基于大数据分析的船舶航迹拟合研究  

Research on ship track fitting based on big data analysis

作　　者：黎永壹 曹欣科 韩开旭 LI Yong-yi;CAO Xin-ke;HAN Kai-xu(College of information Science and Engineering,Guilin University of Technology,Guilin 541006,China;College of Electronic and Information Engineering,Beibu Gulf University,Qinzhou 535011,China)

机构地区：[1]桂林理工大学信息科学与工程学院,广西桂林541006 [2]北部湾大学电子与信息工程学院,广西钦州535011

出　　处：《舰船科学技术》2022年第7期174-177,共4页Ship Science and Technology

基　　金：广西高校科研项目(2017KY0797);广西教改工程项目(2019JGB271);广西自然科学基金项目(2016GXNSFAA380188);国家社会科学基金项目(19XJY015)。

摘　　要：依据AIS设备获取船舶航迹AIS数据,并统一化处理AIS数据,结合船舶航迹数据特征,应用大数据分析技术(数据挖掘算法)提取船舶航迹拟合需求数据,依据相邻时刻航向角差值将船舶航迹划分为直线阶段与曲线阶段,采用线性拟合法与最小二乘曲线拟合法分别拟合直线阶段与曲线阶段的船舶航迹,获取精确的船舶航迹线。实验数据表明:应用本文方法获得的航迹拟合需求数据提取时延小于给定最大限值,船舶航迹拟合结果与实际船舶航迹几乎保持一致,证实了本文方法航迹拟合效果较佳。Obtain the ship track AIS data based on the AIS equipment, and process the AIS data in a unified manner.Combined with the ship track data characteristics, the big data analysis technology(data mining algorithm) is applied to extract the ship track fitting demand data. The ship track is divided into a straight line stage and a curve stage, and the linear fitting method and the least squares curve fitting method are used to fit the ship track in the straight stage and the curve stage respectively to obtain the accurate ship track line. The experimental data show that the data extraction delay of the track fitting requirement obtained by the proposed method is less than the given maximum limit, and the ship track fitting result is almost consistent with the actual ship track, which fully confirms the track fitting effect of the proposed method. better.

关 键 词：大数据分析 船舶航迹 航迹拟合 AIS数据 航迹预测 分段拟合 

分 类 号：U66[交通运输工程—船舶及航道工程]