Research on Robust Beamforming Algorithm Based on Diagonal Loading

A Robust Adaptive Beamforming Algorithm Based on Diagonal Loading is proposed to address non-ideal factors such as small array aperture, steering vector mismatches, and sample covariance matrix errors in small-sized Unmanned Underwater Vehicles (UUV). Initially, a deep neural network is used to estimate the dimension of the signal plus interference subspace. Subsequently, based on the eigenvalues of the sample covariance matrix, the amount of diagonal loading is determined and applied to the sample covariance matrix. Research findings and simulation experiments demonstrate that the proposed algorithm exhibits higher output signal-to-noise ratio(SNR) compared to other algorithms, showcasing robustness against steering vector mismatches and sample covariance matrix errors.