An Empirical Study of Collaborative Acoustic Source Localization

Authors:
Andreas Mantik Ali;Shadnaz Asgari;Travis C. Collier;Michael Allen;Lewis Girod;Ralph E. Hudson;Kung Yao;Charles E. Taylor;Daniel T. Blumstein
Affiliations:
University of California-Los Angeles, Los Angeles, USA;University of California-Los Angeles, Los Angeles, USA;University of California-Los Angeles, Los Angeles, USA;Coventry University, Coventry, UK;Massachusetts Institute of Technology, Cambridge, USA;University of California-Los Angeles, Los Angeles, USA;University of California-Los Angeles, Los Angeles, USA;University of California-Los Angeles, Los Angeles, USA;University of California-Los Angeles, Los Angeles, USA
Venue:
Journal of Signal Processing Systems
Year:
2009

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Abstract

Field biologists use animal sounds to discover the presence of individuals and to study their behavior. Collecting bio-acoustic data has traditionally been a difficult and time-consuming process in which researchers use portable microphones to record sounds while taking notes of their own detailed observations. The recent development of new deployable acoustic sensor platforms presents opportunities to develop automated tools for bio-acoustic field research. In this work, we implement both two-dimensional (2D) and three-dimensional (3D) AML-based source localization algorithms. The 2D algorithm is used to localize marmot alarm-calls of marmots on the meadow ground. The 3D algorithm is used to localize the song of Acorn Woodpecker and Mexican Antthrush birds situated above the ground. We assess the performance of these techniques based on the results from four field experiments: two controlled test of direction-of-arrival (DOA) accuracy using a pre-recorded source signal for 2D and 3D analysis, an experiment to detect and localize actual animals in their habitat, with a comparison to ground truth gathered from human observations, and a controlled test of localization experiment using pre-recorded source to enable careful ground truth measurements. Although small arrays yield ambiguities from spatial aliasing of high frequency signals, we show that these ambiguities are readily eliminated by proper bearing crossings of the DOAs from several arrays. These results show that the AML source localization algorithm can be used to localize actual animals in their natural habitat using a platform that is practical to deploy.