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
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Joseph R. Guerci
has 35 years of advanced technology development experience in industrial, academic, and government settings, including a seven-year term with the Defense Advanced Research Projects Agency (DARPA). Guerci is a fellow of the IEEE, a recipient of the 2007 IEEE Warren D. White Award and the 2020 IEEE Dennis J. Picard Medal, and the author of several bestselling books.