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Design and testing of robust acoustic arrays for localization and enhancement of several bird sources
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Source Information Processing In Sensor Networks archive
Proceedings of the 5th international conference on Information processing in sensor networks table of contents
Nashville, Tennessee, USA
POSTER SESSION: Main track table of contents
Pages: 268 - 275  
Year of Publication: 2006
ISBN:1-59593-334-4
Authors
Chiao-En Chen  UCLA, Los Angeles, CA
Andreas M. Ali  UCLA, Los Angeles, CA
Hanbiao Wang  UCLA, Los Angeles, CA
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Sensor network technology can revolutionize the study of animal ecology by providing a means of non-intrusive, simultaneous, unmanned monitoring. In this paper, we investigate the design, analysis, and testing of acoustic arrays for localizing bird vocalizations of different species. The spectra of the bird waveforms affect the desired dimension of the array. Microphones are placed in a uniform circular array and are finely synchronized within a few microseconds. We apply the Approximate Maximum Likelihood (AML) method to estimate the source direction-of-arrival (DOA) and perform beamforming for signal enhancement. The crossing of the distributed DOA estimated bearings is used to localize the birds, and the enhanced signals are used for training and estimation for the classification of the birds. The experimental results demonstrate the practicality and robustness of our array design.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Chiao-En Chen: colleagues
Andreas M. Ali: colleagues
Hanbiao Wang: colleagues