A beamforming method for multiple source DOA estimation, spectrum separation and localization from field data

Authors:
Juo-Yu Lee;Zac Harlow;Travis Collier;Charles Taylor;Kung Yao
Affiliations:
University of California, Los Angeles, USA;University of California, Los Angeles, USA;University of California, Los Angeles, USA;University of California, Los Angeles, USA;University of California, Los Angeles, USA
Venue:
Proceedings of the 11th international conference on Information Processing in Sensor Networks
Year:
2012

Citing 2
Cited 0

An Empirical Study of Collaborative Acoustic Source Localization

Journal of Signal Processing Systems
Maximum-likelihood source localization and unknown sensor locationestimation for wideband signals in the near-field

IEEE Transactions on Signal Processing

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Abstract

In this abstract, we present a beamforming method for estimating the directions and locations of multiple sources and separating each source's spectrum from field data collected by a wireless acoustic sensor network. Each acoustic sensor is equipped with four microphones that receive acoustic signals in a time-synchronized manner. The difference in time-of-arrival of proximal signals depends on the source direction with respect to the geometry of the microphone array. We show that by using beamforming in the frequency domain, the locations and Direction-Of-Arrivals (DOAs) of multiple 3D sources may be estimated, and the source spectrum may be separated from the audio data spectra.