Abstract
In this paper we present a novel method for the acoustic tracking of multiple Autonomous Underwater Vehicles. While the problem of tracking a single moving vehicle has been addressed in the literature, tracking multiple vehicles is a problem that has been overlooked, mostly due to the inherent difficulties on data association with traditional acoustic localization networks. The proposed approach is based on a Probability Hypothesis Density Filter, thus overcoming the data association problem. Our tracker is able not only to successfully estimate the positions of the vehicles, but also their velocities. Moreover, the tracker estimates are labelled, thus providing a way to establish track continuity of the targets. Using real word data, our method is experimentally validated and the performance of the tracker is evaluated.
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Acknowledgements
This work is financed by the ERDF—European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the FCT—Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project POCI-01-0145-FEDER-006961 . The first author was supported by the Portuguese Foundation for Science and Technology through the Ph.D. grant SFRH/BD/70727/2010.
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Melo, J., Matos, A.C. Tracking multiple Autonomous Underwater Vehicles. Auton Robot 43, 1–20 (2019). https://doi.org/10.1007/s10514-018-9696-7
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DOI: https://doi.org/10.1007/s10514-018-9696-7