Rao test of range-distributed targets in homogeneous clutter plus subspace interference

In this paper, we deal with range-distributed targets detection in Gaussian clutter plus subspace interference, we propose an adaptive Rao detector of range-distributed targets. In this paper, firstly, we assume that clutter covariance matrix is known, then substitute clutter covariance matrix for sample covariance matrix. The algorithm possesses the property of constant false alarm rate (CFAR) with respect to the covariance matrix. In this paper, the performance of the detector is assessed by Monte Carlo simulation, and is compared with generalized Likelihood ratio test (GLRT).