K-means clustering for SAT-AIS data analysis

被引:11
作者
Mieczynska, Marta [1 ]
Czarnowski, Ireneusz [2 ]
机构
[1] Gdynia Maritime Univ, Dept Marine Telecommun, Morska 81-87, PL-81225 Gdynia, Poland
[2] Gdynia Maritime Univ, Dept Informat Syst, Morska 81-87, PL-81225 Gdynia, Poland
关键词
K-means; Clustering; SAT-AIS; Data analysis; Maritime data analytics;
D O I
10.1007/s13437-021-00241-3
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The paper deals with a problem of automatic identification system (AIS) data analysis, especially eliminating the impact of AIS packet collision and detecting existing outliers in AIS data. To solve this problem, a clustering-based approach is proposed. AIS is a system that supports the exchange of information between vessels about their trajectories, e.g. position, speed or course. However, SAT-AIS, which enables the system to work on a global scale, struggles against packet collisions due to the fact that the satellite, which receives AIS data from ships, has a field of view that covers multiple areas that are not synchronized among themselves. As a result, the received data is difficult to process by AIS receivers, because most of the messages have a character of noise. In this paper, results of a computational experiment using k-means algorithm for packet recovery and for dealing with noise have been presented. The outcome proves that a clustering-based approach could be used as an initial step in AIS packet reconstruction, when the original data is incorrect.
引用
收藏
页码:377 / 400
页数:24
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