DOUBLE-ROBUST ADAPTIVE BEAMFORMING BASED ON COVARIANCE MATRIX RECONSTRUCTION AND NORM-BOUNDED CONSTRAINTS

Adaptive beamforming methods are known to be sensitive to array model mismatch, and the obvious performance degradation can take place especially when the desired signal is present in the received data. Recently, a series of robust adaptive beamforming (RAB) methods based on interference-plus-noise covariance matrix (INCM) reconstruction have been proposed, which utilize the Capon spectrum estimator integrated over a region separated from the direction of the desired signal. However, these methods do not take into account the effects of the reconstruction errors. In this paper, a novel method named double-robust adaptive beamforming based on INCM reconstruction and norm-bounded constraints is proposed to combat arbitrary unknown array mismatches. The essence of the proposed method is considering the inevitable errors not only of the reconstructed INCM but also of the estimated steering vector (SV), and then summing up these errors as norm-bounded error matrices. A closed-form solution of the proposed method is finally provided. Simulation results are provided to show the effectiveness and superiority of the proposed method.