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.
