Addressing the data-association problem for multiple sound source localization using DOA estimates

In this paper, we consider the data association problem that arises when localizing multiple sound sources using direction of arrival (DOA) estimates from multiple microphone arrays. In such a scenario, the association of the DOAs across the arrays that correspond to the same source is unknown and must be found for accurate localization. We present an association algorithm that finds the correct DOA association to the sources based on features extracted for each source that we propose. Our method results in high association and localization accuracy in scenarios with missed detections, reverberation, and noise and outperforms other recently proposed methods.

[1]  Peter Molnar,et al.  Bearings-only target localization for an acoustical unattended ground sensor network , 2001, SPIE Defense + Commercial Sensing.

[2]  Nedelko Grbic,et al.  Source localization for multiple speech sources using low complexity non-parametric source separation and clustering , 2011, Signal Process..

[3]  Alexander Bertrand,et al.  Applications and trends in wireless acoustic sensor networks: A signal processing perspective , 2011, 2011 18th IEEE Symposium on Communications and Vehicular Technology in the Benelux (SCVT).

[4]  A. Weiss,et al.  Performance analysis of bearing-only target location algorithms , 1992 .

[5]  J.D. Reed,et al.  Multiple-source localization using line-of-bearing measurements: Approaches to the data association problem , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[6]  Xiao-Ping Zhang,et al.  A Novel Location-Penalized Maximum Likelihood Estimator for Bearing-Only Target Localization , 2012, IEEE Transactions on Signal Processing.

[7]  Harvey F. Silverman,et al.  A Fast Microphone Array SRP-PHAT Source Location Implementation using Coarse-To-Fine Region Contraction(CFRC) , 2007, 2007 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.

[8]  Pubudu N. Pathirana,et al.  Localization of Emitters via the Intersection of Bearing Lines: A Ghost Elimination Approach , 2007, IEEE Transactions on Vehicular Technology.

[9]  Parham Aarabi,et al.  EURASIP Journal on Applied Signal Processing 2003:4, 338–347 c ○ 2003 Hindawi Publishing Corporation The Fusion of Distributed Microphone Arrays for Sound Localization , 2002 .

[10]  Pubudu N. Pathirana,et al.  A discussion on passive location discovery in emitter networks using angle-only measurements , 2006, IWCMC '06.

[11]  Eric A. Lehmann,et al.  Diffuse Reverberation Model for Efficient Image-Source Simulation of Room Impulse Responses , 2010, IEEE Transactions on Audio, Speech, and Language Processing.

[12]  Athanasios Mouchtaris,et al.  Localizing multiple audio sources in a wireless acoustic sensor network , 2015, Signal Process..

[13]  Akihiko Sugiyama,et al.  A new DOA estimation method using a circular microphone array , 2007, 2007 15th European Signal Processing Conference.

[14]  Athanasios Mouchtaris,et al.  Real-time localization of multiple audio sources in a wireless acoustic sensor network , 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

[15]  David R. Wilson,et al.  Field test of an affordable, portable, wireless microphone array for spatial monitoring of animal ecology and behaviour , 2012 .

[16]  Paolo Toth,et al.  Algorithm for the solution of the Bottleneck Assignment Problem , 2005, Computing.

[17]  Kutluyil Dogançay,et al.  Bearings-only target localization using total least squares , 2005, Signal Process..

[18]  Athanasios Mouchtaris,et al.  Real-Time Multiple Sound Source Localization and Counting Using a Circular Microphone Array , 2013, IEEE Transactions on Audio, Speech, and Language Processing.

[19]  Sergios Theodoridis,et al.  Pattern Recognition, Fourth Edition , 2008 .

[20]  Ieee Staff.  2017 25th European Signal Processing Conference (EUSIPCO) , 2017 .