Minimum redundancy space-time adaptive processing utilizing reconstructed covariance matrix

The maximum space-time degrees of freedom (DOF) is restricted to the number of antennas and pulses. In this paper, a novel sparse space time adaptive processing (STAP) scheme is proposed based on the concept of minimum redundancy arrays.We arrange the array geometry and the temporal sampler interval to make the location of joint space-time samples satisfies minimum redundancy interval. According to the structural information imposed on clutter covariance matrix (CCM), the original CCM is estimated by a series of matrix basis accurately, and a higher dimension of CCM can be reconstructed while the virtual spatial and temporal elements are adjustable. Simulation results verify the proposed formulations and the angle-Doppler resolution is increased significantly.