Observations and Bayesian location methodology of transient acoustic signals (likely blue whales) in the Indian Ocean, using a hydrophone triplet

Autor(en)
Ronan Le Bras, Heidi Kuzma, Victor Sucic, Götz Bokelmann
Abstrakt

A notable sequence of calls was encountered, spanning several days in January 2003, in the central part of the Indian Ocean on a hydrophone triplet recording acoustic data at a 250 Hz sampling rate. This paper presents signal processing methods applied to the waveform data to detect, group, extract amplitude and bearing estimates for the recorded signals. An approximate location for the source of the sequence of calls is inferred from extracting the features from the waveform. As the source approaches the hydrophone triplet, the source level (SL) of the calls is estimated at 187 ± 6 dB re: 1 μPa-1 m in the 15-60 Hz frequency range. The calls are attributed to a subgroup of blue whales, Balaenoptera musculus, with a characteristic acoustic signature. A Bayesian location method using probabilistic models for bearing and amplitude is demonstrated on the calls sequence. The method is applied to the case of detection at a single triad of hydrophones and results in a probability distribution map for the origin of the calls. It can be extended to detections at multiple triads and because of the Bayesian formulation, additional modeling complexity can be built-in as needed.

Organisation(en)
Institut für Meteorologie und Geophysik
Externe Organisation(en)
CTBTO Preparatory Comission, Chatelet Resources LLC, University of Rijeka
Journal
Journal of the Acoustical Society of America
Band
139
Seiten
2656-2667
Anzahl der Seiten
12
ISSN
0001-4966
DOI
https://doi.org/10.1121/1.4948758
Publikationsdatum
05-2016
Peer-reviewed
Ja
ÖFOS 2012
105126 Angewandte Geophysik, 105122 Seismik, 105102 Allgemeine Geophysik, 105124 Tektonik
Schlagwörter
ASJC Scopus Sachgebiete
Arts and Humanities (miscellaneous), Acoustics and Ultrasonics
Link zum Portal
https://ucrisportal.univie.ac.at/de/publications/b0996866-b5b6-4308-90fa-fdad92c0cdc5