DocumentCode :
157042
Title :
Particle methods for real-time sound source localization based on the Multiple Signal Classification algorithm
Author :
Hung-Kuang Hao ; Hang-Ming Liang ; Yi-Wen Liu
Author_Institution :
Dept. Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan
fYear :
2014
fDate :
23-25 April 2014
Firstpage :
1
Lastpage :
5
Abstract :
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.
Keywords :
Kalman filters; acoustic signal processing; array signal processing; direction-of-arrival estimation; microphone arrays; reverberation; signal classification; DOA; Kalman filters; MUSIC; acoustic directions of arrival; microphone-array signal processing method; multiple signal classification algorithm; particle filters; particle methods; real-time sound source localization; reverberation; sensor-network platform; two-dimensional sound source localization; Arrays; Kalman filters; Microphones; Multiple signal classification; Noise; Vectors; Kalman filtering; Multichannel audio processing; particle methods; sound source localization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Green Building and Smart Grid (IGBSG), 2014 International Conference on
Conference_Location :
Taipei
Type :
conf
DOI :
10.1109/IGBSG.2014.6835269
Filename :
6835269
Link To Document :
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