LAUSR

In this paper, we consider the problem of adaptive detection for distributed targets embedded in Gaussian disturbance without secondary data. We suppose that some a-priori spectral models for the interference in the cells under test and a lower bound on the power spectral density of the white disturbance term are available. First, we propose an approximate estimation algorithm for the unknown parameters under both hypotheses. Then, we propose a generalized likelihood ratio test that employs the approximate estimates. Finally, we evaluate the performance of the proposed detector under Gaussian disturbance and verify its advantage to some existing techniques.