Abstract
This paper presents a general method for the integration of distributed microphone arrays for localization of a sound source. The recently proposed sound localization technique, known as SRP-PHAT, is shown to be a special case of the more general microphone array integration mechanism presented here. The proposed technique utilizes spatial likelihood functions (SLFs) produced by each microphone array and integrates them using a weighted addition of the individual SLFs. This integration strategy accounts for the different levels of access that a microphone array has to different spatial positions, resulting in an intelligent integration strategy that weighs the results of reliable microphone arrays more significantly. Experimental results using 10 2-element microphone arrays show a reduction in the sound localization error from 0.9 m to 0.08 m at a signal-to-noise ratio of 0 dB. The proposed technique also has the advantage of being applicable to multimodal sensor networks.
Highlights
The localization of sound sources using microphone arrays has been extensively explored in the past [1, 2, 3, 4, 5, 6, 7]
For the ith microphone pair, the probability density function (PDF) of the time difference of arrival (TDOA) is estimated from the histogram consisting of the peaks of cross correlations performed on multiple speech segments
In the case when pairs of microphones are integrated without taking the spatial observabilities into account using spatial likelihood functions (SLFs) obtained using the phase transform (PHAT) technique, the proposed sensor fusion algorithm is equivalent to the steered response power (SRP)-PHAT approach
Summary
The localization of sound sources using microphone arrays has been extensively explored in the past [1, 2, 3, 4, 5, 6, 7]. In these regions, integrating the results of the multiple arrays may yield a more accurate localization than that obtained by the individual arrays Another matter that needs to be taken into consideration for large environments is the level of access of each array to different spatial positions. Each microphone array will have a spatial likelihood function (SLF), which will report the likelihood of a sound source at each spatial position based on the readings of the current microphone array [8, 13, 15] It is shown, using simulations and experimental results, that the SOFs and SLFs for different microphone arrays can be combined to result in a robust sound localization system utilizing multiple microphone arrays. The proposed microphone array integration strategy is shown to be equivalent, in the case that all arrays have equal access, to the array integration strategies previously proposed [7, 12]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
