A Robust Adaptive Beamforming with Diagonal Loading and Steering Vector Estimation

Abstract

A number of robust adaptive beamforming methods have been developed in recent years. These methods suffer from performance problems, some in low SNRs and others in high SNR especially when the desired signal is present in the sample training data. Among these approaches, the diagonal loading have proved the robustness in low SNR even for small size sample training data. The main drawback of this approach is uncertain means of choosing a diagonal loading factor. We present an improved diagonal loading approach and suggest the convenient way of selecting the diagonal factor. The simulations results demonstrate that the new approach is robust as it outperforms the previous Diagonal Loading and many other methods.