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Research on improved indoor positioning algorithm based on WiFi–pedestrian dead reckoning

Author

Listed:
  • Guanghua Zhang
  • Xue Sun
  • Jingqiu Ren
  • Weidang Lu

Abstract

In order to improve the positioning accuracy and reduce the impact of indoor complex environment on WiFi positioning results, an improved fusion positioning algorithm based on WiFi–pedestrian dead reckoning is proposed. The algorithm uses extended Kalman filter as the fusion positioning filter of WiFi–pedestrian dead reckoning. Aiming at the problem of WiFi signal strength fluctuation, Bayesian estimation matching algorithm based on K -nearest neighbor is proposed to reduce the impact of the dramatic change of received signal strength indicator value on the positioning result effectively. For the cumulative error problem in pedestrian dead reckoning positioning algorithm, a post-correction module is used to reduce the error. The experimental results show that the algorithm can improve the shortcomings of these two algorithms and control the positioning accuracy within 1.68 m.

Suggested Citation

  • Guanghua Zhang & Xue Sun & Jingqiu Ren & Weidang Lu, 2019. "Research on improved indoor positioning algorithm based on WiFi–pedestrian dead reckoning," International Journal of Distributed Sensor Networks, , vol. 15(5), pages 15501477198, May.
    • Handle: RePEc:sae:intdis:v:15:y:2019:i:5:p:1550147719851932
    DOI: 10.1177/1550147719851932
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