This book provides a comprehensive and systematic framework for the design of adaptive architectures, which take advantage of the available a priori information to enhance the detection performance. Moreover, this framework also provides guidelines to develop decision schemes capable of estimating the target position within the range bin. To this end, the readers are driven step-by-step towards those aspects that have to be accounted for at the design stage, starting from the exploitation of system and/or environment information up to the use of target energy leakage (energy spillover), which allows inferring on the target position within the range cell under test.In addition to design issues, this book presents an extensive number of illustrative examples based upon both simulated and real-recorded data. Moreover, the performance analysis is enriched by considerations about the trade-off between performances and computational requirements.Finally, this book could be a valuable resource for PhD students, researchers, professors, and, more generally, engineers working on statistical signal processing and its applications to radar systems.

The book describes a new form of radar for which the target response is frequency, i.e., resonance-dependent. The book provides both prototype designs and empirical results collected from a variety of targets. The new form of radar, called RAMAR (Resonance and Aspect Matched Adaptive Radar) advances radar OCo mere ranging and detection OCo to the level of RF spectroscopy, and permits an advance of spectroscopic methods from optical, through infra-red and into the RF spectral range. The book will describe how a target''s response can be a function of frequency components in the transmitted signal''s envelope as well as the signal''s carrier.

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.

Modern radar detection is the new frontier for advanced radar systems capable of operating in challenging scenarios with a plurality of interference sources, both manmade and natural. Written by top researchers and recognized leaders in the field, this is the first book to provide a comprehensive understanding of the current research trends in modern radar detection. It updates readers with the latest radar signal processing algorithms now capable with high-speed computer chips and sophisticated programs. It also includes examples and applications from real systems. This is essential reading for radar systems design engineers within aerospace companies, military radar engineers, and aerospace contractors/consultants.

Principles of Modern Radar: Basic Principles is a comprehensive text for courses in radar systems and technology, a professional training textbook for formal in-house courses and for new hires; a reference for ongoing study following a radar short course and a self-study and professional reference book.

Radar Resource Management (RRM) is vital for optimizing the performance of modern phased array radars, which are the primary sensor for aircraft, ships, and land platforms. Adaptive Radar Resource Management gives an introduction to radar resource management (RRM), presenting a clear overview of different approaches and techniques, making it very suitable for radar practitioners and researchers in industry and universities. Coverage includes: - RRM's role in optimizing the performance of modern phased array radars - The advantages of adaptivity in implementing RRM - The role that modelling and simulation plays in evaluating RRM performance - Description of the simulation tool Adapt_MFR - Detailed descriptions and performance results for specific adaptive RRM techniques - The only book fully dedicated to adaptive RRM - A comprehensive treatment of phased array radars and RRM, including task prioritization, radar scheduling, and adaptive track update rates - Provides detailed knowledge of specific RRM techniques and their performance