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Particle methods for real-time sound source localization based on the Multiple Signal Classification algorithm
Conference paper

Particle methods for real-time sound source localization based on the Multiple Signal Classification algorithm

Hung-Kuang Hao, Hang-Ming Liang and Yi-Wen Liu
Proceedings of 2014 International Conference on Intelligent Green Building and Smart Grid, IGBSG 2014, 6835269
2014

Abstract

Kalman filtering Multichannel audio processing particle methods sound source localization
Multiple Signal Classification (MUSIC) is a microphone-array signal processing method that achieves high resolution for the estimation of acoustic directions of arrival (DOA)[1]. However, MUSIC in its original form does not estimate the distance from the source to the microphone array. In this work, we propose a method to conduct two-dimensional sound source localization using multiple pairs of microphones. The idea of sampling by particles is combined with MUSIC, and the method has been implemented to run in real-time. To improve the performance against reverberation, the result of localization can be post-processed by Kalman filters or particle filters so the location of the source is continuously tracked. Because the new method allows microphone arrays to process their input in parallel, it is potentially suitable to be deployed to a sensor-network platform. © 2014 IEEE.

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