Knowledge-Aided Adaptive Detection of Radar Target in Gaussian Clutter

This paper presents an adaptive detection method of radar target using the priori knowledge of Gaussian clutter. It is assumed that the clutter covariance matrix is random and obeys the inverse complex Wishart distribution. Based on the priori knowledge, we propose an adaptive detector via utilizing the generalized likelihood ratio test. The proposed adaptive detector does not need training data and detection performance can be achieved due to the use of a prior knowledge about the clutter. Finally, the detection performance of the proposed detector is evaluated and the results illustrate that the proposed detector is superior to the conventional counterparts, particularly for small sample number of the received signal.