Adaptive detection of multichannel signals exploiting persymmetry / Jun Liu, Danilo Orlando, Chengpeng Hao, Weijian Liu.

Author/creator Liu, Jun, 1983-
Other author Orlando, Danilo.
Other author Hao, Chengpeng, 1975-
Other author Liu, Weijian, 1982-
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton : CRC Press, Taylor & Francis Group, 2023
Descriptionxviii, 295 pages : illustrations and charts ; 24 cm
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Contents Basic concept -- Output SINR analysis -- Invariance issues under persymmetry -- Persymmetric adaptive subspace detector -- Persymmetric detectors with enhanced rejection capabilities -- Distributed target detection in homogeneous environments -- Robust detection in homogeneous environments -- Adaptive detection with unknown steering vector -- Adaptive detection in interference -- Adaptive detection in partially homogeneous environments -- Robust detection in partially homogeneous environments -- Joint exploitation of persymmetry and symmetric spectrum -- Adaptive detection after covariance matrix classification -- MIMO radar target detection.
Abstract "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 towards efficient detector solutions, especially in challenging sample-starved environments where training data is 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"-- Provided by publisher.
Bibliography noteIncludes bibliographical references.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2022027867
ISBN9781032374246 (hardback)
ISBN9781032374277 (paperback)
ISBN(ebook)

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