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Machine and deep learning approaches to localization and range estimation of underwater acoustic sources

Author
Houegnigan, L.; Safari, P.; Nadeu, C.; Andre, M.; Van Der Schaar, M.
Type of activity
Presentation of work at congresses
Name of edition
3rd Acoustics in Underwater Geosciences Symposium
Date of publication
2017
Presentation's date
2017-07-26
Book of congress proceedings
2017 IEEE/OES Acoustics in Underwater Geosciences Symposium (RIO Acoustics 2017): Rio de Janeiro, Brazil: 25-27 July 2017
First page
1
Last page
6
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
DOI
https://doi.org/10.1109/RIOAcoustics.2017.8349716 Open in new window
Project funding
Deep learning technologies for speech and audio processing
Repository
http://hdl.handle.net/2117/118230 Open in new window
URL
https://ieeexplore.ieee.org/document/8349716/ Open in new window
Abstract
This paper introduces ongoing experiments and early results for the underwater localization and range estimation of acoustic sources. Beyond classical results obtained for direction of arrival estimation, results concerning range estimation using supervised learning with neural networks having both shallow and deep architectures are presented. The developed method is applicable in the context of a single sensor, a compact array, or a small aperture towed array and provided results with great pot...
Citation
Houegnigan, L., Safari, P., Nadeu, C., Andre, M., Van Der Schaar, M. Machine and deep learning approaches to localization and range estimation of underwater acoustic sources. A: Acoustics in Underwater Geosciences Symposium. "2017 IEEE/OES Acoustics in Underwater Geosciences Symposium (RIO Acoustics 2017): Rio de Janeiro, Brazil: 25-27 July 2017". Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1-6.
Keywords
Array processing, Deep architectures, Deep learning, Density estimation, Direction of arrival estimation, Learning approach, Network architecture, Neural networks, Range estimation, Range finders, Real time solution, Source localization, Underwater acoustics, Underwater localization, acoustics, array processing, deep learning, neural networks, range estimation, source localization Acoustics
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
LAB - Laboratory of Applied Bioacoustics
TALP - Centre for Language and Speech Technologies and Applications
VEU - Speech Processing Group

Participants