An Indoor Pedestrian Localization Algorithm Based on Multi-Sensor Information Fusion - Journal of Computer and Communications

JCC > Vol.5 No.3, March 2017

Journal of Computer and Communications

Volume 5, Issue 3 (March 2017)

ISSN Print: 2327-5219 ISSN Online: 2327-5227

Google-based Impact Factor: 1.12 Citations

An Indoor Pedestrian Localization Algorithm Based on Multi-Sensor Information Fusion ()

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Download as PDF (Size: 814KB) PP. 102-115

DOI: 10.4236/jcc.2017.53012 1,281 Downloads 2,489 Views Citations

Author(s)

Xiangyu Xu^1,2, Mei Wang^1,2, Liyan Luo^1,2, Zhibin Meng^1,2, Enliang Wang^1,2

Affiliation(s)

¹Key Laboratory of Cognitive Radio & Information Processing, Ministry of Education, Guilin University of Electronic Technology, Guilin, China.
²Guangxi Experiment Center of Information Science, Guilin, China.

ABSTRACT

For existing indoor localization algorithm has low accuracy, high cost in deployment and maintenance, lack of robustness, and low sensor utilization, this paper proposes a particle filter algorithm based on multi-sensor fusion. The pedestrian’s localization in indoor environment is described as dynamic system state estimation problem. The algorithm combines the smart mobile terminal with indoor localization, and filters the result of localization with the particle filter. In this paper, a dynamic interval particle filter algorithm based on pedestrian dead reckoning (PDR) information and RSSI localization information have been used to improve the filtering precision and the stability. Moreover, the localization results will be uploaded to the server in time, and the location fingerprint database will be built incrementally, which can adapt the dynamic changes of the indoor environment. Experimental results show that the algorithm based on multi-sensor improves the localization accuracy and robustness compared with the location algorithm based on Wi-Fi.

KEYWORDS

Multi-Sensor Fusion, Indoor Localization, Pedestrian Dead Reckoning (PDR), Particle Filter

Share and Cite:

Xu, X. , Wang, M. , Luo, L. , Meng, Z. and Wang, E. (2017) An Indoor Pedestrian Localization Algorithm Based on Multi-Sensor Information Fusion. Journal of Computer and Communications, 5, 102-115. doi: 10.4236/jcc.2017.53012.

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