A GLRT detector in partially correlated texture based compound-Gaussian clutter

Abstract

This paper addresses the problem of target detection in the presence of a non-Gaussian clutter modeled in compound-Gaussian form which realizes the clutter process as a product of two independent random processes ‘texture’ and ‘speckle’. The likelihood ratio test (LRT) detector applied to this detection problem reduces the detector to a matched filter (MF) when the texture is considered as completely correlated during a coherent processing interval (CPI). However, in practical applications, the textural component exhibits a correlation which is less than unity. The conventional form of MF based detectors existing in the literature yield a significant fall in the detection performance in such clutter scenarios. In this paper, we propose a generalized likelihood ratio test (GLRT) detector which can effectively detect a fluctuating target in the presence of a compound-Gaussian clutter with partially correlated texture. The results are presented to show the performance superiority of the proposed detector over the existing MF detector in such varying texture scenarios.