Robust CFAR detection of random signals in compound-Gaussian clutter plus thermal noise

An algorithm for detecting a random target signal against a mixture of corr elated compound-Gaussian clutter and white Gaussian thermal noise is propos ed. The new detection strategy is obtained by extending the generalised mat ched subspace detector previously derived by Gini and Farina (1999) for onl y compound-Gaussian clutter. Two different versions of the detection strate gy are proposed and compared: the first relies on the estimation of the rad ar clutter texture component; the second trades-off performance with comput ational complexity by using the texture mean value in place of its estimate . The texture estimator mean square error is derived in closed form and ana lysed. Additionally, the robustness of the detector false alarm rate to cha nges of clutter parameters and the detection performance are numerically in vestigated by Monte Carlo simulation.