Robust Adaptive Beamforming Method Based on Steering Vector Correction and Diagonal Loading

The beamforming algorithm is a classic method in array signal processing. When the steering vector and the covariance matrix of noise (including interference) are precisely estimated, the Capon beamforming algorithm ensures minimal distortion of the expected signal while maximizing interference suppression. However, in practical engineering scenarios, the output signal-to-interference-plus-noise ratio (SINR) of the Capon beamforming algorithm significantly decreases when there are mismatches in the steering vector and the covariance matrix contains the expected signal. To enhance its robustness, robust beamforming methods and some of their improved algorithms have been widely adopted. Building upon this foundation, this paper proposes a two-stage robust beamforming algorithm. Simulation results demonstrate that compared to other classical algorithms, this algorithm achieves a higher output signal-to-interference-plus-noise ratio, and is insensitive to steering vector mismatches, and performs well under scenarios with limited snapshots, exhibiting superior robustness.