
Adaptive Detection of Multichannel Signals Exploiting Persymmetry
CRC Press
1st Edition
Published on 20. December 2022
Book
Hardback
296 pages
978-1-032-37424-6 (ISBN)
Description
This book offers a systematic presentation of persymmetric adaptive detection, including detector derivations and the definition of key concepts, followed by detailed discussion relating to theoretical underpinnings, design methodology, design considerations, and techniques enabling its practical implementation.
The received data for modern radar systems are usually multichannel, namely, vector-valued, or even matrix-valued. Multichannel signal detection in Gaussian backgrounds is a fundamental problem for radar applications. With an overarching focus on persymmetric adaptive detectors, this book presents the mathematical models and design principles necessary for analyzing the behavior of each kind of persymmetric adaptive detector. Building upon that, it also introduces new design approaches and techniques that will guide engineering students as well as radar engineers toward efficient detector solutions, especially in challenging sample-starved environments where training data are limited.
This book will be of interest to students, scholars, and engineers in the field of signal processing. It will be especially useful for those who have a solid background in statistical signal processing, multivariate statistical analysis, matrix theory, and mathematical analysis.
The received data for modern radar systems are usually multichannel, namely, vector-valued, or even matrix-valued. Multichannel signal detection in Gaussian backgrounds is a fundamental problem for radar applications. With an overarching focus on persymmetric adaptive detectors, this book presents the mathematical models and design principles necessary for analyzing the behavior of each kind of persymmetric adaptive detector. Building upon that, it also introduces new design approaches and techniques that will guide engineering students as well as radar engineers toward efficient detector solutions, especially in challenging sample-starved environments where training data are limited.
This book will be of interest to students, scholars, and engineers in the field of signal processing. It will be especially useful for those who have a solid background in statistical signal processing, multivariate statistical analysis, matrix theory, and mathematical analysis.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
General, Postgraduate, Professional, Professional Practice & Development, Professional Reference, Professional Training, Undergraduate Advanced, and Undergraduate Core
Illustrations
59 s/w Abbildungen, 59 s/w Zeichnungen, 5 s/w Tabellen
5 Tables, black and white; 59 Line drawings, black and white; 59 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Weight
500 gr
ISBN-13
978-1-032-37424-6 (9781032374246)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Jun Liu | Danilo Orlando | Chengpeng Hao
Adaptive Detection of Multichannel Signals Exploiting Persymmetry
Book
11/2024
1st Edition
CRC Press
€70.90
Shipment within 10-20 days

Jun Liu | Danilo Orlando | Chengpeng Hao
Adaptive Detection of Multichannel Signals Exploiting Persymmetry
E-Book
12/2022
1st Edition
CRC Press
€63.49
Available for download

Jun Liu | Danilo Orlando | Chengpeng Hao
Adaptive Detection of Multichannel Signals Exploiting Persymmetry
E-Book
12/2022
1st Edition
CRC Press
€63.49
Available for download
Persons
Jun Liu is an Associate Professor with the Department of Electronic Engineering and Information Science, University of Science and Technology of China. Dr. Liu is a member of the Sensor Array and Multichannel (SAM) Technical Committee, IEEE Signal Processing Society.
Danilo Orlando is an Associate Professor at Universita degli Studi "Niccolo Cusano". His research interests focus on signal processing for radar and sonar systems. He has co-authored more than 150 publications in international journals, conferences, and books.
Chengpeng Hao is a Professor at the Institute of Acoustics, Chinese Academy of Sciences. His research interests are in the fields of statistical signal processing, array signal processing, radar, and sonar engineering. He has authored and co-authored more than 100 scientific publications in international journals and conferences.
Weijian Liu is an Associate Professor with the Wuhan Electronic Information Institute, China. His research interests include multichannel signal detection and statistical and array signal processing.
Danilo Orlando is an Associate Professor at Universita degli Studi "Niccolo Cusano". His research interests focus on signal processing for radar and sonar systems. He has co-authored more than 150 publications in international journals, conferences, and books.
Chengpeng Hao is a Professor at the Institute of Acoustics, Chinese Academy of Sciences. His research interests are in the fields of statistical signal processing, array signal processing, radar, and sonar engineering. He has authored and co-authored more than 100 scientific publications in international journals and conferences.
Weijian Liu is an Associate Professor with the Wuhan Electronic Information Institute, China. His research interests include multichannel signal detection and statistical and array signal processing.
Content
1. Basic Concept 2. Output SINR Analysis 3. Invariance Issues under Persymmetry 4. Persymmetric Adaptive Subspace Detector 5. Persymmetric Detectors with Enhanced Rejection Capabilities 6. Distributed Target Detection in Homogeneous Environments 7. Robust Detection in Homogeneous Environments 8. Adaptive Detection With Unknown Steering Vector 9. Adaptive Detection in Interference 10. Adaptive Detection in Partially Homogeneous Environments 11. Robust Detection in Partially Homogeneous Environments 12. Joint Exploitation of Persymmetry and Symmetric Spectrum 13. Adaptive Detection After Covariance Matrix Classification 14. MIMO Radar Target Detection