室内可见光定位算法研究

doi:10.16039/j.cnki.cn22-1249.2022.01.011

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摘要

针对室内场所定位精度低的问题，本文提出一种基于改进粒子群算法的 RSSI（Received Signal Strength Indication：接收信号强度指示）可见光定位方法。采用莱维飞行算法对粒子群算法进行改进，解决了标准粒子群算法易陷入局部最优的问题，提高了算法的收敛速度和定位精度。在 5m×5m×3m 的室内环境下，经过仿真测试，本文改进后的粒子群算法结合 RSSI 定位方法定位精度可以达到0.038241m，算法稳定度上升，定位精度更高，更适合在室内定位中使用。

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	任永旺
	赵钢
	张慧颖

关键词: 可见光定位接收信号强度粒子群算法莱维飞行

Abstract:

Aiming at the problem of low positioning accuracy in indoor places, this paper proposes a RSSI (Received Signal Strength Indication) visible light positioning method based on improved particle swarm optimization algorithm. The Lévy flight algorithm is used to improve the particle swarm optimization algorithm, which solves the problem that the standard particle swarm optimization algorithm is easy to fall into the local optimum, and improves the convergence speed and positioning accuracy of the algorithm. In the indoor environment of 5m×5m×3m, after simulation test, the improved particle swarm optimization algorithm combined with RSSI positioning method can reach a positioning accuracy of 0.038241m, the algorithm stability is improved, the positioning accuracy is higher, and it is more suitable for indoor positioning.

Key words: Visible Light Localization Receiving Signal Strength Indication Particle Swarm Optimization Lévy Flight

出版日期: 2022-01-25 发布日期: 2022-01-25 整期出版日期: 2022-01-25

TP202

引用本文:

任永旺, 赵钢, 张慧颖. 室内可见光定位算法研究[J]. 吉林化工学院学报, 2022, 39(1): 63-67.
REN Yongwang, ZHAO Gang, ZHANG Huiying. Research on Indoor Visible Light Localization Algorithm . Journal of Jilin Institute of Chemical Technology, 2022, 39(1): 63-67.

链接本文:

https://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2022.01.011 或 https://xuebao.jlict.edu.cn/CN/Y2022/V39/I1/63

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