Currently, various indoor positioning technologies are widely studied, and visible light positioning (VLP) is a promising technology due to its high accuracy, low cost, and high output rate. However, the most common method based on the received signal strength (RSS) requires calibrating the model in advance, which has a weak generalization ability. This article focuses on the VLP method based on the time difference of arrival (TDOA), which does not require heavy preparatory work. First, we analyze the influence of different errors on TDOA-based VLP, such as the time synchronization error and receiver noise. Second, a convolution neural network (CNN)–based network is designed for phase difference estimation, which significantly improves the accuracy of phase difference estimation compared to the traditional in-phase and quadrature signal-based method. Finally, a particle filter based on the motion state is proposed to improve positioning accuracy and robustness. Simulated experiments evaluate the proposed methods, and the final results show a significant improvement in accuracy when compared with traditional methods. The improvements in ranging and localization accuracy can both reach over 50%.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Visible Light Positioning System Based on a Particle Filter and Deep Learning


    Contributors:


    Publication date :

    2024-06-01


    Size :

    7037642 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Indoor Positioning System Based on Visible Light Communications

    Avendano Lopez, Carlos Miguel / Ibarra-Manzano, Mario-Alberto / Castro-Sanchez, Rogelio et al. | IEEE | 2018


    Visible light positioning: Automotive use case

    Roberts, R / Gopalakrishnan, P / Rathi, S | IEEE | 2010


    VEHICLE POSITIONING BY VISIBLE LIGHT COMMUNICATION

    KRAPF ARNO | European Patent Office | 2017

    Free access

    Indoor Positioning System Using Visible Light and Accelerometer

    Yasir, M. / Ho, S. / Vellambi, B. N. | British Library Online Contents | 2014


    Visible Light Positioning Considering Multi-Path Reflections

    Li, Zhengpeng / Zhao, Lei / Jiang, Ming | IEEE | 2019