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.

Constant false alarm rate detection processes are important in radar signal processing. Such detection strategies are used as an alternative to optimal Neyman-Pearson based decision rules, since they can be implemented as a sliding window process running on a radar range-Doppler map. This book examines the development of such detectors in a modern framework. With a particular focus on high resolution X-band maritime surveillance radar, recent approaches are outlined and examined. Performance is assessed when the detectors are run in real X-band radar clutter. The book introduces relevant mathematical tools to allow the reader to understand the development, and follow its implementation.

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.

This book presents a comprehensive tutorial exposition of radar detection using the methods and techniques of mathematical statistics. The material presented is as current and useful to today's engineers as when the book was first published by Prentice-Hall in 1968 and then republished by Artech House in 1980. The book is divided into six parts. Part I is introductory and describes the nature of the radar detection problem. Part II reviews the mathematical tools necessary for a study of detection theory. Part III contains tutorial expositions in a radar context of the classical signal-to-noise and a posteriori theories, both of which have played important roles in the evolution of modern radar. The unifying theme of the book is provided by statistical decision theory, introduced in the last chapter of Part III, which provides the framework for the chapters that follow. The first three chapters of Part IV contain a unified tutorial exposition of single and multiple hit detection theory. The last two chapters are respectively devoted to the use of the radar equation and a discussion of cumulative detection probability. The latter includes a procedure for minimizing the power-aperture product of a search radar. The performance of near-optimum multiple hit detection strategies are considered in Part V. These include binary and pulse train detection strategies. The first chapter in Part VI applies sequential detection theory to the radar detection problem. It includes the Marcus and Swerling test strategy and a two-step approximation to sequential detection. The second chapter contains the development of Bayes decision rules and Bayes receivers for optimizing the detection of multiple targets with unknown parameters, such as range, velocity, angle, etc.

Collects the revised and updated versions of lectures presented at an advanced course on [title] held at the Accademia dei Lincei, Rome, 1988, as well as some additional chapters. The 13 chapters address basic concepts on detection, estimation, and optimum filtering; models of clutter; CFAR techniques in clutter; pulse compression and equivalent technologies; pulse doppler radar; MTI, MTD, and adaptive clutter cancellation; rejection of active interference; architecture and implementation of radar signal processors; identification of radar targets; phased arrays; bistatic radars; space-based radar; and evolution and future trends of radar. Primarily for radar engineers and researchers, as well as advanced students. Distributed by INSPEC. Annotation copyright by Book News, Inc., Portland, OR

What is radar? What systems are currently in use? How do they work? Understanding Radar Systems provides engineers and scientists with answers to these critical questions, focusing on actual radar systems in use today. It's the perfect resource for those just entering the field or a quick refresher for experienced practitioners. The book leads readers through the specialized language and calculations that comprise the complex world of modern radar engineering as seen in dozens of state-of-the-art radar systems. The authors stress practical concepts that apply to all radar, keeping math to a minimum. Most of the book is based on real radar systems rather than theoretical studies. The result is a valuable, easy-to-use guide that makes the difficult parts of the field easier and helps readers do performance calculations quickly and easily.

Increasing the noise immunity of complex signal processing systems is the main problem in various areas of signal processing. At the present time there are many books and periodical articles devoted to signal detection, but many important problems remain to be solved. New approaches to complex problems allow us not only to summarize investigations, but also to improve the quality of signal detection in noise. This book is devoted to fundamental problems in the generalized approach to signal processing in noise based on a seemingly abstract idea: the introduction of an additional noise source that does not carry any information about the signal in order to improve the qualitative performance of complex signal processing systems. Theoretical and experimental studies carried out by the author lead to the conclusion that the proposed generalized approach to signal processing in noise allows us to formulate a decision-making rule based on the determi nation of the jointly sufficient statistics of the mean and variance of the likelihood function (or functional). Classical and modern signal detection theories allow us to define only the sufficient statistic of the mean of the likelihood function (or functional). The presence of additional information about the statistical characteristics of the like lihood function (or functional) leads to better-quality signal detection in comparison with the optimal signal detection algorithms of classical and modern theories.