A Recursive Method Implementation for Robust Adaptive Beamforming in the Presence of Mismatches

When adaptive arrays are applied to practical problems, the performance degradation of adaptive beamforming algorithms may become even more pronounced than in the ideal case because some of underlying assumptions on the environment, sources, or sensor array can be violated and this may cause a mismatch between the look direction of the beamformer and the actual direction of arrival(DOA) of the signal. In the practical environment, complete knowledge of signal characteristics is not available and the environment is time varying. In these cases, the recursive algorithm to robust adaptive beamforming is required. In this paper, we propose robust adaptive beamforming algorithm based on explicit modeling of uncertainties in source DOA and a Bayesian approach. The proposed algorithm has nearly optimal performance under good conditions, is robust to uncertainty in DOA under poor conditions and makes the mean output array SINR consistently close to the optimal one. Computer simulation results demonstrate better performance of our proposed algorithm than that of other algorithms.