Reduced complexity robust, CFAR detectors for large sensor arrays

Partially adaptive array processors, used to detect weak signals in highly cluttered environments, can be designed using a cross-spectral metric performance criteria. The cross-spectral metric provides a systematic way to tackle a wide variety of partially adaptive array processing problems. It yields a robust CFAR detector not critically dependent upon exact knowledge of the interference subspace rank. In a typical adaptive signal detection problem its performance is better than that of a full complexity processor, even when the degrees of freedom are reduced by a factor of four.