Research into vessel behaviour pattern recognition in the maritime domain: Past, present and future

被引:15
|
作者
Dogancay, Kutluyil [1 ]
Tu, Ziming [2 ]
Ibal, Gokhan [2 ]
机构
[1] Univ South Australia, UniSA Stem, Mawson Lakes, SA 5095, Australia
[2] DST Grp, Joint & Operat Anal Div, Fishermans Bend, Vic 3207, Australia
关键词
Pattern of life; Vessel behaviour recognition; Anomaly detection; Bayesian networks; Plan recognition; Target tracking; Target classification; SYSTEM;
D O I
10.1016/j.dsp.2021.103191
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A comprehensive literature review on vessel behaviour pattern recognition in maritime and littoral environments, spanning a period of three decades, is presented. A vast majority of research focuses on anomalous vessel behaviour detection from Automated Identification System (AIS) data, using artificial intelligence (AI), Bayesian networks and machine learning based methods. AIS is a cooperative system that employs VHF transceivers to share vessel information through terrestrial and satellite communication networks. To track small boats not fitted with AIS, uncooperative surveillance systems are employed. These systems have been studied in a relatively small number of publications. In vessel behaviour pattern recognition, target classification is critically important, particularly, in asymmetric warfare situations. The paper concludes with a discussion of future outlook in vessel behaviour pattern recognition research. Crown Copyright (C) 2021 Published by Elsevier Inc. All rights reserved.
引用
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页数:7
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