Abstract
Safe navigation and guidance of an autonomous surface vehicle (ASV) depends on automatic sensor fusion methods capable of discovering static and moving obstacles in the vicinity of the ASV. A key component in such a system is a method for target tracking . In this paper, we report a complete radar tracking system based on the classical probabilistic data association filter (PDAF) . The tracking system is tested on real radar data recorded in Trondheimsfjorden, Norway.
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Acknowledgements
This work was supported by the Research Council of Norway through the projecs 223254 (Centre for Autonomous Marine Operations and Systems at NTNU) and the project 244116/O70 (Sensor Fusion and Collision Avoidance for Autonomous Marine Vehicles). The authors would like to express great gratitude to Kongsberg Maritime and Maritime Robotics for placing high-grade navigation technology and the Telemetron vehicle at our disposal, and especially Thomas Ingebretsen for help with implementing the software interfaces.
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Wilthil, E.F., Flåten, A.L., Brekke, E.F. (2017). A Target Tracking System for ASV Collision Avoidance Based on the PDAF. In: Fossen, T., Pettersen, K., Nijmeijer, H. (eds) Sensing and Control for Autonomous Vehicles. Lecture Notes in Control and Information Sciences, vol 474. Springer, Cham. https://doi.org/10.1007/978-3-319-55372-6_13
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DOI: https://doi.org/10.1007/978-3-319-55372-6_13
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