|本期目录/Table of Contents|

[1]甄荣,邵哲平,潘家财,等.基于统计学理论的船舶轨迹异常识别[J].集美大学学报(自然科学版),2015,20(3):193-197.
　ZHEN Rong,SHAO Zhe-ping,PAN Jia-cai,et al.A Study on the Identification of Abnormal Ship Trajectory Based on Statistic Theories[J].Journal of Jimei University,2015,20(3):193-197.
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《集美大学学报（自然科学版）》[ISSN:1007-7405/CN:35-1186/N]

卷:
第20卷
期数:
2015年第3期
页码:
193-197
栏目:
航海技术与物流工程
出版日期:
2015-05-25

文章信息/Info

Title:
A Study on the Identification of Abnormal Ship Trajectory Based on Statistic Theories
作者:
甄荣; 邵哲平; 潘家财; 赵强
（集美大学航海学院，福建 厦门 361021）
Author(s):
ZHEN Rong; SHAO Zhe-ping; PAN Jia-cai; ZHAO Qiang
(Navigation College,Jimei University,Xiamen 361021,China)
关键词:
船舶; 航行轨迹; 统计学; AIS信息; 监控
Keywords:
ship; trajectory; statistic theories; AIS Data; surveillance
分类号:
-
DOI:
-
文献标志码:
A
摘要:
为了准确识别异常航行轨迹的船舶，以船舶AIS信息为数据源，利用统计学中曲线拟合的最小二乘法对训练集船舶轨迹点进行拟合，得到船舶典型航行轨迹的数学表达模型，以此作为标准，通过计算监控船舶轨迹点与典型轨迹间的距离是否大于典型轨迹95%置信区间的范围，从而对轨迹异常的船舶进行识别.实验结果表明，该方法可以有效地识别轨迹异常船舶.将该方法运用到监控系统中可以提高海上交通监控效率.
Abstract:
In order to identify the abnormal trajectory of a ship in the maritime traffic monitoring system automatically,sourced from shipborne AIS data,the curve fitting of statistic theories was used to fit the trajectory points of a training vessel,so as to obtain the mathematical model for the typical route of a ship.Based on this, ships with abnormal trajectories are identified through calculating whether the distance between validation data and typical route is wider than the 95% confidence interval of the typical route.The results show that abnormal ship trajectories can be identified efficiently this way.If this is applied to the vessel traffic surveillance system,the efficiency such surveillance will be increased significantly.

参考文献/References:

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备注/Memo

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更新日期/Last Update: 2015-07-04