@inproceedings{0839e243a57f4d08a0b9311687d314a1,
title = "Map Matching Algorithm Based on Trajectory Feature Identification",
abstract = "Inertial navigation system (INS) plays a dominant role in the field of navigation of land vehicles of military use for its rich information and autonomy. However, a well-known fact is that INS error accumulates over time. Map Matching technology is an effective way of solving the error accumulation problem of INS with the help of digital map while maintaining the autonomy property. One key problem of Map Matching is how to make good use of map information to fully correct the INS error. Typical Map Matching correction methods simply project the INS position on the Matched road, which can hardly eliminate the position error along the road direction. In this paper, a Map-Matching algorithm based on Light Barrier Method local feature correction is designed to better identify the featured road points and compensate accumulated position error along the road direction without greatly increase the load of computation. The feasibility and accuracy of the matching method are verified through actual automobile experiment. Test results show that this method can effectively reduce the positioning error of long-term inertial navigation system.",
keywords = "INS, Light Barrier Method, Map-Matching, Pearson Correlation",
author = "Yongqiang Han and Dunhui Zhao and Xingang Zhang and Jianhua Xu and Tian Xiaochun",
note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",
year = "2021",
month = jul,
day = "26",
doi = "10.23919/CCC52363.2021.9550121",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "3657--3661",
editor = "Chen Peng and Jian Sun",
booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",
address = "United States",
}