By Topic

An Empirical Study of Collaborative Acoustic Source Localization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Andreas M. Ali ; Electrical Engineering, UC, Los Angeles ; Kung Yao ; Travis C. Collier ; Charles E. Taylor
more authors

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 deploy- able acoustic sensor platforms presents opportunities to develop automated tools for bio-acoustic field research. In this work, we implement an AML-based source localization algorithm, and use it to localize marmot alarm-calls. We assess the performance of these techniques based on results from two field experiments: (1) a controlled test of direction-of- arrival (DOA) accuracy using a pre-recorded source signal, and (2) an experiment to detect and localize actual animals in their habitat, with a comparison to ground truth gathered from human observations. 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.

Published in:

2007 6th International Symposium on Information Processing in Sensor Networks

Date of Conference:

25-27 April 2007