Fast-Convergence Algorithm for Blind Source Separation Based on Array Signal Processing

Abstract

We propose a now algorithm for blind source separation (BSS), in which independent component analysis (ICA) and bram forming arc combined to resolve the lowconvergence problem through optimization in ICA. The proposed method consists of the following two parts: frequency-domain ICA with direction-of-arrival (DOA) estimation, and null beamforming based on the estimated DOA. The alternation of learning between ICA and beamforming can realize fast- and high-convergence optimization. The results of the signal separation experiments reveal that the signal separation performance of the proposed algorithm is superior to that of the conventional ICA-based BSS method.