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Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach, Second Edition

Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach, Second Edition

By (author): Joseph R. Guerci
Copyright: 2020
Pages: 200
ISBN: 9781630817732

Hardback $139.00 Qty:

This highly-anticipated second edition of the bestselling Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach, the first book on the subject, provides up-to-the-minute advances in the field of cognitive radar (CR). Adaptive waveform methods are discussed in detail, along with optimum resource allocation and radar scheduling. Chronicling the 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. It 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.

Introduction; Optimum Multi-Input Multioutput (MIMO) Radar; Adaptive Multi-Input Multioutput (MIMO) Radar; Introduction to Knowledge-Aided (KA) Adaptive Radar; Putting It All Together; Optimum Radar Resource Allocation and Scheduling; Areas for Future Research.
  • Joseph R. Guerci J.R. Guerci has 30 years of experience in advanced technology research and development in government, industrial, and academic settings including the US Defense Advanced Research Projects Agency (DARPA) as Director of the Special Projects Office (SPO) where he led the inception, research, development, execution, and ultimately transition of next generation multidisciplinary defense technologies. In 2007, he received the IEEE Warren D. White Award for radar adaptive processing and is a Fellow of the IEEE for contributions to advanced radar theory and embodiment in real-world systems.
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