Adaptive Beamforming for Uniform Linear Arrays With Unknown Mutual Coupling

This letter proposes a new adaptive beamforming algorithm for uniform linear arrays (ULAs) with unknown mutual coupling. It is based on the fact that the mutual coupling matrix (MCM) of a ULA can be approximated as a banded symmetric Toeplitz matrix as the mutual coupling between two sensor elements is inversely related to their separation, and hence it is negligible when they are separated by a few wavelengths. Taking advantage of this specific structure of the MCM, a new approach to calibrate the signal steering vector is proposed. By incorporating this improved steering vector estimate with a diagonally loaded robust beamformer, a new adaptive beamformer for ULA with unknown mutual coupling is obtained. Simulation results show that the proposed steering vector estimate considerably improves the robustness of the beamformer in the presence of unknown mutual coupling. Moreover, with appropriate diagonal loading, it is found that the proposed beamformer can achieve nearly optimal performance at all signal-to-noise ratio (SNR) levels.