• Optical Communication Technology
  • Vol. 48, Issue 2, 1 (2022)
ZHAO Li, LIU Haitao*, and CHEN Junbo
Author Affiliations
  • [in Chinese]
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    DOI: 10.13921/j.cnki.issn1002-5561.2022.02.001 Cite this Article
    ZHAO Li, LIU Haitao*, CHEN Junbo. Indoor visible light location method based on neural network optimized by beetle antennae search algorithm[J]. Optical Communication Technology, 2022, 48(2): 1 Copy Citation Text show less

    Abstract

    Aiming at the problems of slow training speed and weak generalization ability which leads to low positioning accuracy in visible light indoor positioning technology based on neural network, a visible light positioning method based on beetle antennae search(BAS) algorithm is proposed to optimize neural network. A measured model of 0.8 m×0.8 m×0.8 m is built. In this method, the connection weight matrix of the neural network is optimized by using the BAS algorithm and the indoor wireless channel parameters are fitted to achieve indoor location. The simulation results show that the average positioning error of the simulation method is less than 3.42 cm, which is 40% higher than the neural network training speed. In the experiment, the average error measured in the plane of height h=0.25 m is less than 4.0 cm.
    ZHAO Li, LIU Haitao*, CHEN Junbo. Indoor visible light location method based on neural network optimized by beetle antennae search algorithm[J]. Optical Communication Technology, 2022, 48(2): 1
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