A Bayesian approach to robust constrained CMA

When adaptive arrays are applied to practical problems, adaptive beamformers can suffer significant performance degradation in the presence of the mismatch between the actual direction of arrival (DOA) of the signal and the look direction of the beamformers. In this paper, a novel robust constrained constant modulus algorithm (CMA) is proposed by using a Bayesian approach, which is robust to uncertainty in source DOA. The proposed algorithm has nearly optimal performance under good conditions, provides an improved robustness to uncertainty in DOA under poor conditions and improves the mean output array SINR. Computer simulations compare the performance of our algorithm with conventional constrained CMA.