Poster abstract: voxnet acoustic array for multiple bird source separation by beamforming using measured data

Authors:
Shengsheng Cai;Travis Collier;Lewis Girod;Ralph E. Hudson;Kung Yao;Charles E. Taylor;Ming Bao;Zhi Wang
Affiliations:
Zhejiang University, Hangzhou, China;UCLA, Los Angeles, USA;MIT, Cambridge, USA;UCLA, Los Angeles, USA;UCLA, Los Angeles, USA;UCLA, Los Angeles, USA;IACAS, Beijing, China;Zhejiang University, Hangzhou, China
Venue:
Proceedings of the 12th international conference on Information processing in sensor networks
Year:
2013

Citing 2
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Abstract

In this paper, we present simulation and experimental studies of multiple bird source separation based on the Voxnet acoustic array node. The Approximate Maximum Likelihood (AML) method is used to estimate blindly the direction-of-arrivals(DOAs) of the sources to generate the steering vectors in order to separate the sources via beamforming. Simulation and measured data confirmed the proper operations of the AML beamforming algorithm and the Voxnet hardware node.