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Author: David Blacknell
Publisher: IET
ISBN: 1849196850
Category : Technology & Engineering
Languages : en
Pages : 292
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Book Description
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.
Author: David Blacknell
Publisher: IET
ISBN: 1849196850
Category : Technology & Engineering
Languages : en
Pages : 292
Get Book Here
Book Description
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.
Author: Bruce Jay Schachter
Publisher:
ISBN: 9781510618565
Category : Algorithms
Languages : en
Pages : 0
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Book Description
"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"--
Author: Bruce Jay Schachter
Publisher:
ISBN: 9781510631199
Category : Algorithms
Languages : en
Pages :
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Book Description
"From an engineer designing Automatic Target Recognition (ATR) systems for 40 years, comes this step-by-step guide to producing state-of-the-art ATR systems. The full spectrum of ATR designs are covered, from systems that just suggest targets to the warfighter to ATRs that could serve as the "brains" of lethal autonomous robots. Unfortunately, when it comes to ATR, some practitioners claim that their off-the-shelf canned algorithms magically leap from academic research to deployment with scant domain knowledge or system engineering. Deep learning is marketed more than deep understanding, deep explainability or deep fusion of on-platform resources. Naïve practitioners twist a few algorithmic knobs, and test on data of uncertain virtue, until performance seems superb. Unfortunately, with the enemy and ever changing environment conspiring to defeat detection and recognition, naively designed ATRs can fail in unexpected and spectacular ways. Trustworthy ATRs need to fuse multiple data and metadata sources, continuously learn from and adapt to their environment, interact with humans in natural language, and deal with in-library and out-of-library targets and confusor objects. This book provides a blueprint for smarter, more autonomous, more sophisticated ATR designs"--
Author: Uttam K. Majumder
Publisher: Artech House
ISBN: 1630816396
Category : Technology & Engineering
Languages : en
Pages : 290
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Book Description
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.
Author: Nicholas Wager
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This research investigated signal processing of two dimensional signals for the detection of targets in noise, particularly in complex background pattern noise. The researchers hypothesized that this type of noise was vulnerable to non-linear processing. They investigated whether the human eye/brain acting as a surrogate for a non-linear processor could outperform an optimum linear processor in a quantitative sense. The researchers did this by conducting computer experiments to determine the ability of an operator and an optimum linear filter to determine a known pattern's presence or absence in a noisy image. The performance of both the operator and optimum linear filter are recorded as probability of detection, probability of false alarm pairs, which the researchers use to determine effective signal-to-noise ratio. The performance of man versus machine (optimum linear filter) is compared quantitatively using the effective signal-to-noise ratio. Operator and machine/filter are tested against circular targets in Random White Gaussian noise and in satellite images. The researchers report that the machine filter outperforms the man when the details of both target and background are known in advance, but the man outperforms the machine/filter when the details are known only in a statistical sense.
Author: Nicholas Wager
Publisher:
ISBN:
Category :
Languages : en
Pages : 145
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Book Description
This research investigated signal processing of two dimensional signals for the detection of targets in noise, particularly in complex background pattern noise. The researchers hypothesized that this type of noise was vulnerable to non-linear processing. They investigated whether the human eye/brain acting as a surrogate for a non-linear processor could outperform an optimum linear processor in a quantitative sense. The researchers did this by conducting computer experiments to determine the ability of an operator and an optimum linear filter to determine a known pattern's presence or absence in a noisy image. The performance of both the operator and optimum linear filter are recorded as probability of detection, probability of false alarm pairs, which the researchers use to determine effective signal-to-noise ratio. The performance of man versus machine (optimum linear filter) is compared quantitatively using the effective signal-to-noise ratio. Operator and machine/filter are tested against circular targets in Random White Gaussian noise and in satellite images. The researchers report that the machine filter outperforms the man when the details of both target and background are known in advance, but the man outperforms the machine/filter when the details are known only in a statistical sense.
Author: Firooz Sadjadi
Publisher: Springer Science & Business Media
ISBN: 0387369430
Category : Science
Languages : en
Pages : 269
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Book Description
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.
Author: Firooz A. Sadjadi
Publisher: SPIE-International Society for Optical Engineering
ISBN: 9780819428202
Category : Computers
Languages : en
Pages : 616
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Book Description
This work explores automatic target recognition (ATR). It is divided into sections which look at topics such as: advanced systems for ATR, including airborne video surveillance; multisensor ATR; and adaptive and learning techniques for ATR.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This report describes the development of multiscale, multiresolution methods for automatic target recognition (ATR). The methods are applied to and developed specifically for synthetic aperture radar data. Applications include high level reasoning over learned target models, information theoretic approaches for pose estimation, and model development from multiple views.
Author:
Publisher:
ISBN:
Category : Image processing
Languages : en
Pages : 438
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Book Description
