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.

介绍了跨越三年的海上和沿海环境中船舶行为模式识别的综合文献综述。绝大多数研究都集中在使用人工智能 (AI)、贝叶斯网络和基于机器学习的方法从自动识别系统 (AIS) 数据中检测异常船只行为。AIS 是一个协作系统，它使用 VHF 收发器通过地面和卫星通信网络共享船舶信息。为了跟踪未安装 AIS 的小船，采用了不合作的监视系统。这些系统已在相对较少的出版物中进行了研究。在船舶行为模式识别中，目标分类至关重要，尤其是在不对称战争情况下。