This paper compare two real-time passive underwater acoustic methods to track multiple emitting whales using four or more omni-directional widely-spaced bottom-mounted hydrophones. The Stochastic Matched Filter (SMF) is first used in the whale tracking. The SMF with an echo removal is compared to the Teager-Kaiser-Mallat (TKM) filter method. We briefly review the SMF and TKM theory, rough Time Delays Of Arrival are calculated, selected and filtered, and used to estimate the positions of whales for a constant or linear sound speed profile. The complete algorithm is tested on real data from the NUWC and the AUTEC. We evaluate the a priori performance of the system via the Cramér-Rao Lower Bound (CRLB) and Monte Carlo simulations. The CRLB and Monte Carlo simulations are computed and compared with the tracking results. SMF shows higher performance than TKM with more position estimated.
Results is validated by similar results from the US Navy andHawaii univ labs in the case of one whale, and by similar whales counting from the Columbia univ. ROSA lab in the case of multiple whales. The model is validated with good performances with the theoric CRLB and the computed confidence ellipses. At this time, our tracking method is the only one giving typical speed and depth estimations for multiple (4) emitting whales located at 1 to 5 km from the hydrophones.
This paper provides a real-time passive underwater acoustic method to track multiple emitting whales using four or more omni-directional widely-spaced bottom-mounted hydrophones. After a non-parametric Teager-Kaiser-Mallat signal filtering, rough Time Delays Of Arrival are calculated, selected and filtered, and used to estimate the positions of whales for a constant or linear sound speed profile. The complete algorithm is tested on real data from the NUWC 1 and the AUTEC 2 . Our model is validated by similar results from the US Navy and Hawaii univ labs in the case of one whale, and by similar whales counting from the Columbia univ. ROSA lab in the case of multiple whales. At this time, our tracking method is the only one giving typical speed and depth estimations for multiple (5) emitting whales located at 1 to 5 km from the hydrophones.
This paper discusses on estimating the behavior of a sperm whale using hydrophones recordings thanks to a set of features extracted from a real-time passive underwater acoustic tracking algorithm for multiple emitting whales. Acoustic localization permits to study whales' behavior in deep water (several hundreds of meters) without infering with the environment. Here, we use a real-time multiple tracking algorithm, which provides a localization of one or several sperm whales. Thanks to the positions coordinates and the audio files, we are able to automatically label the signal and to extract different features such as the speed, energy of the clicks, Inter-Click-Interval (ICI)... These features allow us to cross-analyse the whale behavior (foraging , hunting, ingestion) and to see the influence of each parameters and the dependency between them. Finally, we generate a XML file for description and efficient access of deep ocean sound records for cetacean studies, which leads to index and structure the audio files. Thus, the behavior study is facilitated choosing and accessing the corresponding index in the recording. The complete method is processed on real data from the NUWC 1 and the AUTEC 2 . As an illustration, we process the algorithm on a one whale case and study the correlation between the features and the whale behavior during the diving.
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