A Novel Robust Adaptive Beamforming Algorithm Based on Steering Vector Estimation and Covariance Matrix Reconstruction

In low-orbit satellite communications, the use of adaptive beamforming technology can greatly improve the anti-interference performance of the receiver. Considering that adaptive beamforming is highly sensitive to any form of error, a robust adaptive beamforming technique, predicated on the reconstruction of the interference-plus-noise covariance matrix (INCM) and the estimation of the steering vector (SV), is proposed in this study. The method initially constructs SV error neighborhood tables for the desired and interference signals based on the results of the direction of arrival estimation. The SV that maximizes the multiple signal classification spectrum is then found in the tables as an estimate of the SVs of the desired and interfering signals. Subsequently, the interference covariance matrix is reconstructed based on the estimated interference SVs. Finally, the noise components are separated by projection, thus reconstructing the noise covariance matrix (NCM) and INCM. The proposed method reconstructs a more precise NCM compared with other methods, resulting in enhanced performance. Analysis of simulation results demonstrated that the proposed technique is effective and robust.