Indoor Three-dimensional Positioning System Based on Visible Light Communication Using Improved Immune PSO Algorithm

Yong CHEN; Han ZHENG; Qixiang SHEN; Huanlin LIU

doi:10.11999/JEIT190936

Volume 43 Issue 1

Jan. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(1): 101-107

Yong CHEN, Han ZHENG, Qixiang SHEN, Huanlin LIU. Indoor Three-dimensional Positioning System Based on Visible Light Communication Using Improved Immune PSO Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(1): 101-107. doi: 10.11999/JEIT190936

Citation:

Yong CHEN, Han ZHENG, Qixiang SHEN, Huanlin LIU. Indoor Three-dimensional Positioning System Based on Visible Light Communication Using Improved Immune PSO Algorithm[J]. Journal of Electronics & Information Technology, 2021, 43(1): 101-107. doi: 10.11999/JEIT190936

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Indoor Three-dimensional Positioning System Based on Visible Light Communication Using Improved Immune PSO Algorithm

doi: 10.11999/JEIT190936

1.
Key Laboratory of Industrial Internet of Things & Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (51977021), The Chongqing Natural Science Foundation (cstc2019jcyj-msxmX0613)

Received Date: 2019-11-21
Rev Recd Date: 2020-06-10

Available Online: 2020-07-17

Publish Date: 2021-01-15

Abstract

Abstract

For the problem that the three-dimensional positioning accuracy is not high and the positioning time is too long in indoor Visible Light Communication(VLC). An indoor visible light three-dimensional positioning system based on Improved IMmune Particle Swarm Optimization(IIMPSO) algorithm is proposed. By analyzing the indoor multipath effects, the fitter Field Of View (FOV) is selected to reduce the influence of the reflection. Meanwhile, the positioning model under the tilt state is improved. The Kalman filter algorithm is used to reduce the impact of environmental interference on the received power. On the basis, it is integrated with the improved immune particle swarm algorithm. Simulation results show the average positioning error of the indoor three-dimensional positioning system is 0.031 m, and the positioning time is 2.3 s in the indoor of 5 m × 5 m × 3 m. Compared with the existing three-dimensional positioning system, the positioning accuracy and convergence speed are significantly improved.
- Visible Light Communication(VLC),
- Indoor three-dimensional positioning,
- Field Of View(FOV),
- Immune particle swarm algorithm

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References(19)

References

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