Study of Automatic Anomalous Behaviour Detection Techniques for Maritime Vessels
Study of Automatic Anomalous Behaviour Detection Techniques for Maritime Vessels
复制标题
海上船舶异常行为自动检测技术研究
DOI：
10.1017/s0373463317000066
复制
发表时间：
2017-07-01
影响因子：
2.4
通讯作者：
Shu, Gao
中科院分区：
文献类型：
--
作者：
Sidibe, Abdoulaye;Shu, Gao
海洋领域是大宗运输使用最多的环境，使海上安全和安保成为一个重要问题。海上安全和安保的一个主要方面是对海上情况的了解。为了实现有效的海上态势感知，最近已经在基于自动识别系统（AIS）提供的运动数据的自动异常海上船舶运动行为检测方面做出了许多努力。在本文中，我们提出了一个国家的最先进的自动异常海上船舶行为检测技术的基础上AIS运动数据的审查。首先，我们将2011年至2016年期间提出的一些自动检测异常海上船舶行为的方法分类为不同的类别，包括统计，机器学习和数据挖掘，并概述它们。然后，我们讨论了一些相关的问题，提出的方法，并确定在异常的海上船舶行为的自动检测的趋势。
The maritime domain is the most utilised environment for bulk transportation, making maritime safety and security an important concern. A major aspect of maritime safety and security is maritime situational awareness. To achieve effective maritime situational awareness, recently many efforts have been made in automatic anomalous maritime vessel movement behaviour detection based on movement data provided by the Automatic Identification System (AIS). In this paper we present a review of state-of-the-art automatic anomalous maritime vessel behaviour detection techniques based on AIS movement data. First, we categorise some approaches proposed in the period 2011 to 2016 to automatically detect anomalous maritime vessel behaviour into distinct categories including statistical, machine learning and data mining, and provide an overview of them. Then we discuss some issues related to the proposed approaches and identify the trend in automatic detection of anomalous maritime vessel behaviour.