Open AccessValidation of Radar Image Tracking Algorithms with Simulated Data
Author(s) -
Frank Heymann,
Julian Hoth,
Paweł Banyś,
Gregor Siegert
Publication year - 2017
Publication title -
transnav the international journal on marine navigation and safety of sea transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.253
H-Index - 5
eISSN - 2083-6481
pISSN - 2083-6473
DOI - 10.12716/1001.11.03.18
Subject(s) - computer science , radar , state vector , radar tracker , computer vision , tracking (education) , bittorrent tracker , position (finance) , particle filter , metric (unit) , artificial intelligence , real time computing , algorithm , filter (signal processing) , engineering , eye tracking , telecommunications , pedagogy , physics , operations management , economics , classical mechanics , finance , psychology
Collision avoidance is one of the high‐level safety objectives and requires a complete and reliable description of the maritime traffic situation. The radar is specified by the IMO as the primary sensor for collision avoidance. In this paper we study the performance of multi‐target tracking based on radar imagery to refine the maritime traffic situation awareness. In order to achieve this we simulate synthetic radar images and evaluate the tracking performance of different Bayesian multi‐target trackers (MTTs), such as particle and JPDA filters. For the simulated tracks, the target state estimates in position, speed and course over ground will be compared to the reference data. The performance of the MTTs will be assessed via the OSPA metric by comparing the estimated multi‐object state vector to the reference. This approach allows a fair performance analysis of different tracking algorithms based on radar images for a simulated maritime scenario.
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