Design and testing of robust acoustic arrays for localization and enhancement of several bird sources

Authors:
Chiao-En Chen;Andreas M. Ali;Hanbiao Wang
Affiliations:
UCLA, Los Angeles, CA;UCLA, Los Angeles, CA;UCLA, Los Angeles, CA
Venue:
Proceedings of the 5th international conference on Information processing in sensor networks
Year:
2006

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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.