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

Hiroshi SARUWATARI  Toshiya KAWAMURA  Tsuyoki NISHIKAWA  Kiyohiro SHIKANO  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E86-A   No.3   pp.634-639
Publication Date: 2003/03/01
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section LETTER (Special Section on Blind Signal Processing: Independent Component Analysis and Signal Separation)
Category: Convolutive Systems
Keyword: 
blind source separation,  microphone array,  independent component analysis,  beamforming,  

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Summary: 
We propose a new algorithm for blind source separation (BSS), in which independent component analysis (ICA) and beamforming are combined to resolve the low-convergence 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.