Addressing the data-association problem for multiple sound source localization using DOA estimates

In this paper, we consider the data association problem that arises when localizing multiple sound sources using direction of arrival (DOA) estimates from multiple microphone arrays. In such a scenario, the association of the DOAs across the arrays that correspond to the same source is unknown and must be found for accurate localization. We present an association algorithm that finds the correct DOA association to the sources based on features extracted for each source that we propose. Our method results in high association and localization accuracy in scenarios with missed detections, reverberation, and noise and outperforms other recently proposed methods.