Robust Beamforming Based on Covariance Matrix Reconstruction and ADMM

Considering at the issue that the performance of the traditional beamforming algorithm will decrease sharply when the disturbance occurs at the disturbed position and the steering vector mismatch occurs, a new robust beamforming method based on covariance matrix reconstruction and Alternating Direction Method of Multipliers (ADMM) is proposed. Firstly, based on the maximum output power criterion of beamformers, an optimization model is designed to solve the optimal steering vector. Then, the covariance matrix is reconstructed by using the defined interference range to widen the nullity and enhance the anti-motion interference ability of the system. Then, for the quadratic inequality constraint problem of the steering vector, this paper uses ADMM to solve the model iteratively, and obtains the specific solution of the steering vector in each iteration. In addition, the complexity of the algorithm is also analyzed. The experimental results show that, compared with the existing beamforming algorithms, the proposed method Widen the width of zero notch in the interference area, improves the anti-interference performance of the beam, and can well correct the mismatched steering vector.