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Laser & Optoelectronics Progress, Volume. 61, Issue 4, 0428003(2024)

Co-Location Algorithm Based on Chan and Improved Sparrow Search Algorithm

Bishuai Chen1,2、*, Yanjie Wang1、**, Shengyao Jia1, Siyuan Hu2, and Peilin Gong3
Author Affiliations
  • 1College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, Zhejiang, China
  • 2Zhejiang Key Laboratory of Safety Engineering and Technology Research, Hangzhou 310012, Zhejiang, China
  • 3Suichang Hongchang Mining Development Co., Ltd., Lishui 323300, Zhejiang, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (12)
    Equations (26)
    References (19)
    Cited By (1)
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    Figures & Tables(12)
    Schematic diagram of TOA positioning model

    Fig. 1. Schematic diagram of TOA positioning model

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    SPM chaos map distribution chart

    Fig. 2. SPM chaos map distribution chart

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    Sparrow population after K-means clustering

    Fig. 3. Sparrow population after K-means clustering

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    Histogram of chaotic values

    Fig. 4. Histogram of chaotic values

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    Adaptive weight factor variation curve

    Fig. 5. Adaptive weight factor variation curve

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    Ablation experiment

    Fig. 6. Ablation experiment

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    Algorithm convergence diagram

    Fig. 7. Algorithm convergence diagram

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    Positioning ERMSE for different ranging noises

    Fig. 8. Positioning ERMSE for different ranging noises

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    Physical map of UWB positioning equipment

    Fig. 9. Physical map of UWB positioning equipment

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    Experimental site and plane two-dimensional map

    Fig. 10. Experimental site and plane two-dimensional map

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    • Table 1. Basic parameters of equipment

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      Table 1. Basic parameters of equipment

      Basic parameter
      STM32F103C8T6Operating voltage /V：2.0‒3.6
      Operating temperature /℃：-40‒105
      Clock frequency /MHz：72
      Memory capacity /kB：128
      DWM1000Operating voltage /V：2.8‒3.6 V
      Operating temperature /℃：-40‒8
      Data rate：110 kbit/s，6.8 Mbit/s
      Transmit power：-14 dBm/-10 dBm

    • Table 2. Experimental data and positioning results

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      Table 2. Experimental data and positioning results

      Test PointChanChan-TaylorChan-PSOChan-SSAChan-ISSA
      MeanRMSEMeanRMSEMeanRMSEMeanRMSEMeanRMSE
      T1（3.14，7.53）（3.088，7.607）0.0929（3.103，7.502）0.0464（3.095，7.562）0.0552（3.097，7.564）0.0548（3.108，7.557）0.0419
      T2（7.86，3.22）（7.920，3.154）0.0892（7.875，3.183）0.0399（7.819，3.186）0.0533（7.903，3.191）0.0519（7.887，3.194）0.0375
      T3（7.86，10.40）（8.177，9.971）0.5334（8.006，10.351）0.1540（8.012，10.223）0.2333（8.014，10.241）0.2214（7.960，10.362）0.1070
      T4（12.58，8.60）（13.061，9.635）1.1413（12.617，8.902）0.3043（12.961，9.379）0.8672（12.732，9.219）0.6374（12.603，8.812）0.2132
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    Bishuai Chen, Yanjie Wang, Shengyao Jia, Siyuan Hu, Peilin Gong. Co-Location Algorithm Based on Chan and Improved Sparrow Search Algorithm[J]. Laser & Optoelectronics Progress, 2024, 61(4): 0428003

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: May. 11, 2023

    Accepted: Jun. 1, 2023

    Published Online: Feb. 26, 2024

    The Author Email: Bishuai Chen (981624489@qq.com), Yanjie Wang (wangyanjie@163.com)

    DOI:10.3788/LOP231279

    CSTR:32186.14.LOP231279

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology