Automatic identification system (AIS) trajectory data compression algorithm of a fishing vessel based on improved Sliding Window

DONG Wanting, YU Hong, ZHOU Yizhi, ZHANG Fangyan, LIANG Liang, LU Xiaoli

Journal of Dalian Fisheries University ›› 2020, Vol. 35 ›› Issue (3) : 462.

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Journal of Dalian Fisheries University ›› 2020, Vol. 35 ›› Issue (3) : 462. DOI: 10.16535/j.cnki.dlhyxb.2019-265

Automatic identification system (AIS) trajectory data compression algorithm of a fishing vessel based on improved Sliding Window

  • DONG Wanting1, YU Hong1,2,3*, ZHOU Yizhi1, ZHANG Fangyan1, LIANG Liang1, LU Xiaoli1
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Abstract

An automatic identification system (AIS) trajectory data compression algorithm of a fishing vessel is proposed based on improved Sliding Window to deal with poor AIS trajectory data quality of the fishing vessels due to requirement for more feature points. The algorithm achieves effective compression of fishing vessel trajectories as much as possible by effective using temporal information and position information of the fishing vessel AIS trajectory data, the feature points determined by the characteristics of the longitude and latitude change trend between the adjacent track points, and effective compression of high-density stagnation points based on retention time information to keep fishing vessel straight intermediate point by sampling method. The comparative tests revealed that the compression ratio of the algorithm was reduced from 99% to less than 94% compared with the D-P algorithm, with good feature points of the fishing vessel trajectory, and improvement of the trajectory distortion of compressing trajectory. The findings indicate that the algorithm is more suitable for compressing fishing vessel trajectory.

Key words

fishing vessel trajectory / automatic identification system (AIS) data / trajectory compression

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DONG Wanting, YU Hong, ZHOU Yizhi, ZHANG Fangyan, LIANG Liang, LU Xiaoli. Automatic identification system (AIS) trajectory data compression algorithm of a fishing vessel based on improved Sliding Window[J]. Journal of Dalian Fisheries University, 2020, 35(3): 462 https://doi.org/10.16535/j.cnki.dlhyxb.2019-265
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