基于自适应阈值的船舶轨迹异常点检测算法  

Vessel Trajectory Outlier Detection Algorithm Based on Adaptive Threshold

作　　者：韩昭蓉 许光銮[2,3] 黄廷磊[2,3] 任文娟 HAN Zhao-rong;XU Guang-luan;HUANG Ting-lei;REN Wen-juan(School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China;Institute of Electronics,Chinese Academy of Sciences,Beijing 100190,China;Key Laboratory of Technology in Geo-Spatial Information Processing and Application System,Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]中国科学院大学电子电气与通信工程学院,北京100049 [2]中国科学院电子学研究所,北京100190 [3]中国科学院空间信息处理与应用系统技术重点实验室,北京100190

出　　处：《计算机与现代化》2018年第9期42-47,51,共7页Computer and Modernization

基　　金：国家自然科学基金资助项目(61725105;61331017)

摘　　要：定位技术的快速发展催生了轨迹大数据,轨迹数据中总是存在着明显偏离轨迹的异常点。检测出轨迹中的异常点对提高数据质量和后续知识发现精度至关重要。目前轨迹异常点检测算法主要为恒定速度阈值法,没有考虑目标在不同时刻运动状态的变化,仅能检测出速度超出指定阈值的一部分异常点,甚至出现检测错误的情况,算法鲁棒性较差。针对现有问题,本文提出一种基于自适应阈值的轨迹异常点检测算法(Trajectory Outlier Detection Algorithm based on adaptive Threshold,TODAT)。TODAT算法充分考虑了目标在一段时间内的运动信息和观测噪声的影响,采用局部阈值窗和均值滤波窗来计算阈值和速度,同时又引入了经济航速阈值和连续异常点放回机制。基于真实船舶数据的实验结果表明,本文算法可根据轨迹数据得到自适应的阈值,有效检测出全部异常点,大幅度提高轨迹数据的质量。The rapid development of positioning technology has given rise to trajectory big data,and there are always obviously aberrant outliers in trajectories. Detecting outliers in trajectory data is crucial for improving data quality and the accuracy of subsequent knowledge discovery. The existing trajectory outlier detection algorithm is mainly the constant speed threshold approach,the method does not consider the change of the motion state at different moments of the object,can only detect a part of outliers whose velocity exceeds the specified threshold,and even leads to the detection error,the robustness of the algorithm is poor. Aiming at above problems,this paper proposes a Trajectory Outlier Detection Algorithm based on adaptive Threshold（ TODAT）.Taking full account of the motion information and observation noise impact of the object in a period of time,the TODAT algorithm applies the local threshold window and the mean filtering window to calculate the threshold and velocity,and also adds the economic speed threshold and the continuous outliers re-judgment mechanism. The experimental results based on real vessel data show that the proposed algorithm can get the adaptive threshold according to trajectory data,effectively detect all the outliers and greatly improve the quality of the trajectory data.

关 键 词：轨迹数据 异常点检测 自适应阈值 局部阈值 均值滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]