测绘学报 ›› 2017, Vol. 46 ›› Issue (8): 1034-1046.doi: 10.11947/j.AGCS.2017.20160469

• 地图学与地理信息 • 上一篇    下一篇

粗精匹配结合的矢量道路辅助惯性导航算法

李翔1,2, 华一新1, 张宏1, 张江水1   

  1. 1. 信息工程大学地理空间信息学院, 河南 郑州 450001;
    2. 地理信息工程国家重点实验室, 陕西 西安 710000
  • 收稿日期:2016-09-21 修回日期:2017-07-01 出版日期:2017-08-20 发布日期:2017-09-01
  • 作者简介:李翔(1987-),男,博士,研究方向为GIS辅助定位技术。E-mail:ryolx13@126.com
  • 基金资助:
    国家自然科学基金(41271450;41471336);国家科技支撑计划(2012BAK12B02);地理信息工程国家重点实验室开放基金课题(SKLGIE2015-M-4-4);国家重点研发计划(2016YFB0502300)

Positioning Correction Algorithm of Vector Road Aided Inertial Navigation Based on the Rough/Fine Matching Method

LI Xiang1,2, HUA Yixin1, ZHANG Hong1, ZHANG Jiangshui1   

  1. 1. Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China;
    2. State Key Laboratory of Geo-information Engineering, Xi'an 710000, China
  • Received:2016-09-21 Revised:2017-07-01 Online:2017-08-20 Published:2017-09-01
  • Supported by:
    The National Natural Science Foundation of China (Nos.41271450;41471336);The National Science and Technology Supporting Program (No. 2012BAK12B02);The Key Laboratory of Geo-information Engineering Fund(No.SKLGIE2015-M-4-4);The National Key Research and Development Plan(No.2016YFB0502300)

摘要: 针对无源环境下无法采用卫星导航定位方式对惯性导航系统的累积误差进行修正的问题,提出一种采用高精度的矢量道路数据进行粗精匹配的导航校正算法。该方法首先通过分析惯导轨迹的特征标示点以及外接矩形,剔除明显的误匹配道路和冗余道路,获取待匹配道路集合;进而,结合ICCP算法具有匹配精度较高,匹配结果较稳定的优点,完成惯导轨迹位置误差的补偿和校正;最后,根据匹配方差和历史匹配轨迹对匹配结果的准确性进行分析和判断。仿真实验结果表明,该算法能够提高惯性导航定位误差的校正精度,减少在复杂道路交叉口等情况的误匹配。

关键词: 粗精匹配, 矢量道路, 轨迹特征, 特征标示点, ICCP算法

Abstract: In the passive environment, accumulated positioning errors of the inertial navigation system (INS) could not be corrected by satellite navigation and positioning, a rough/fine matching method based on high-precision road data was proposed to adjust the vehicle trajectory data acquired by INS. Firstly, by analyzing the feature label point and its minimum bounding rectangle in inertial trajectory, the obvious error matching road and redundant road could be eliminated and the candidate matching road sets could be captured. Then, with the advantages of high precision and stable matching result, the ICCP algorithm was built to compensate and correct the positioning errors caused by INS. Finally, the matching variance and history matching results could be used to judge whether the matching results were correct. Simulation results illustrated that this method could improve the correction accuracy and reduce the false matching results in the complex road intersections.

Key words: rough/fine matching, vector road, trajectory feature, the feature label point, ICCP algorithm

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