MULTIPLE SOUND SOURCE LOCALIZATION BASED ON TDOA CLUSTERING AND MULTI-PATH MATCHING PURSUIT

Multiple sound source localization in wireless acoustic sensor networks (WASNs) is a challenging problem. Although compressive sensing based methods have shown effectiveness in uncorrelated sources localization, their performance degrades significantly when they are used to locate multiple speech sources. To this end, we propose a multiple sound source localization method based on the time difference of arrival (TDOA) clustering and the multi-path matching pursuit algorithm. First, TDOAs are calculated locally in time-frequency (TF) bins of sensor recordings. Then, the TDOAs are clustered after utilizing outlier rejection to remove erroneous estimations. Finally, a multi-path matching pursuit algorithm is proposed to solve a sparse localization model for localizing multiple sound sources. Experimental results show that the proposed method yields good performance for multiple sound source localization, especially in strong noisy scenarios.