Adaptive Radar Resource Management

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

Discover the technology for the next generation of radar systems Here is the first book that brings together the key concepts essential for the application of Knowledge Based Systems (KBS) to radar detection, tracking, classification, and scheduling. The book highlights the latest advances in both KBS and radar signal and data processing, presenting a range of perspectives and innovative results that have set the stage for the next generation of adaptive radar systems. The book begins with a chapter introducing the concept of Knowledge Based (KB) radar. The remaining nine chapters focus on current developments and recent applications of KB concepts to specific radar functions. Among the key topics explored are: Fundamentals of relevant KB techniques KB solutions as they apply to the general radar problem KBS applications for the constant false-alarm rate processor KB control for space-time adaptive processing KB techniques applied to existing radar systems Integrated end-to-end radar signals Data processing with overarching KB control All chapters are self-contained, enabling readers to focus on those topics of greatest interest. Each one begins with introductory remarks, moves on to detailed discussions and analysis, and ends with a list of references. Throughout the presentation, the authors offer examples of how KBS works and how it can dramatically improve radar performance and capability. Moreover, the authors forecast the impact of KB technology on future systems, including important civilian, military, and homeland defense applications. With chapters contributed by leading international researchers and pioneers in the field, this text is recommended for both students and professionals in radar and sonar detection, tracking, and classification and radar resource management.

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.

Chronicling the new field of cognitive radar (CR), this cutting-edge resource provides an accessible introduction to the theory and applications of CR, and presents a comprehensive overview of the latest developments in this emerging area. The first book on the subject, Cognitive Radar covers important breakthroughs in advanced radar systems, and offers new and powerful methods for combating difficult clutter environments. You find details on specific algorithmic and real-time high-performance embedded computing (HPEC) architectures. This practical book is supported with numerous examples that clarify key topics, and includes more than 370 equations.

A valuable resource for radar engineers and managers of all levels, this revised edition provides an introduction to the capabilities and limitations of radar, as well as a detailed advanced study of key radar signal processing topics. The book explains the concepts and theory of radar signal processing such as resolution, ambiguities, antennas, waveforms, the theory of detecting targets in noise and/or clutter, and tracking using data processing. It also presents equations for the determination of maximum radar range in free space and as affected by multipath and the horizon.

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 constitutes revised selected papers from the 24th Argentine Congress on Computer Science, CACIC 2018, held in Tandil, Argentina, in October 2018. The 26 papers presented in this volume were carefully reviewed and selected from a total of 155 submissions. They were organized in topical sections named: Agents and Systems; Distributed and Parallel Processing; Technology Applied to Education; Graphic Computation, Images and Visualization; Software Engineering; Databases and Data Mining; Hardware Architectures, Networks, and Operating Systems; Innovation in Software Systems; Signal Processing and Real-Time Systems; Computer Security; Innovation in Computer Science Education; and Digital Governance and Smart Cities.