AN ADAPTIVE SUBSPACE DETECTOR FOR TARGET IN TARGET-INDUCED CLUTTER PLUS GAUSSIAN NOISE BACKGROUND

In this paper, we consider the problem of detecting target in target-induced clutter ( TIC) plus Gaussian noise background. Processing this detection problem, the traditional generalized likelihood ratio detector (GLRD) deals with the clutter as a part of the noise. An adaptive subspace detector for TIC (TIC-ASD) background is proposed. Different from the traditional GLRD, the TIC-ASD deals with the clutter and the noise separately. The signal and the clutter covariance matrix are estimated with the aid of generalized likelihood ratio (GLR) principle. The test statistic is constructed by replacing the signal and the clutter covariance matrix with their maximum likelihood estimations (MLEs). Experimental simulations are provided to demonstrate the detection performance of the TIC-ASD and the GLRD. Simulation results show that the TIC-ASD outperforms the GLRD in both single antenna and multi antenna scenarios.