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
- 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
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.
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