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http://dx.doi.org/10.7471/ikeee.2020.24.4.1176

A New Vessel Path Prediction Method Based on Anticipation of Acceleration of Vessel  

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 Institute - 1st Directorate, Agency for Defense Development)
Publication Information
Journal of IKEEE / v.24, no.4, 2020 , pp. 1176-1179 More about this Journal
Abstract
Vessel path prediction methods generally predict the latitude and longitude of a future location directly. However, in the case of direct prediction, errors could be large since the possible output range is too broad. In addition, error accumulation could occur since recurrent neural networks-based methods employ previous predicted data to forecast future data. In this paper, we propose a vessel path prediction method that does not directly predict the longitude and latitude. Instead, the proposed method predicts the acceleration of the vessel. Then the acceleration is employed to generate the velocity and direction, and the values decide the longitude and latitude of the future location. In the experiment, we show that the proposed method makes smaller errors than the direct prediction method, while both methods employ the same model.
Keywords
Vessel path prediction; Ship trajectory prediction; Long short-term memory network (LSTM); recurrent neural network (RNN); Acceleration prediction;
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