Knowledge-aided Bayesian detection with MIMO radar in compound-Gaussian clutter

In this paper, we consider the adaptive detection with multiple-input multiple-output (MIMO) radar in the presence of compound-Gaussian clutter. A Bayesian framework is exploited where the covariance matrices of the primary and the secondary data are assumed to be random, with an inverse complex Wishart distribution. In this framework, the generalized likelihood ratio test (GLRT) is derived. Finally, we evaluate the capabilities of the proposed detector against compound-Gaussian clutter as well as their superiority with respect to some existing techniques.