Time Difference of Arrival Estimation Exploiting Multichannel Spatio-Temporal Prediction

被引:27
作者
He, Hongsen [1 ,2 ,3 ]
Wu, Lifu [1 ,2 ]
Lu, Jing [1 ,2 ]
Qiu, Xiaojun [1 ,2 ]
Chen, Jingdong [4 ]
机构
[1] Nanjing Univ, Key Lab Modern Acoust, Nanjing 210093, Jiangsu, Peoples R China
[2] Nanjing Univ, Inst Acoust, Nanjing 210093, Jiangsu, Peoples R China
[3] SW Univ Sci & Technol, Sch Informat Engn, Mianyang 621010, Peoples R China
[4] Northwestern Polytech Univ, Xian 710072, Peoples R China
来源
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING | 2013年 / 21卷 / 03期
关键词
Microphone arrays; multichannel recursive prediction; multichannel spatio-temporal prediction (MCSTP); pre-whitening; spatial prediction; spatio-temporal prediction; time delay estimation (TDE); EIGENVALUE DECOMPOSITION ALGORITHM; DELAY ESTIMATION; LOCALIZATION; PERFORMANCE; NOISY;
D O I
10.1109/TASL.2012.2223674
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
To localize sound sources in room acoustic environments, time differences of arrival (TDOA) between two or more microphone signals must be determined. This problem is often referred to as time delay estimation (TDE). The multichannel cross-correlation-coefficient (MCCC) algorithm, which is an extension of the traditional cross-correlation method from two- to multiple-channel cases, exploits spatial information among multiple microphones to improve the robustness of TDE. In this paper, we propose a multichannel spatio-temporal prediction (MCSTP) algorithm, which can be viewed as a generalization of the MCCC principle from using only spatial information to using both spatial and temporal information. A recursive version of this new algorithm is then developed, which can achieve similar performance as MCSTP, but is computationally more efficient. Experimental results in reverberant and noisy environments demonstrate the advantages of this new method for TDE.
引用
收藏
页码:463 / 475
页数:13
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