Paper Info
Title
Effect Evaluation of Spatial Characteristics on Map Matching-Based Indoor Positioning.
Abstract
Map-matching is a popular method that uses spatial information to improve the accuracy of positioning methods. The performance of map matching methods is closely related to spatial characteristics. Although several studies have demonstrated that certain map matching algorithms are affected by some spatial structures (e.g., parallel paths), they focus on the analysis of single map matching method or few spatial structures. In this study, we explored how the most commonly-used four spatial characteristics (namely forks, open spaces, corners, and narrow corridors) affect three popular map matching methods, namely particle filtering (PF), hidden Markov model (HMM), and geometric methods. We first provide a theoretical analysis on how spatial characteristics affect the performance of map matching methods, and then evaluate these effects through experiments. We found that corners and narrow corridors are helpful in improving the positioning accuracy, while forks and open spaces often lead to a larger positioning error. We hope that our findings are helpful for future researchers in choosing proper map matching algorithms with considering the spatial characteristics.
Year
DOI
Venue
2020
10.3390/s20226698
SENSORS
Keywords
DocType
Volume
map matching,indoor positioning,spatial information,particle filtering,hidden Markov model,geometric
Journal
20
Issue
ISSN
Citations 
22
1424-8220
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Shuaiwei Luo100.68
Fuqiang Gu2383.56
fan xu38420.78
Jianga Shang4335.04