Subspace Selection for Quadratic Detector of Random Signals in Unknown Correlated Clutter

Abstract

The Letter deals with constant false alarm rate (CFAR) detection of random Gaussian target signals embedded in Gaussian clutter with unknown covariance. The proposed detector is analyzed on the assumption that clutter covariance is not known and a random target signal has low-rank property. The low-dimensional subspace-based approach leads to a robust false alarm rate (RFAR) detector. The detection performance loss and the false alarm stability loss to unknown clutter covariance have been evaluated for example scenario.