuss how quantum entanglement can be exploited to increase the radar and lidar signature of rectangular targets. In particular, we will show how the effective visibility of the target is increased if observed with an entangled multi-photon quantum sensor.

Sequential feature selection for detecting buried objects using forward looking ground penetrating radar

NASA Astrophysics Data System (ADS)

Shaw, Darren; Stone, Kevin; Ho, K. C.; Keller, James M.; Luke, Robert H.; Burns, Brian P.

2016-05-01

Forward looking ground penetrating radar (FLGPR) has the benefit of detecting objects at a significant standoff distance. The FLGPR signal is radiated over a large surface area and the radar signal return is often weak. Improving detection, especially for buried in road targets, while maintaining an acceptable false alarm rate remains to be a challenging task. Various kinds of features have been developed over the years to increase the FLGPR detection performance. This paper focuses on investigating the use of as many features as possible for detecting buried targets and uses the sequential feature selection technique to automatically choose the features that contribute most for improving performance. Experimental results using data collected at a government test site are presented.

Polarization Characteristics of Coherent Waves

DTIC Science & Technology

2012-03-12

Columbus, OH, 1952. 9. F.T. Ulaby and C. Elachi, Radar Polarimetry for Geoscience Applications (Artech House, Inc., 1990). 10. H. Mott...15. J.R. Huynen, “Comments on Target Decomposition Theorems,” Direct and Inverse Methods in Radar Polarimetry , Part 1. NAO ASI Series (Kluwer

Frequency Diverse Array Radar

DTIC Science & Technology

2010-09-01

Postgraduate School Monterey, CA 93943-5000 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING /MONITORING AGENCY NAME( S ) AND ADDRESS(ES) N/A...given. Lastly, the radar applications of FDA are considered. The received power from a target at a fixed range is simulated in MATLAB and the

Mobile high-performance computing (HPC) for synthetic aperture radar signal processing

NASA Astrophysics Data System (ADS)

Misko, Joshua; Kim, Youngsoo; Qi, Chenchen; Sirkeci, Birsen

2018-04-01

The importance of mobile high-performance computing has emerged in numerous battlespace applications at the tactical edge in hostile environments. Energy efficient computing power is a key enabler for diverse areas ranging from real-time big data analytics and atmospheric science to network science. However, the design of tactical mobile data centers is dominated by power, thermal, and physical constraints. Presently, it is very unlikely to achieve required computing processing power by aggregating emerging heterogeneous many-core processing platforms consisting of CPU, Field Programmable Gate Arrays and Graphic Processor cores constrained by power and performance. To address these challenges, we performed a Synthetic Aperture Radar case study for Automatic Target Recognition (ATR) using Deep Neural Networks (DNNs). However, these DNN models are typically trained using GPUs with gigabytes of external memories and massively used 32-bit floating point operations. As a result, DNNs do not run efficiently on hardware appropriate for low power or mobile applications. To address this limitation, we proposed for compressing DNN models for ATR suited to deployment on resource constrained hardware. This proposed compression framework utilizes promising DNN compression techniques including pruning and weight quantization while also focusing on processor features common to modern low-power devices. Following this methodology as a guideline produced a DNN for ATR tuned to maximize classification throughput, minimize power consumption, and minimize memory footprint on a low-power device.