Antarctic Blue Whale Calls Detection Based on an Improved Version of the Stochastic Matched Filter

International audience As a first step to Antarctic Blue Whale monitoring, a new method based on a passive application of the Stochastic Matched Filter (SMF) is developed. To perform Z-call detection in noisy environment, improvements on the classical SMF requirements are proposed. The signal’s refe...

Full description

Bibliographic Details
Main Authors: Bouffaut, Léa, Dreo, Richard, Labat, Valérie, Boudraa, Abdel-Ouahab, Barruol, Guilhem
Other Authors: Institut de Recherche de l'Ecole Navale (IRENAV), Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Arts et Métiers Sciences et Technologies, HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), Laboratoire GéoSciences Réunion (LGSR), Université de La Réunion (UR)-Institut de Physique du Globe de Paris (IPG Paris), Institut de Physique du Globe de Paris (IPGP), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université de La Réunion (UR)-Institut de Physique du Globe de Paris (IPG Paris)-Centre National de la Recherche Scientifique (CNRS)
Format: Conference Object
Language:English
Published: HAL CCSD 2017
Subjects:
Kos
Online Access:https://hal.science/hal-02140787
https://hal.science/hal-02140787/document
https://hal.science/hal-02140787/file/IRENAV_EUSIPCO_2017_BOUFFAUT.pdf
Description
Summary:International audience As a first step to Antarctic Blue Whale monitoring, a new method based on a passive application of the Stochastic Matched Filter (SMF) is developed. To perform Z-call detection in noisy environment, improvements on the classical SMF requirements are proposed. The signal’s reference is adjusted, the background noise estimation is reevaluated to avoid operator’s selection, and the time-dependent Signal to Noise Ratio (SNR) estimation is revised by time-frequency analysis. To highlight the SMF’s robustness against noise, it is applied on a Ocean Bottom Seismometers hydrophone-recorded data and compared to the classical Matched Filter: the output’s SNR is maximized and the false alarm drastically decreased.