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Artech House UK
Space-Time Adaptive Processing for Radar, Second Edition

Space-Time Adaptive Processing for Radar, Second Edition

By (author): Joseph R. Guerci
Copyright: 2014
Pages: 292
ISBN: 9781608078219

eBook £62.00
Space-time adaptive processing (STAP) is an exciting technology for advanced radar systems that allows for significant performance enhancements over conventional approaches. Based on a time-tested course taught in industry, government and academia, this second edition reviews basic STAP concepts and methods, placing emphasis on implementation in real-world systems. It addresses the needs of radar engineers who are seeking to apply effective STAP techniques to their systems, and serves as an excellent reference for non-radar specialists with an interest in the signal processing applications of STAP. Engineers find the analysis tools they need to assess the impact of STAP on a variety of important radar applications. A toolkit of STAP algorithms and implementation techniques allows practitioners the flexibility of adapting the best methods to their application. In addition, this second edition adds brand new coverage on STAP on Transmitù and Knowledge-Aided STAP (KA-STAP).
Introduction; Adaptive Array Processing; Space-Time Adaptive Processing; Other Important Factors Affecting STAP Performance; STAP for Radar: Methods, Algorithms, and Performance; Statistical Basis for STAP; STAP on Transmit; Knowledge-Aided (KA) STAP
  • 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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