计算机应用 ›› 2016, Vol. 36 ›› Issue (1): 122-127.DOI: 10.11772/j.issn.1001-9081.2016.01.0122

• 先进计算 • 上一篇    下一篇

基于运动状态改变的在线全球定位系统轨迹数据压缩

刘磊军, 房晨, 张磊, 鲍苏宁   

  1. 中国矿业大学 计算机科学与技术学院, 江苏 徐州 221116
  • 收稿日期:2015-07-01 修回日期:2015-09-13 出版日期:2016-01-10 发布日期:2016-01-09
  • 通讯作者: 刘磊军(1991-),男,安徽安庆人,硕士研究生,主要研究方向:移动对象轨迹数据挖掘
  • 作者简介:房晨(1991-),男,河北衡水人,硕士研究生,主要研究方向:智能信息处理;张磊(1977-),男,江苏徐州人,副教授,博士,CCF会员,主要研究方向:移动对象轨迹数据挖掘;鲍苏宁(1991-),男,江苏泰州人,硕士研究生,主要研究方向:移动对象轨迹数据挖掘。
  • 基金资助:
    中央高校基本科研业务费专项(2014XT04);教育部博士点基金资助项目(20110095110010);江苏省自然科学基金资助项目(BK20130208)。

Online compression of global positioning system trajectory data based on motion state change

LIU Leijun, FANG Cheng, ZHANG Lei, BAO Suning   

  1. College of Computer Science and Technology, China University of Mining and Technology, Xuzhou Jiangsu 221116, China
  • Received:2015-07-01 Revised:2015-09-13 Online:2016-01-10 Published:2016-01-09
  • Supported by:
    This work is partially supported by the Fundamental Research Funds for the Central Universities (2014XT04), the Research Fund for the Doctoral Program of Higher Education of China (20110095110010) and the Natural Science Foundation of Jiangsu Province (BK20130208).

摘要: 针对基于偏移量计算的轨迹数据压缩算法中对于关键点的评估不足以及基于在线轨迹数据压缩算法中累积误差和对偏移量考虑不足的问题,提出一种基于运动状态改变的在线全球定位系统(GPS)轨迹数据压缩算法——限定同步欧氏距离(SED)的阈值结合算法(SLTA)。该算法通过轨迹点的转向角度大小和速度变化大小来评估轨迹点信息量的大小;同时用SED限制点的偏移量,以达到较好的信息保留度。实验结果表明,SLTA的轨迹压缩率能够达到50%左右,与阈值结合算法(TA)相比,SLTA的平均SED误差(5 m以内)可以忽略不计;相对于基于偏移量计算的轨迹数据压缩算法,SLTA的平均角度误差最小(1.5°~2.3°),运行时间最稳定。SLTA能够稳定有效地进行在线GPS轨迹数据压缩。

关键词: 全球定位系统, 轨迹数据压缩, 同步欧氏距离, 阈值结合算法, 运动状态

Abstract: Concerning the insufficient consideration of the cumulative error and offset which online Global Positioning System (GPS) trajectory data compression based on motion state change and the insufficient key point evaluation of online GPS trajectory data compression based on the offset calculation, an online compression of GPS trajectory data based on motion state change, named Synchronous Euclidean Distance (SED) Limited Thresholds Algorithm (SLTA), was proposed. This algorithm used steering angle and speed change to evaluate information of trajectory point. At the same time, SLTA introduced the SED to limit offset of trajectory point. So SLTA could reach better information retention. The experimental results show that the trajectory compression ratio can reach about 50%. Compared with Thresholds Algorithm (TA), the average SED error (less than 5 m) of SLTA can be negligible. For other trajectory data compression algorithms, SLTA's average angel error is the lowest (1.5°-2.3°) and run time is the most stable. SLTA can stably and effectively do online GPS trajectory data compression.

Key words: Global Positioning System (GPS), trajectory data compression, Synchronous Euclidean Distance (SED), Thresholds Algorithm (TA), motion state

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