Adaptive Diagonal Loading of MVDR Beamformer For Sustainable Performance In Noisy Conditions

The performance of Minimum Variance Distortionless Response (MVDR) beamformer can be improved by enhancing its ability to suppress interference and noise effectively. Generally, the number of microphones should be large in order to get greater interference suppression. However, this decreases the stability of a beamformer. To improve stability a diagonal loading factor is added in the noise covariance matrix. An increase in loading factor causes poor suppression and larger deviations in the values of the loading factor mislead the steering vector in another direction. As the exact noise covariance matrix is unknown, it is estimated from the interference and noise. In this paper, the issue of estimation error is addressed. The amount of diagonal loading is estimated adaptively by considering actual snapshots of the input signal. An additional constraint on the diagonal loading is proposed, which improves the robustness and stability of the MVDR beamformer. A tradeoff between the stability and diagonal loading factor is investigated. The effect of adaptive diagonal loading on output SINR and stability is analyzed.