Adaptive beamformer based on the augmented complex least mean square algorithm

In this article, an adaptive beamforming system based on the augmented complex least mean square algorithm is analysed. In this approach, the adaptive filter is used as a widely linear system. The second-order statistical information of the signals involved in the array is exploited. Under this consideration, the ability of the adaptive array to minimize the effects of interferences and complex white noise could be enhanced. The equations for the optimal weights and the array factor are derived for the proposed beamforming system. Computer simulations have been performed to evaluate the performance of the adaptive array, and the results were compared with two of the most common standard adaptive beamforming algorithms: the least mean square and recursive least square. The numerical simulations show that the proposed adaptive array has a better performance in time and spatial domain as compared to the classical beamforming systems.