New Adaptive Beamforming for Coherent Interference based on Covariance Matrix Reconstruction

Abstract

Conventional beamforming fail to derive the full-rank covariance matrix due to the existent of coherent interference in the spatial domain. Most of the existing methods suppress the correlation interference by sacrificing the degree of freedom (DOF). In this paper, we develop a new adaptive beamforming for coherent interference without the loss of DOF, and the process of this new algorithm is as follows. First, the steering vector of the interference signal is estimated through convex optimization. Then we estimate the interference signal power by decomposing the covariance matrix and reconstruct the interference plus noise covariance matrix (INCM). Finally, the array weights are obtained based on the maximum SNR criterion. The proposed method has no loss of DOF and the array gain is adjacent to the ideal value. The feasibility of the technique is proved by theoretical derivation, and the effectiveness of the method is also verified by numerical results.