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http://dx.doi.org/10.7471/ikeee.2020.24.2.661

Maritime region segmentation and segment-based destination prediction methods for vessel path prediction  

Kim, Jonghee (School of Electrical Engineering, Korea Advanced Institute of Science and Technology)
Jung, Chanho (Dept. of Electrical Engineering, Hanbat National University)
Kang, Dokeun (The 3rd R&D Institute - 4th Directorate, Agency for Defense Development)
Lee, Chang Jin (The 5th R&D Insitute - 1st Directorate, Agency for Defense Development)
Publication Information
Journal of IKEEE / v.24, no.2, 2020 , pp. 661-664 More about this Journal
Abstract
In this paper, we propose a maritime region segmentation method and a segment-based destination prediction method for vessel path prediction. In order to perform maritime segmentation, clustering on destination candidates generated from the past paths is conducted. Then the segment-based destination prediction is followed. For destination prediction, different prediction methods are applied according to whether the current region is linear or not. In the linear domain, the vessel is regarded to move constantly, and linear prediction is applied. In the nonlinear domain with an uncertainty, we assume that the vessel moves similarly to the most similar past path. Experimental results show that applying the linear prediction and the prediction method using a similar path differently depending on the linearity and the uncertainty of the path is better than applying one of them alone.
Keywords
vessel path prediction; maritime region segmentation; destination prediction; linear/nonlinear region classification; mixed prediction;
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