Generalized State Coherence Transform for Multidimensional TDOA Estimation of Multiple Sources

被引:51
作者
Nesta, Francesco [1 ]
Omologo, Maurizio [1 ]
机构
[1] Fdn Bruno Kessler IRST, I-38123 Povo, TN, Italy
来源
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING | 2012年 / 20卷 / 01期
关键词
Blind source separation (BSS); independent component analysis (ICA); multi-source localization; multidimensional localization; permutation problem; underdetermined source separation; LOCALIZATION; ICA;
D O I
10.1109/TASL.2011.2160168
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
According to the physical meaning of the frequency-domain blind source separation (FD-BSS), each mixing matrix estimated by independent component analysis (ICA) contains information on the physical acoustic propagation related to each source and then can be used for localization purposes. In this paper, we analyze the Generalized State Coherence Transform (GSCT) which is a non-linear transform of the space represented by the whole demixing matrices. The transform enables an accurate estimation of the propagation time-delay of multiple sources in multiple dimensions. Furthermore, it is shown that with appropriate nonlinearities and a statistical model for the reverberation, GSCT can be considered an approximated kernel density estimator of the acoustic propagation time-delay. Experimental results confirm the good properties of the transform and its effectiveness in addressing multiple source TDOA detection (e.g., 2-D TDOA estimation of several sources with only three microphones).
引用
收藏
页码:246 / 260
页数:15
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