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Modern Radar Detection Theory is a comprehensive reference on the latest developments in adaptive radar detection. It explores the key algorithms used with advanced radar systems, such as airborne early warning, capable of operating in challenging scenarios with a plurality of man-made and natural interference sources. Results on real radar data are extensively discussed.

Topics covered include:

adaptive radar detection in Gaussian interference with unknown spectral properties
invariance theory as an instrument to force the Constant False Alarm Rate (CFAR) property at the design stage
one-stage and two-stage detectors and their performances
operating scenarios where a small number of training data for spectral estimation is available
Bayesian radar detection to account for prior information in the interference covariance matrix
radar detection in the presence of non-Gaussian interference.
Detector design techniques based on a variety of criteria are thoroughly presented and CFAR issues are discussed. Performance analyses representative of practical airborne as well as ground-based and shipborne radars situations are shown.