A novel jammer suppression method based on KASPICE-STAP

Abstract

Echo data received by airborne radar may contain target, clutter, noise and jammer. Conventional space-time adaptive processing} (STAP) methods show poor performance in conformal arrays and heterogeneous environments especially with jammer in echo data. In this paper, a novel jammer suppression method based on knowledge aided semi parametric/sparse iterative covariance-based estimation STAP (KASPICE-STAP) is propose to improve the jammer suppression performance with conformal arrays. The proposed method estimates angles and power of the jammers to reconstruct the jammer covariance matrix. For each iteration, we also estimate the clutter covariance matrix. Then, with the excellent performance of the proposed method, we can obtain an accurate interference covariance matrix of the cell under test. Simulation results and theoretical analysis verify the effectiveness of the proposed method.