Blind adaptive detection of distributed targets in compound-Gaussian clutter

This paper considers the problem of detecting distributed targets in the presence of compound-Gaussian noise with unknown statistics. At the design stage, in order to cope with the a priori uncertainty, we model clutter returns as Gaussian vectors with the same structure of the covariance matrix, but possibly different power levels. Hence, resorting to the method of sieves, we devise a fully blind detector, which ensures the constant false alarm rate (CFAR) property with respect to the disturbance power levels. Moreover the performance analysis confirms the capability of the novel receiver to operate in scenarios of practical interest for radar systems. Finally the comparison with the plain modified generalized likelihood ratio test (MGLRT), devised assuming Gaussian disturbance, and shows that even in the presence of Gaussian clutter, the newly proposed detector achieves satisfactory performance.