Non-Line-of-Sight Sound Localization using a Single Microphone

This paper presents an acoustic non-line-of-sight localization technique that uses a single microphone and assumes only a single diffraction in the first-arrival sound. Knowing a map of the environment of interests, the proposed technique considers the frequency, time and power profiles of the received first-arrival sound. The profiles at different positions are estimated by the application of a diffraction model and compared with the measured profiles to compute the sound source position relative to the point of diffraction. A key achievement of the proposed technique is to enable non-line-of-sight localization using only one microphone without any time-consuming premeasurement. This technique is validated experimentally with two sound sources and under a couple of background noise levels.

[1]  Jean Rouat,et al.  Robust localization and tracking of simultaneous moving sound sources using beamforming and particle filtering , 2007, Robotics Auton. Syst..

[2]  G. Carter,et al.  The generalized correlation method for estimation of time delay , 1976 .

[3]  Darren B. Ward,et al.  Particle filtering algorithms for tracking an acoustic source in a reverberant environment , 2003, IEEE Trans. Speech Audio Process..

[4]  Garry J. Heard,et al.  Experimental validation of regularized array element localization , 2004 .

[5]  Peter R. Roth,et al.  Effective measurements using digital signal analysis , 1971, IEEE Spectrum.

[6]  G. C. Carter,et al.  The smoothed coherence transform , 1973 .

[7]  Jwu-Sheng Hu,et al.  Location and Orientation Detection of Mobile Robots Using Sound Field Features under Complex Environments , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  Paul M. Hofman,et al.  Relearning sound localization with new ears , 1998, Nature Neuroscience.

[9]  Hiroshi Mizoguchi,et al.  Multiple Sound Source Mapping for a Mobile Robot by Self-motion Triangulation , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Makoto Kumon,et al.  Spectral Cues for Robust Sound Localization with Pinnae , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  R. Kouyoumjian,et al.  A uniform geometrical theory of diffraction for an edge in a perfectly conducting surface , 1974 .

[12]  Joseph H. DiBiase A High-Accuracy, Low-Latency Technique for Talker Localization in Reverberant Environments Using Microphone Arrays , 2000 .

[13]  Deborah Estrin,et al.  Robust range estimation using acoustic and multimodal sensing , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[14]  Mark Yim,et al.  Automatic Configuration Recognition Methods in Modular Robots , 2008, Int. J. Robotics Res..

[15]  Makoto Kumon,et al.  Audio servo for robotic systems with pinnae , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Larry J. Greenstein,et al.  UWB delay profile models for residential and commercial indoor environments , 2005, IEEE Transactions on Vehicular Technology.

[17]  B. Kapralos,et al.  Acoustical diffraction modeling utilizing the Huygens-Fresnel principle , 2005, IEEE International Workshop on Haptic Audio Visual Environments and their Applications.

[18]  Ashutosh Saxena,et al.  Learning sound location from a single microphone , 2009, 2009 IEEE International Conference on Robotics and Automation.

[19]  Jwu-Sheng Hu,et al.  Gaussian mixture-sound field landmark model for robot localization , 2005, IEEE International Conference Mechatronics and Automation, 2005.

[20]  L. C. Mak Non-Line-of-Sight Localisation of a Sound Source , 2009 .