Three dimensional acoustic source localization and tracking using statistically weighted hybrid particle filtering algorithm

Authors:
T. Li;W. Ser
Affiliations:
Center for Signal Processing, School of Electrical and Electronics Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore;Center for Signal Processing, School of Electrical and Electronics Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
Venue:
Signal Processing
Year:
2010

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Abstract

The source height estimation (SHE) based hybrid particle filtering (PF) algorithm was originally presented by the authors in EUSIPCO 2008. The accuracy of the source height estimation was proposed to be used as a direct judgement of whether the current acoustic sensor array's observation is originated from the true source state or from the reverberation. According to the judgement, the hybrid PF algorithm adaptively allocates the particles using either the bootstrap (BS) algorithm or the sequential importance sampling (SIS) algorithm to effectively tackle the reverberation effects. In this paper, a comprehensive analysis is conducted on the work reported in that conference paper and additional novelties are included too. The newly designed quad-stage statistical (QSS) source height estimation algorithm (QSS-SHE) creates more hypotheses in the effective evaluation of the accuracy of the height estimation. Based on the QSS evaluations, the more precisely defined statistical weights (SW) based hybrid structure is introduced. At every time instance, particles sampled using both the BS and the SIS algorithms are mixed and updated according to their associated SW. The resulted hybrid particle filtering (SW-PF) algorithm demonstrates more robust tracking performance as compared to the hybrid PF algorithm originally proposed in the conference paper.