Robust Adaptive Array Beamforming Based On Independent Component Analysis With Regularized Constraints

摘要

This paper deals with adaptive array beamforming based on stochastic gradient descent independent component analysis (ICA) for suppressing interference with robust capabilities. The approach first uses estimates of the interested source directions to construct the multiple regularized constraints, which form an efficient ICA-based beamformer to achieve fast convergence and more robust capabilities than existing MCMV and ESB beamformers. In conjunction with the regularization parameters of the high-order derivative constraints, the width of the main beam for remaining the desired signal and the depth of nulls for suppressing inter-ferers can be adjusted. Several computer simulation examples are provided for illustration and comparison.