Disambiguation in multidimensional tracking of multiple acoustic sources using a Gaussian likelihood criterion
Pengxiao Teng, Anthony Lombard, Walter Kellermann · 2010
The TDOA-based acoustic source localization approaches suffer from a pairing problem in the case of multiple dimensions and multiple sources. To resolve this problem, usually three or more microphone pairs are required. In this paper, we propose a new solution based on a Gaussian likelihood function to pair TDOAs, which allows us to localize multiple moving acoustic sources in several dimensions using a minimum number of microphone pairs. Moreover, the proposed method is combined with a particle filter for tracking multiple moving sources. Experimental results demonstrate the effectiveness of the proposed scheme.