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Synthetic Aperture Radar Sar Automatic Target Recognition Atr Parametric Study
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Book Synopsis Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) Parametric Study by :
Download or read book Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) Parametric Study written by and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAR ATR is a very complex problem that still has not been mastered. SAR ATR is difficult largely due to the fact that SAR imagery exhibits large variability. SAR imagery is a function of many variables called operating conditions (OCs) that can be subdivided into three large groups. The three main OCs are target, environment, and sensor. Sensor operating conditions deal with the properties of the sensor that have some of the largest effects on the formation of SAR images, including depression angle, squint angle, frequency, PRF, polarization, single/multi-look, sensor abnormalities, noise level, strip versus spot, and resolution. In the development and testing of SAR ATR algorithms to date the effects of sensor OCs have been given very little thought. The ultimate objective of this study is to develop a road map for studying various effects of varying sensor OCs on the performance of SAR ATR algorithms. For achieving this goal, we conducted literature searches to see how much had been done in sensor OC study. We also studied alternative data sources and the ways to generate SAR data related to the variation of sensor OCs to support SAR parametric study. In addition, we allocated and implemented a number of baseline ATR algorithms for the evaluation of their performance under the variation of sensor OCs. Our research has established an experimental paradigm for SAR parametric study.
Book Synopsis Context and Quasi-Invariants in Automatic Target Recognition (ATR) with Synthetic Aperture Radar (SAR) Imagery by :
Download or read book Context and Quasi-Invariants in Automatic Target Recognition (ATR) with Synthetic Aperture Radar (SAR) Imagery written by and published by . This book was released on 2000 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report focuses on the development of an automatic target recognition (ATR) system using high resolution synthetic aperture radar (SAR) imagery. The system achieves 95 to 100 percent recognition rates when applied to a set of MSTAR images. Typically, the system takes less than one minute to match an input image to a candidate vehicle class with Matlab programs running on a Pentium II 300 MHz machine. Experiments based on conventional recognition techniques were conducted for comparisons. Study of persistent scattering confirms the feasibility of implementing a SAR ATR system using physical image features. A new generic vehicle model, parameterized by the length, width, and orientation of a target is used in a two-phase recognition process with hypothesis generation and verification aimed at addressing the combinatorial target recognition problem. In the hypothesis generation stage, a few likely candidate target classes are identified from a target database with positive evidence. The candidates are assessed using both positive and negative evidence in the hypothesis verification stage. Leading surface estimation, image alignment, Delaunay walk, and recognition metrics are introduced to improve performance of the SAR ATR system.
Book Synopsis Statistical Pattern Recognition for Synthetic Aperture Radar (SAR)/Automatic Target Recognition (ATR). Volume 2 by :
Download or read book Statistical Pattern Recognition for Synthetic Aperture Radar (SAR)/Automatic Target Recognition (ATR). Volume 2 written by and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art research on spectral estimation, feature extraction, and pattern recognition algorithms are presented for radar signal processing and automatic target recognition. Advanced space-time spectral estimation algorithms are presented for multiple moving target feature extraction as well as clutter and jamming suppression for airborne high range resolution (HRR) phased-array radar. A nonparametric adaptive filtering-based approach, referred to as the Gapped-data Amplitude and Phase EStimation (GAPES) algorithm, is proposed for the spectral analysis of gapped data sequences as well as synthetic aperture radar (SAR) imaging with angle diversity data fusion. A QUasi-parametric ALgorithm for target feature Extraction (QUALE) algorithm is also investigated for angle diversity data fusion. Support Vector Machines (SVMs) as compared with other advanced classifiers in the MSTAR Public Domain Release and HRR data are found to outperform neural networks and matched filters. A new concept to create negative examples from the known target class is presented and shown to tremendously improve the rejection of confusers. Finally, Information Theoretic Learning (ITL) is proposed as a new algorithm to demix HRR signatures of closely parked targets.
Book Synopsis Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) by : David Blacknell
Download or read book Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) written by David Blacknell and published by IET. This book was released on 2013-08-23 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radar Automatic Target Recognition (ATR) and NonCooperative Target Recognition (NCTR) captures material presented by leading international experts at a NATO lecture series and explores both the fundamentals of classification techniques applied to data from a variety of radar modes and selected advanced techniques at the forefront of research. The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge, although steady progress has been made over the past couple of decades. This book explores both the fundamentals of classification techniques applied to data from a variety of radar modes and selected advanced techniques at the forefront of research. Topics include: the problem as applied to the ground, air and maritime domains; impact of image quality on the overall target recognition performance; performance of different approaches to the classifier algorithm; improvement in performance to be gained when a target can be viewed from more than one perspective; ways in which natural systems perform target recognition; impact of compressive sensing; advances in change detection, including coherent change detection; and challenges and directions for future research.
Book Synopsis Adaptive Processing of SAR Data for ATR. by :
Download or read book Adaptive Processing of SAR Data for ATR. written by and published by . This book was released on 2005 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Impact of Phase Information on Radar Automatic Target Recognition by : Linda Jennifer Moore
Download or read book Impact of Phase Information on Radar Automatic Target Recognition written by Linda Jennifer Moore and published by . This book was released on 2016 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional synthetic aperture radar (SAR) systems tend to discard phase information of formed complex radar imagery prior to automatic target recognition (ATR). This practice has historically been driven by available hardware storage, processing capabilities, and data link capacity. Recent advances in high performance computing (HPC) have enabled extremely dense storage and processing solutions. Therefore, previous motives for discarding radar phase information in ATR applications have been mitigated. First, we characterize the value of phase in one-dimensional (1-D) radar range profiles and two dimensional (2-D) SAR imagery with respect to the ability to correctly estimate target features, which are currently employed in ATR algorithms for target discrimination. These features correspond to physical characteristics of a target through radio frequency (RF) scattering phenomenology. Physics-based electromagnetic scattering models developed from the geometrical theory of diffraction are utilized for the information analysis presented here. Information is quantified by the error of target parameter estimates from noisy radar signals when phase is either retained or discarded. Operating conditions (OCs) of signal-to-noise ratio, bandwidth, and aperture extent are considered. Second, we investigate the value of phase in 1-D radar returns with respect to the ability to correctly classify canonical targets. Classification performance is evaluated via three techniques, namely, naïve Bayes, logistic regression and a bound on Bayes error rate (BER). These classification techniques maintain varying assumptions on the observed data set, with the BER bound making no assumptions. In each case, phase information is demonstrated to improve radar target classification rates.
Book Synopsis Algorithms for Synthetic Aperture Radar Imagery V by : Edmund G. Zelnio
Download or read book Algorithms for Synthetic Aperture Radar Imagery V written by Edmund G. Zelnio and published by SPIE-International Society for Optical Engineering. This book was released on 1998 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: A presentation of algorithms for synthetic aperture radar imagery. It studies: image formation; image registration and fusion; image quality assessment; and feature extraction.
Download or read book Automatic Target Recognition written by and published by . This book was released on 2007 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Automatic Target Recognition Using High-Range Resolution Data by :
Download or read book Automatic Target Recognition Using High-Range Resolution Data written by and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new algorithm is presented for Automatic Target Recognition (ATR) using High Range Resolution (HRR) profiles as opposed to traditional Synthetic Aperture Radar (SAR) images. ATR performance using SAR images degrades considerably in case of moving targets due to blurring caused in the cross-range domain. ATR based on HRR profiles, which are formed without Fourier transform in the cross-range, is expected to have superior performance for moving targets with the proposed method. One of the major contributions of this project so far has been the utilization of Eigen-templates as ATR features that are obtained via Singular Value Decomposition (SVD) of HRR profiles. SVD analysis of a large class of HRR data revealed that the Range-space eigenvectors corresponding to the largest singular value accounted for more than 90% of target energy. Hence, it has been proposed that the Range-space Eigen-vectors be used as templates for classification. The effectiveness of data normalization and Gaussianization of profile data in improving classification performance is also studied. With extensive simulation studies it is shown that the proposed Eigen-template based ATR approach provides consistent superior performance with recognition rate reaching 99.5% for the four class XPATCH database. This research project is being conducted in direct collaboration with the Sensors Directorate's ATR Assessment Branch, Wright Laboratories, Wright-Patt AFB, Dayton, Ohio, where it is being monitored by Dr. Rob Williams. A primary objective df this collaborative effort is to complement and augment various other ongoing research activities being conducted or supported by the Wright Labs ATR research team.
Book Synopsis ATR Performance Modeling and Estimation by : Dan E. Dudgeon
Download or read book ATR Performance Modeling and Estimation written by Dan E. Dudgeon and published by . This book was released on 1998 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this document is to assess the state of the art of performance modeling and estimation for synthetic aperture radar (SAR) automatic target recognition (ATR) algorithms. The study underlying this report is part of the Lincoln Laboratory effort under the OSD ATR Program. The intent is not to produce an exhaustive, detailed, voluminous report describing all ongoing efforts, but rather to capture in a succinct yet essentially complete way the approaches currently in use for modeling the performance of SAR ATR algorithms. To provide context for this document's assessment and recommendations, a brief discussion of the breadth of ATR problems and some of the resulting technical challenges will be conducted. This discussion will generally be couched in terms of the SAR ground surveillance problem of detecting and recognizing various military vehicles, though many of the statements are easily extended to other sensors and other applications. Basic performance metrics will be defined, and a discussion will ensue of the kinds of questions it would be useful to have addressed by a performance model. The principal approaches to modeling the performance of SAR ATR algorithms and estimating performance characteristics under a variety of conditions will then be outlined and assessed. The document concludes by recommending certain actions to encourage progress in the development of SAR ATR performance modeling and evaluation tools and methodologies.
Book Synopsis Search and Rescue Synthetic Apperture Radar SAR2 by :
Download or read book Search and Rescue Synthetic Apperture Radar SAR2 written by and published by . This book was released on 1995 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Automatic Target Recognition for Synthetic Aperture Radar Imagery Data Using Hausdorff Distance Transform by : Alvin Wang
Download or read book Automatic Target Recognition for Synthetic Aperture Radar Imagery Data Using Hausdorff Distance Transform written by Alvin Wang and published by . This book was released on 2004 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic Target Recognition (ATR) is a pattern recognition technique used to detect targets in a defined area of interest. The objective of the research was to discover the potential of applying ATR to Synthetic Aperture Radar (SAR) images and to explore the opportunities of employing Hausdorff Distance Transform (HDT) on multiple feature sets.
Book Synopsis Algorithms for Synthetic Aperture Radar Imagery by :
Download or read book Algorithms for Synthetic Aperture Radar Imagery written by and published by . This book was released on 2007 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sparse Representations for Radar with MATLAB Examples by : Peter Knee
Download or read book Sparse Representations for Radar with MATLAB Examples written by Peter Knee and published by Springer Nature. This book was released on 2022-05-31 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the field of sparse representations is relatively new, research activities in academic and industrial research labs are already producing encouraging results. The sparse signal or parameter model motivated several researchers and practitioners to explore high complexity/wide bandwidth applications such as Digital TV, MRI processing, and certain defense applications. The potential signal processing advancements in this area may influence radar technologies. This book presents the basic mathematical concepts along with a number of useful MATLAB® examples to emphasize the practical implementations both inside and outside the radar field. Table of Contents: Radar Systems: A Signal Processing Perspective / Introduction to Sparse Representations / Dimensionality Reduction / Radar Signal Processing Fundamentals / Sparse Representations in Radar
Book Synopsis Understanding Synthetic Aperture Radar Images by : Chris Oliver
Download or read book Understanding Synthetic Aperture Radar Images written by Chris Oliver and published by SciTech Publishing. This book was released on 2004 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical reference shows SAR system designers and remote sensing specialists how to produce higher quality SAR images using data-driven algorithms, and apply powerful new techniques to measure and analyze SAR image content.
Book Synopsis Radar Signal Processing and Its Applications by : Jian Li
Download or read book Radar Signal Processing and Its Applications written by Jian Li and published by Springer. This book was released on 2013-12-21 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Radar Signal Processing and Its Applications brings together in one place important contributions and up-to-date research results in this fast-moving area. In twelve selected chapters, it describes the latest advances in architectures, design methods, and applications of radar signal processing. The contributors to this work were selected from the leading researchers and practitioners in the field. This work, originally published as Volume 14, Numbers 1-3 of the journal, Multidimensional Systems and Signal Processing, will be valuable to anyone working or researching in the field of radar signal processing. It serves as an excellent reference, providing insight into some of the most challenging issues being examined today.
Book Synopsis The Evaluation of Synthetic Aperture Radar Image Segmentation Algorithms in the Context of Automatic Target Recognition by :
Download or read book The Evaluation of Synthetic Aperture Radar Image Segmentation Algorithms in the Context of Automatic Target Recognition written by and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image segmentation is a process to extract and organize information energy in the image pixel space according to a prescribed feature set. It is often a key preprocess in automatic target recognition (ATR) algorithms. In many cases, the performance of image segmentation algorithms will have significant impact on the performance of ATR algorithms. Due to the variations in feature set definitions and the innovations in the segmentation processes, there is large number of image segmentation algorithms existing in the ATR world. The problem is which image segmentation algorithm performs best for an ATR application. There are a number of measures to evaluate the performance of segmentation algorithms, such as Percentage Pixels Same (pps), Partial Directed Hausdorff (pdh), and Complex Inner Product (cip). In the research, we found that the combination of the three measures shows effectiveness in the evaluation of segmentation algorithms against truth data (human master segmentation). However, we don't know what are the impact of those measures in the performance of ATR algorithms that are commonly measured by Probability of detection (PDet), Probability of false alarm (PFA), Probability of identification (PID), etc. In all practical situations, ATR boxes are implemented without human observer in the loop. The performance of synthetic aperture radar (SAR) image segmentation should be evaluated in the context of ATR rather than human observers.
