A robust adaptive beamformer based on desired signal covariance matrix estimation

In order to remove desired signal component from the sample covariance matrix, a novel robust adaptive beamformer is proposed based on desired signal covariance matrix estimation. The desired signal direction is first calculated based on the first-order Taylor series approximation, and then the desired signal's steering vector and power are estimated by using iterative robust minimum variance beamforming, respectively. After above two processing, the desired signal covariance matrix can be estimated. Furthermore, the interference-plus-noise covariance matrix can be reconstructed by subtracting the desired signal covariance matrix from the sample covariance matrix. Finally, simulation results demonstrate that the proposed algorithm is robust against steering vector mismatches resulted from gain and phase perturbation as compared to other beamformers.