Robust adaptive beamforming in the presence of strong desired signal and DOA mismatch

The performances of most previous beamformers degrade dramatically when the desired signal (DS) of high signal-to-noise ratio (SNR) is present in the training data with direction-of-arrival (DOA) mismatch. In this paper, two new robust adaptive beamformers are presented to achieve robustness over a large range of SNR. The basic ideas of the presented beamformers are based on the interference-plus-noise covariance matrix reconstruction and two different steering vector estimation methods. Compared with the previous steering vector estimation method, they have good performance while have less computational complexity and don't need any specific optimization software. Simulation results demonstrate that the performances of the proposed beamformers are close to the optimal values over a large range of SNR.