A Study of WiFi-Aided Magnetic Matching Indoor Positioning Algorithm - 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

A Study of WiFi-Aided Magnetic Matching Indoor Positioning Algorithm ()

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Download as PDF (Size: 2331KB) PP. 91-101

DOI: 10.4236/jcc.2017.53011 1,442 Downloads 2,595 Views Citations

Author(s)

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

Aiming at the shortcomings of the existing indoor location algorithm, such as low accuracy of positioning, high deployment and maintenance cost, and unstable robustness, this paper proposes a method of indoor location based on the integration of smartphone with WiFi and magnetic field using multi-sensor fusion. In the initial stages of positioning, rough location is achieved by Wi-Fi-RSSI fingerprints which provides an initial location and geomagnetic matching area for indoor positioning based on particle filter magnetic field matching. This paper proposes the use of median filter algorithm to deal with the original magnetic field data and covariance interpolation algorithm to generate magnetic field map, and effectively reduce the interference which caused by geomagnetic fluctuations, thereby it will improves the positioning accuracy. Finally, through conducting comprehensive experiments and tests, the results show that the proposed technique can reliably achieve 0.836 meters precision in current experimental environment.

KEYWORDS

Indoor Positioning, Magnetic Field, Particle Filter, Smartphones

Share and Cite:

Wang, E. , Wang, M. , Meng, Z. and Xu, X. (2017) A Study of WiFi-Aided Magnetic Matching Indoor Positioning Algorithm. Journal of Computer and Communications, 5, 91-101. doi: 10.4236/jcc.2017.53011.

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