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OverviewThis 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. Full Product DetailsAuthor: Jun Liu , Danilo Orlando , Chengpeng Hao , Weijian LiuPublisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.453kg ISBN: 9781032374277ISBN 10: 1032374276 Pages: 296 Publication Date: 29 November 2024 Audience: General/trade , College/higher education , Professional and scholarly , General , Tertiary & Higher Education Format: Paperback Publisher's Status: Forthcoming Availability: Not yet available  This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release. Table of Contents1. 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 DetectionReviewsAuthor InformationJun 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 Università degli Studi ""Niccolò 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. Tab Content 6Author Website:Countries AvailableAll regions |
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