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Introduction to Radar Target Recognition

Introduction to Radar Target Recognition
Author: P. Tait
Publisher: IET
Total Pages: 428
Release: 2005
Genre: Technology & Engineering
ISBN: 0863415016

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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.


Deep Learning for Radar and Communications Automatic Target Recognition

Deep Learning for Radar and Communications Automatic Target Recognition
Author: Uttam K. Majumder
Publisher: Artech House
Total Pages: 290
Release: 2020-07-31
Genre: Technology & Engineering
ISBN: 1630816396

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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.


Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR)

Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR)
Author: David Blacknell
Publisher: IET
Total Pages: 292
Release: 2013-08-23
Genre: Technology & Engineering
ISBN: 1849196850

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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.


Introduction to Radar Using Python and MATLAB

Introduction to Radar Using Python and MATLAB
Author: Lee Andrew (Andy) Harrison
Publisher: Artech House
Total Pages: 464
Release: 2019-10-31
Genre: Technology & Engineering
ISBN: 1630815993

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This comprehensive resource provides readers with the tools necessary to perform analysis of various waveforms for use in radar systems. It provides information about how to produce synthetic aperture (SAR) images by giving a tomographic formulation and implementation for SAR imaging. Tracking filter fundamentals, and each parameter associated with the filter and how each affects tracking performance are also presented. Various radar cross section measurement techniques are covered, along with waveform selection analysis through the study of the ambiguity function for each particular waveform from simple linear frequency modulation (LFM) waveforms to more complicated coded waveforms. The text includes the Python tool suite, which allows the reader to analyze and predict radar performance for various scenarios and applications. Also provided are MATLAB® scripts corresponding to the Python tools. The software includes a user-friendly graphical user interface (GUI) that provides visualizations of the concepts being covered. Users have full access to both the Python and MATLAB source code to modify for their application. With examples using the tool suite are given at the end of each chapter, this text gives readers a clear understanding of how important target scattering is in areas of target detection, target tracking, pulse integration, and target discrimination.


Radar Target Detection

Radar Target Detection
Author: Daniel Meyers
Publisher: Elsevier
Total Pages: 513
Release: 2012-12-02
Genre: Technology & Engineering
ISBN: 0323147534

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Radar Target Detection: Handbook of Theory and Practice covers a set of graphical solutions to the detection problem, designated as Meyer Plots, for radar systems design. A radar system's major purpose is the detection and location of an object by means of a return signal, which could be either a reflection or a beacon. This book is composed of four chapters. Chapter 1 presents the basic radar range equation, which is the basic relationship which permits the calculation of echo signal strength from measurable or known parameters of the radar transmitter, antenna, propagation path, and target. Chapter 2 provides examples for determining statistical signal detection using Meyer Plots, particularly for determining detection probability and integration loss and efficiency. Chapter 3 describes the application of target models to determination of detection probability. Chapter 4 examines how Meyer Plots can be used to solve problems involving most any target model.


Deep Neural Network Design for Radar Applications

Deep Neural Network Design for Radar Applications
Author: Sevgi Zubeyde Gurbuz
Publisher: SciTech Publishing
Total Pages: 419
Release: 2020-12-31
Genre: Technology & Engineering
ISBN: 1785618520

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Novel deep learning approaches are achieving state-of-the-art accuracy in the area of radar target recognition, enabling applications beyond the scope of human-level performance. This book provides an introduction to the unique aspects of machine learning for radar signal processing that any scientist or engineer seeking to apply these technologies ought to be aware of.


Target Recognition and Tracking for Millimeter Wave Radar in Intelligent Transportation

Target Recognition and Tracking for Millimeter Wave Radar in Intelligent Transportation
Author: Lin Cao
Publisher: Springer Nature
Total Pages: 248
Release: 2023-06-03
Genre: Technology & Engineering
ISBN: 9819915333

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This book starts with the introduction of the radar working system from a mathematical point of view. It shows the composition of transmitted signal and echo signal, and describes the principle of speed measurement and distance measurement for different radar systems. The book focuses on millimeter-wave radar technologies related to echo signal denoising, target identification, clustering, and target tracking and develops a workable plan for the information fusion idea between millimeter-wave radar and machine vision. This book breaks down the systematic processing flow of millimeter-wave radar echo signals one by one from the standpoint of intelligent transportation, concentrating on the introduction of principles and reinforced by a plethora of experimental instances. So that readers from all relevant professions may comprehend millimeter-wave radar's involvement throughout the complete system process.


Introduction to Radar Systems

Introduction to Radar Systems
Author: Merrill Ivan Skolnik
Publisher: McGraw-Hill Companies
Total Pages: 672
Release: 1962
Genre: Technology & Engineering
ISBN:

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Since the publication of the second edition of "Introduction to Radar Systems," there has been continual development of new radar capabilities and continual improvements to the technology and practice of radar. This growth has necessitated the addition and updating of the following topics for the third edition: digital technology, automatic detection and tracking, doppler technology, airborne radar, and target recognition. The topic coverage is one of the great strengths of the text. In addition to a thorough revision of topics, and deletion of obsolete material, the author has added end-of-chapter problems to enhance the "teachability" of this classic book in the classroom, as well as for self-study for practicing engineers.


Introduction to Radar Systems

Introduction to Radar Systems
Author: Merrill I Skolnik
Publisher: McGraw-Hill Education
Total Pages: 0
Release: 2002-12-20
Genre: Technology & Engineering
ISBN: 9780072881387

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Since the publication of the second edition of "Introduction to Radar Systems," there has been continual development of new radar capabilities and continual improvements to the technology and practice of radar. This growth has necessitated the addition and updating of the following topics for the third edition: digital technology, automatic detection and tracking, doppler technology, airborne radar, and target recognition. The topic coverage is one of the great strengths of the text. In addition to a thorough revision of topics, and deletion of obsolete material, the author has added end-of-chapter problems to enhance the "teachability" of this classic book in the classroom, as well as for self-study for practicing engineers.


Introduction to Radar Systems

Introduction to Radar Systems
Author: Merrill I. Skolnik
Publisher:
Total Pages: 581
Release: 1988
Genre: Radar
ISBN:

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