Stochastic Matched Filter outperforms Teager-Kaiser-Mallat for tracking a plurality of sperm whales

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 Cramer-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 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. 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.

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