Wang, Z., Xing, L., Xiong, Z., Ding, Y., Sun, Y. and Shi, C. (2022) An Improved Pedestrian Navigation Method Based on the Combination of Indoor Map Assistance and Adaptive Particle Filter. Remote Sensing, 14, Article No. 6282.
https://doi.org/10.3390/rs14246282

has been cited by the following article:

• TITLE: An Improved Particle Filter Map Matching Algorithm for Personal Inertial Positioning

  AUTHORS: Xiaolong Zhang, Tao Zhou, Jing Wang, Tao Wang, Hui Zhao

  KEYWORDS: Personal Positioning, Inertial Navigation, Dead Reckoning, Map Matching, Particle Filtering

  JOURNAL NAME: Journal of Computer and Communications, Vol.11 No.6, June 30, 2023

  ABSTRACT: The current particle filtering map matching algorithm has problems such as low map utilization and poor accuracy of turnoff positioning, etc. This paper proposed an improved particle filtering-based map-matching algorithm for the inertial positioning of personnel. The historical moment position constraint and feasible region constraint of particles were introduced in this paper. A resampling method based on multi-stage backtracking of particles was proposed. Therefore, the effectiveness of newly generated particles could be guaranteed. The utilization rate of map information could be improved, thus enhancing the accuracy of personnel localization. The walking experiment results showed that, compared with the traditional PDR algorithm, the proposed method had higher localization accuracy and better repeatability of the localization trajectory for multi-turn paths. Under the total travel of 480 meters, the deviation of the starting end point was less than 2 meters, which was about 0.4% of the total travel.