Robust Widely Linear Beamforming via Noncircularity Coefficient Integration and Extended Covariance Matrix Reconstruction
Huichao Yang, Linjie Dong · IEEE Sensors Journal · 2023
This article addresses the robustness of the widely linear (WL) beamformer and introduces a novel robust WL beamforming method that utilizes an extended covariance matrix reconstruction. The interference-plus-noise covariance matrix (INCM) is reconstructed within segmented regions using an integration operation based on the nominal steering vector (SV) and Capon power. This process leads to the reconstruction of the pseudo-interference covariance matrix (PICM) through the utilization of the noncircularity coefficient (NC), which is computed via nominal parameters. To estimate the SV, eigenvalue decomposition is applied, taking into account the redundancy of the integration operation. Besides, the SV of the desired signal (DS) is also acquired using a similar process involving the principal eigenvector. Consequently, the weight vector of the WL beamformer is derived. Simulation results are provided to demonstrate the robustness and effectiveness of the proposed method under conditions of certain mismatch errors.