Main > Chinese Journal of Lasers >  Volume 47 >  Issue 12 >  Page 1206001 > Article
  • Abstract
  • Abstract
  • View Summary
  • Figures (11)
  • Tables (3)
  • Equations (0)
  • References (15)
  • Get PDF(in Chinese)
  • Paper Information
  • Received: Jun. 4, 2020

    Accepted: --

    Posted: Dec. 1, 2020

    Published Online: Nov. 26, 2020

    The Author Email: Yong Chen (chenyong@cqupt.edu.cn)

    DOI: 10.3788/CJL202047.1206001

  • Get Citation
  • Copy Citation Text

    Chen Yong, Wu Jie, Liu Huanlin, Zheng Han. Visible Light and Inertial Navigation Fusion Indoor Positioning System Based on Hidden Markov Model[J]. Chinese Journal of Lasers, 2020, 47(12): 1206001

    Download Citation

  • Category
  • Fiber optics and optical communication
  • Share
Chinese Journal of Lasers, Vol. 47, Issue 12, 1206001 (2020)

Visible Light and Inertial Navigation Fusion Indoor Positioning System Based on Hidden Markov Model

Yong Chen1,*, Jie Wu1, Huanlin Liu2, and Han Zheng1

Author Affiliations

  • 1Key Laboratory of Industrial Internet of Things & Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • 2Key Laboratory of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Abstract

Aiming at the problems of high mobile positioning complexity, low positioning accuracy, and unreasonable positioning for users in large indoor places, a visible light and inertial navigation fusion positioning algorithm based on the hidden Markov model is proposed in this work. First, the indoor parking lot map and positioning fingerprint in the off-line database construction stage are established, the visible light receiving signal strength of each reference node and the distance and angle between the nodes are collected, and a hidden Markov model is established. Then, in the online positioning stage, the candidate set of state transfer is reduced according to the user''s maximum moving speed, and the visible light signal and motion information are obtained. Finally, an improved Viterbi algorithm is used for user trajectory matching and positioning. Simulation results show that the proposed algorithm can accurately predict the user''s trajectory in an indoor parking lot of 2500m 2, the prediction accuracy of the reference node is about 85%, and the average positioning error is about 3.35 m. Compared with other four positioning algorithms, the positioning trajectory of the proposed algorithm is more continuous and smooth with higher accuracy.

keywords

Please Enter Your Email: