Robust adaptive beamforming algorithm based on a bayesian approach

When applying adaptive arrays to actualities, the performance of existing adaptive array algorithms degenerates substantially because of the slight mismatch between actual and presumed array responses to expected signal. With the recursive process given, a novel robust adaptive beamforming algorithm is therefore proposed using Bayesian approach to respond to the current environment by learning or estimating the direction of arrival (DOA) of the actual signal from observations. The computational complexity of the proposed algorithm can thus be efficiently reduced in comparison with other algorithms since the recursive method is used to obtain inverse matrix, and it can provide excellent robustness for 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 algorithm proposed is superior in performance to conventional ones.