Novel Robust Adaptive Beamforming
Chia-Cheng Huang, Ju-Hong Lee · 2012
Diagonal loading (DL) is one of the widely used techniques against the errors due to steering vector mismatch and finite sample effect. Recently, a variable loading (VL) has shown its advantages over the DL due to using different loading for each eigenvalue of the correlation matrix of the received array data rather than a fixed loading for all of the eigenvalues as the DL. In this paper, a novel robust beamforming method is presented. As compared to the DL and the VL, the weight vector of the proposed method is with a more general form of diagonal loaded correlation matrix. Simulation results show that the proposed method is more robust than the DL and the VL against the errors as mentioned above.