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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.

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.