• Chinese Journal of Lasers
  • Vol. 47, Issue 12, 1206001 (2020)
Chen Yong1、*, Wu Jie1, Liu Huanlin2, and Zheng Han1
Author Affiliations
  • 1Key Laboratory of Industrial Internet of Things & Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • 2Key Laboratory of Optical Fiber Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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    DOI: 10.3788/CJL202047.1206001 Cite this Article Set citation alerts
    Chen Yong, Wu Jie, Liu Huanlin, Zheng Han. Visible Light and Inertial Navigation Fusion Indoor Positioning System Based on Hidden Markov Model[J]. Chinese Journal of Lasers, 2020, 47(12): 1206001 Copy Citation Text show less
    Indoor positioning fingerprint map
    Fig. 1. Indoor positioning fingerprint map
    Diagram of HMM
    Fig. 2. Diagram of HMM
    Diagram of candidate set of user maximum speed limit
    Fig. 3. Diagram of candidate set of user maximum speed limit
    Schematic diagrams of Viterbi algorithm based on user maximum speed. (a) Traditional Viterbi algorithm; (b) improved Viterbi algorithm
    Fig. 4. Schematic diagrams of Viterbi algorithm based on user maximum speed. (a) Traditional Viterbi algorithm; (b) improved Viterbi algorithm
    Flow chart of fusion positioning algorithm
    Fig. 5. Flow chart of fusion positioning algorithm
    Fingerprint map of indoor parking lot
    Fig. 6. Fingerprint map of indoor parking lot
    Experimental trajectory of indoor parking lot
    Fig. 7. Experimental trajectory of indoor parking lot
    Cumulative error distribution function
    Fig. 8. Cumulative error distribution function
    Positioning track maps of four contrast algorithms. (a) Kalman filter based VLC and PDR fusion location trajectory map; (b) visible light fingerprint positioning trajectory; (c) traditional HMM VLC positioning trajectory; (d) inertial navigation positioning trajectory
    Fig. 9. Positioning track maps of four contrast algorithms. (a) Kalman filter based VLC and PDR fusion location trajectory map; (b) visible light fingerprint positioning trajectory; (c) traditional HMM VLC positioning trajectory; (d) inertial navigation positioning trajectory
    CDF of positioning error of compared algorithms
    Fig. 10. CDF of positioning error of compared algorithms
    Location error graph corresponding to different numbers of candidate nodes
    Fig. 11. Location error graph corresponding to different numbers of candidate nodes
    SymbolParameterValue
    SRoom size /m22500
    HPDReceiving height /m1
    HLEDLED height /m4
    NLedNumber of LEDs in each lamp26
    PPtTransmitted power of lamp /W5-10
    TTs(Ψ)Gain of optical filter1
    gΨGain of optical concentrator1
    FFOVField-of-view /(°)55
    APhysical area of photo-detector /cm21
    NnodesNumber of nodes162
    VmaxMaximum speed /(m·s-1)5
    Table 1. Simulation parameters
    Number of experimentsForecast numberof nodesAccuracy of nodeprediction /%Maximumerror /mMinimumerror /mAverageerror /mRoot meansquare error /m
    103000825.10.63.854.42
    206000855.40.33.473.95
    309000845.50.23.564.17
    Table 2. Positioning error statistics
    PositioningmethodMaximumerror /mMinimumerror /mAverageerror /mRoot meansquare error /mMedianerror /m
    VLCFM[9]7.30.104.615.104.22
    VLC-HMM7.40.305.526.135.04
    INPM[10]9.60.056.627.145.56
    KF VLC-IN[11]6.50.604.274.853.74
    Proposed method5.50.203.353.882.92
    Table 3. Positioning error statistics of compared algorithms
    Chen Yong, Wu Jie, Liu Huanlin, Zheng Han. Visible Light and Inertial Navigation Fusion Indoor Positioning System Based on Hidden Markov Model[J]. Chinese Journal of Lasers, 2020, 47(12): 1206001
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