Guerci J.R. Space-Time Adaptive Processing for Radar

2nd edition. — New York: Artech House, 2015. — 283 p.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.
The burgeoning popularity of space-time adaptive processing (STAP) is easily demonstrated with a quick keyword search. Although originally coined for airborne multichannel moving target indicator (MTI) radar, the acronym has been adopted in many disciplines in which joint adaptive sensor temporal and spatial processing are performed (e.g., multidimensional adaptive filtering). Although a widely published topic, there is a void in coverage at the introductory to intermediate level—a niche which this book is designed to address.
Multichannel space-time array processing is an extremely rich topic area in and of itself. When coupled with the modern marvel of a radar system, it is doubtful that any single source could come close to providing comprehensive coverage.Preface
Preface to the Second Edition References

Introduction
The Need for STAP in MTI Radar.
STAP for MTI Radar.
New to the Second Edition.
Book Organization References.Adaptive Array ProcessingOptimum Spatial (Angle) Beamforming.
Optimum Temporal (Doppler/Pulse) Processing.
Adaptive 1-D Processing.
Adaptivity in Nonstationary Environments.
ULA Antenna Pattern Response.
Derivation of the Maximum Likelihood Sample Covariance Matrix.Space-Time Adaptive ProcessingNeed for Joint Space and Time Processing.
Optimum Space-Time Processing for MTI Radar.
STAP.
Summary Problems References.Other Important Factors Affecting STAP PerformanceChannel Mismatch.
Other Interference Subspace Leakage Effects.
Antenna Array Misalignment.
Nonlinear Arravs.
Interference Nonstationarity and the Iceberg.STAP for Radar: Methods, Algorithms, and PerformanceData-Independent Reduced-Rank STAP.
Data-Dependent Reduced-Rank STAP.
Structured-Covariance and Model-Based Methods.
Illustrative Design Examples.Other TopicsStatistical Basis for STAP.
STAP Implementation.STAP on TransmitOptimum MIMO Waveform Design for the Additive Colored Noise Case.
Optimum MIMO Design for Maximizing Signal-to-Clutter.
Optimum MIMO Design for Target Identification.
Constrained Optimum MIMO Radar.
Adaptive Multi-Input Multi-Output (MIMO) Radar.Knowledge-Aided (KA) STAP
The Need for KA STAP.
Introduction to KA Radar: Back to “Bayes-ics”.
Real-Time KA-STAP: The DARPA/AFRL KASSPER Project.
KA STAP Epilogue.About the Author
Index