Robust adaptive beamforming algorithm based on diagonal loading

LMS algorithm is simple and effective as adaptive beamforming algorithms, but its performance is known to degrade substantially in the presence of even slight mismatches between the actual and presumed array responses to the desired signal. In order to overcome the shortage, a novel approach to robust adaptive beamforming based on diagonal loading was proposed. The diagonal loading factor and convergence performance were analyzed and the convergence scope of robust constrained LMS (RCLMS) algorithm was also given. The proposed RCLMS algorithm based on diagonal loading offers faster convergence rate, provides excellent robustness against the signal steering vector mismatches and makes the mean output array SINR consistently close to the optimal one. Computer simulation results support the analysis and compare the performance of the proposed algorithm with the traditional constrained-LMS algorithm.