Download or read book Performance Analysis of Automatic Target Recognition Using High Resolution Radar written by Vikas S. Kedia and published by . This book was released on 1998 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Learning for Radar and Communications Automatic Target Recognition written by Uttam K. Majumder and published by Artech House. This book was released on 2020-07-31 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.

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.

Download or read book Physics of Automatic Target Recognition written by Firooz Sadjadi and published by Springer Science & Business Media. This book was released on 2007-09-04 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the roles of sensors, physics–based attributes, classification methods, and performance evaluation in automatic target recognition. It details target classification from small mine–like objects to large tactical vehicles. Also explored in the book are invariants of sensor and transmission transformations, which are crucial in the development of low latency and computationally manageable automatic target recognition systems.

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.

Download or read book Analysis of High Resolution Polarimetry Data of Static Targets in Automatic Target Recognition Context written by Nicholas M. Sandirasegaram and published by . This book was released on 2007 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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:

Download or read book Automatic Target Recognition Using High Resolution Radar Range profiles written by Steven P. Jacobs and published by . This book was released on 1997 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Design and Performance Analysis of a Configurable Hardware Solution of an Adaptive Automatic Target Recognition Algorithm written by Steven E. Morrison and published by . This book was released on 2001 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Analysis of Performance of Automatic Target Recognition Systems written by G. Marino and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: An Automatic Target Recognition (ATR) system is a sensor which is usually able to recognize targets or objects based on gathered data. The application of automatic target recognition technology is a critical element of robotic warfare. ATR systems are used in unmanned aerial vehicles and cruise missiles. There are many systems which are able to collect data (e.g. radar sensor, electro-optic sensor, infra-red devices) which are commonly used to collect information and detect, recognise and classify potential targets. Despite significant effort during the last decades, some problems in ATR systems have not been solved yet. This Ph. D. tried to understand the variation of the information content into an ATR system and how to measure as well as how to preserve information when it passes through the processing chain because they have not been investigated properly yet. Moreover the investigation focused also on the definition of class-separability in ATR system and on the definition of the degree of separability. As a consequence, experiments have been performed for understanding how to assess the degree of class-separability and how the choice of the parameters of an ATR system can affect the final classifier performance (i.e. selecting the most reliable as well as the most information ii iii preserving ones). As results of the investigations of this thesis, some important results have been obtained: Definition of the class-separability and of the degree of classseparability (i.e. the requirements that a metric for class-separability has to satisfy); definition of a new metric for assessing the degree of classseparability; definition of the most important parameters which affect the classifier performance or reduce/increase the degree of class-separability (i.e. Signal to Clutter Ratio, Clutter models, effects of despeckling processing). Particularly the definition of metrics for assessing the presence of artefacts introduced by denoising algorithms, the ability of denoising algorithms in preserving geometrical features of potential targets, the suitability of current mathematical models at each stage of processing chain (especially for clutter models in radar systems) and the measurement of variation of information content through the processing chain are some of them most important issues which have been investigated.

Download or read book Automatic Target Recognition written by Bruce Jay Schachter and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This third edition of Automatic Target Recognition provides a roadmap for breakthrough ATR designs with increased intelligence, performance, and autonomy. Clear distinctions are made between military problems and comparable commercial Deep Learning problems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. A reference design is provided for a next-generation ATR that can continuously learn from and adapt to its environment. The convergence of diverse forms of data on a single platform supports new capabilities and improved performance. This third edition broadens the notion of ATR to multisensor fusion. Radical continuous-learning ATR architectures, better integration of data sources, well-packaged sensors, and low-power teraflop chips will enable transformative military designs"--

Download or read book Automatic Target Recognition written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-07-04 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Automatic Target Recognition The capacity of an algorithm or device to detect targets or other objects based on data acquired from sensors is referred to as automatic target recognition, abbreviated as ATR. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Automatic target recognition Chapter 2: Computer vision Chapter 3: Radar Chapter 4: Synthetic-aperture radar Chapter 5: Beamforming Chapter 6: Pulse-Doppler radar Chapter 7: Inverse synthetic-aperture radar Chapter 8: Radar signal characteristics Chapter 9: Time delay neural network Chapter 10: Track algorithm (II) Answering the public top questions about automatic target recognition. (III) Real world examples for the usage of automatic target recognition in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of automatic target recognition' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of automatic target recognition.

Download or read book Introduction to Radar Target Recognition written by P. Tait and published by IET. This book was released on 2005 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book text provides an overview of the radar target recognition process and covers the key techniques being developed for operational systems. It is based on the fundamental scientific principles of high resolution radar, and explains how the underlying techniques can be used in real systems, taking into account the characteristics of practical radar system designs and component limitations. It also addresses operational aspects, such as how high resolution modes would fit in with other functions such as detection and tracking.

Download or read book The Affect of Image Compression on a Synthetic Aperture Radar Automatic Target Recognition Prescreener and the Relation to SAR Image Statistics written by and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: High resolution SAR imagery compressed using three compression algorithms; Vector Quantization (VQ), JPEG and a Wavelet based MRES algorithm. The restored compressed imagery was processed through a morphology based prescreening Automatic Target Recognition algorithm and the results plotted on ROC curves. Based on these curves MRES and JPEG were found to perform significantly better than VQ. Several image statistics were computed for the restored compressed and uncompressed imagery. A prescreener performance figure of merit (FOM) was computed for each compression ratio for each algorithm. The correlation between each statistic and the FOM was computed. The results show the entropy is the statistic which correlates best with the FOM. Spearman's rank coefficient was used to perform a non parametric analysis on the image statistics. The results confirmed the first results showing that entropy is the best predictor of prescreener performance. This analysis also showed that JPEG and MRES results are fundamentally different from VQ results. This is not unexpected since these two are based on transforms whereas VQ is a purely empirical technique.

Download or read book Target Recognition Using High Resolution Radar written by and published by . This book was released on 1971 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.

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.