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

被引：0
|
作者：
Chen Y. [1 ]
Wu J. [1 ]
Liu H. [2 ]
Zheng H. [1 ]
机构：
[1] Key Laboratory of Industrial Internet of Things & Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing
[2] Key Laboratory of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing
来源：
Zhongguo Jiguang/Chinese Journal of Lasers | 2020年 / 47卷 / 12期
关键词：
Fusion positioning; Hidden Markov model; Inertial navigation; Optical communications; Viterbi algorithm;
D O I：
10.3788/CJL202047.1206001
中图分类号：
学科分类号：
摘要：
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 2500 m2, 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. © 2020, Chinese Lasers Press. All right reserved.
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