Robust subspace technique for joint angle/doppler estimation in non-Gaussian clutter

We consider the problem of joint angle and doppler estimation for Space-Time Adaptive Processing (STAP) airborne radar in non-gaussian clutter which is modeled as a complex symmetric alpha stable SαS process. We introduce a sign covariance estimate which has almost robust performance in heavy tailed noise [1]. The subspace estimate is calculated via the propagator method [2] to reduce the computational load in the way that it does not require the eigendecomposition. Performance of the proposed technique is assessed through simulations and it is shown that the method reveals better performance than FLOM-MUSIC [3] and ROC-MUSIC[4].