Localization and separation of acoustic sources by using a 2.5-dimensional circular microphone array

2017 ◽  
Vol 142 (1) ◽  
pp. 286-297 ◽  
Author(s):  
Mingsian R. Bai ◽  
Chang-Sheng Lai ◽  
Po-Chen Wu
Keyword(s):  
Microphone Array ◽  
Acoustic Sources

A Real-Time Multiple Acoustic Sources Localization Method Using Widely Spaced Microphone Array

2013 ◽  
Vol 391 ◽  
pp. 580-583 ◽  
Author(s):  
Tian Yi Gu ◽  
Zhao Zhao ◽  
Ya Qi Wu ◽  
Zhi Yong Xu ◽  
Jing Yi Wang
Keyword(s):  
Real Time ◽  
Microphone Array ◽  
Localization Method ◽  
Cluster Process ◽  
Sound Detection ◽  
Acoustic Sources ◽  
Phase Differences

A real-time disambiguous localization method for multiple acoustic sources using widely spaced microphone array is proposed in this paper. The observation signals in each frame are firstly discriminated utilizing conventional energy-based sound detection measurement. Using inter-microphone phase differences (IPD), as well as an iterative cluster process, the DOAs of sources can be estimated while the phase wrapping ambiguity in conventional DUET is avoided.

scholarly journals Incident Signal Power Comparison for Localization of Concurrent Multiple Acoustic Sources

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Daniele Salvati ◽  
Sergio Canazza
Keyword(s):  
Open Space ◽  
Traditional Approach ◽  
Microphone Array ◽  
Measurement Techniques ◽  
Signal Power ◽  
Noisy Environment ◽  
Multiple Sources ◽  
Power Comparison ◽  
Open Spaces ◽  
Acoustic Sources

In this paper, a method to solve the localization of concurrent multiple acoustic sources in large open spaces is presented. The problem of the multisource localization in far-field conditions is to correctly associate the direction of arrival (DOA) estimated by a network array system to the same source. The use of systems implementing a Bayesian filter is a traditional approach to address the problem of localization in multisource acoustic scenario. However, in a real noisy open space the acoustic sources are often discontinuous with numerous short-duration events and thus the filtering methods may have difficulty to track the multiple sources. Incident signal power comparison (ISPC) is proposed to compute DOAs association. ISPC is based on identifying the incident signal power (ISP) of the sources on a microphone array using beamforming methods and comparing the ISP between different arrays using spectral distance (SD) measurement techniques. This method solves the ambiguities, due to the presence of simultaneous sources, by identifying sounds through a minimization of an error criterion on SD measures of DOA combinations. The experimental results were conducted in an outdoor real noisy environment and the ISPC performance is reported using different beamforming techniques and SD functions.

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