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Bayesian Inference for Acoustic Direction of Arrival Analysis Using Spherical Harmonics

Graduate Program in Architectural Acoustics, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
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Entropy 2019, 21(6), 579; https://doi.org/10.3390/e21060579
Received: 25 April 2019 / Revised: 31 May 2019 / Accepted: 7 June 2019 / Published: 10 June 2019
(This article belongs to the Special Issue Bayesian Inference and Information Theory)
This work applies two levels of inference within a Bayesian framework to accomplish estimation of the directions of arrivals (DoAs) of sound sources. The sensing modality is a spherical microphone array based on spherical harmonics beamforming. When estimating the DoA, the acoustic signals may potentially contain one or multiple simultaneous sources. Using two levels of Bayesian inference, this work begins by estimating the correct number of sources via the higher level of inference, Bayesian model selection. It is followed by estimating the directional information of each source via the lower level of inference, Bayesian parameter estimation. This work formulates signal models using spherical harmonic beamforming that encodes the prior information on the sensor arrays in the form of analytical models with an unknown number of sound sources, and their locations. Available information on differences between the model and the sound signals as well as prior information on directions of arrivals are incorporated based on the principle of the maximum entropy. Two and three simultaneous sound sources have been experimentally tested without prior information on the number of sources. Bayesian inference provides unambiguous estimation on correct numbers of sources followed by the DoA estimations for each individual sound sources. This paper presents the Bayesian formulation, and analysis results to demonstrate the potential usefulness of the model-based Bayesian inference for complex acoustic environments with potentially multiple simultaneous sources. View Full-Text
Keywords: Bayesian inference; maximum entropy; spherical harmonics; direction of arrival; model selection; parameter estimation Bayesian inference; maximum entropy; spherical harmonics; direction of arrival; model selection; parameter estimation
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Xiang, N.; Landschoot, C. Bayesian Inference for Acoustic Direction of Arrival Analysis Using Spherical Harmonics. Entropy 2019, 21, 579.

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