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Estimation of the complex‐valued mixing matrix by single‐source‐points detection with less sensors than sources
Author(s) -
Li Hui,
Shen Yuehong,
Wang Jiangong,
Ren Xishun
Publication year - 2012
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.1517
Subject(s) - underdetermined system , mixing (physics) , matrix (chemical analysis) , cluster analysis , algorithm , blind signal separation , computer science , signal (programming language) , set (abstract data type) , field (mathematics) , pattern recognition (psychology) , mathematics , artificial intelligence , telecommunications , pure mathematics , composite material , programming language , channel (broadcasting) , physics , materials science , quantum mechanics
This paper essentially considers the direction‐of‐arrival (DOA) estimation of far‐field source signals in the underdetermined blind separation, where the mixing matrix is complex‐valued. By distinguishing single‐source‐points (SSPs) from multi‐source‐points in the time‐frequency domain, a novel estimation algorithm is proposed based on the detection of SSPs, where only single source contributes and samples all correspond to one of the mixing column vectors. To further enhance the estimation accuracy, a modified version of the proposed algorithm is also presented, which utilizes the probability density distribution of the already detected SSPs and reselects those reliable SSPs with most likely probabilities. Finally, the mixing matrix as well as the DOAs can be obtained by performing the K‐means clustering algorithm on samples at selected SSPs. The results of numerical simulations validate the efficiency of both the two estimation algorithms. One of the outstanding superiorities for the SSPs‐based idea is that it can distinguish multiple DOAs using only two sensors; the other is that it relaxes the signal sparsity requirement to allow SSPs to merely occur at a small number of time‐frequency locations. Copyright © 2011 John Wiley & Sons, Ltd.