Null Broadening Robust Beamforming Based on Decomposition and Iterative Second-order Cone Programming

Abstract

To solve the problem that the performance of adaptive beamformer degrades severely in the presence of steering vector mismatch or non-stationary interference, a null broadening robust beamforming based on decomposition and iterative second-order cone programming (SOCP) is proposed. The width and depth of the nulls is controlled. The magnitude response constraints are applied to control the beamwidth and ripple of mainlobe, so the SV mismatch can be overcame. Due to the decomposition of the non-convex magnitude response constraints, the proposed approach can be solved by decomposition and iterative SOCP. Simulation results show that the proposed approach can effectively broaden the null width and enhance the null depth, and it is also robust against SV mismatch, especially large SV mismatch. The proposed approach is jointly robust against the SV mismatch and non-stationary interference, and is still effective in the case of low snapshot, which enhances the robustness of adaptive beamformer in complex environments.

Keywords

• robust adaptive beamforming
• null broadening
• magnitude response constraints
• second-order cone programming
• joint robustness