Robust adaptive beamforming algorithm under directional uncertainty

When applying adaptive arrays to actualities, the performance of existing adaptive array algorithms is known to degrade substantially because of the slight mismatch between actual and presumed array responses to the desired signal. In this paper, a novel robust adaptive beamforming algorithm under directional uncertainty is therefore proposed using a Bayesian approach to respond to the current environment by learning or estimating the direction of arrival (DOA) of the actual signal from observations. The proposed algorithm can provide excellent robustness to the uncertainty of DOA of actual signal and make the mean output array SINR consistently close to the optimal one. Simulation results reveal that the proposed algorithm is superior in performance to conventional adaptive beamforming algorithms.