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基于UWB的井下人员定位算法研究

贺磊 魏明生 仇欣宇 唐守锋 李文帅 张旭

贺磊,魏明生,仇欣宇,等. 基于UWB的井下人员定位算法研究[J]. 工矿自动化,2022,48(6):134-138.  doi: 10.13272/j.issn.1671-251x.2022020035
引用本文: 贺磊,魏明生,仇欣宇,等. 基于UWB的井下人员定位算法研究[J]. 工矿自动化,2022,48(6):134-138.  doi: 10.13272/j.issn.1671-251x.2022020035
HE Lei, WEI Mingsheng, QIU Xinyu, et al. Research on positioning algorithm of underground personnel based on UWB[J]. Journal of Mine Automation,2022,48(6):134-138.  doi: 10.13272/j.issn.1671-251x.2022020035
Citation: HE Lei, WEI Mingsheng, QIU Xinyu, et al. Research on positioning algorithm of underground personnel based on UWB[J]. Journal of Mine Automation,2022,48(6):134-138.  doi: 10.13272/j.issn.1671-251x.2022020035

基于UWB的井下人员定位算法研究

doi: 10.13272/j.issn.1671-251x.2022020035
基金项目: 国家重点研发计划项目(2017YFF0205500);江苏省研究生科研与实践创新计划项目(SJCX20_0908,SJCX21_1134)。
详细信息
    作者简介:

    贺磊(1994—),男,江苏徐州人,硕士研究生,主要研究方向为室内定位系统,E-mail:786429282@qq.com

    通讯作者:

    魏明生(1976—),男,山东济宁人,副教授,博士,主要从事传感器检测方面的研究工作,E-mail:weims516@163.com

  • 中图分类号: TD655.3

Research on positioning algorithm of underground personnel based on UWB

  • 摘要: 针对井下高实时性、高精度的人员定位需求,研究了基于超宽带(UWB)的井下人员定位算法。采用双边双向测距(DS−TWR)方式测量定位基站与定位标签的距离,该方式不需要定位基站与定位标签系统时钟同步,从源头上提高了定位精度。根据测距信息,采用加权最小二乘(WLS)算法和CHAN两种位置解算算法估算定位标签的坐标,通过静态实验和动态实验对2种算法的性能进行对比分析,并通过均方根误差和误差累计分布函数(CDF)综合评估定位精度。实验结果表明:静态实验时,CHAN算法和WLS算法的均方根误差分别为5.878 6,8.007 4 cm,CHAN算法的均方根误差比WLS算法低26.59%;动态实验时,CHAN算法和WLS算法的均方根误差分别为12.292 3,21.180 9 cm,CHAN算法的均方根误差比WLS算法低41.97%;CHAN算法的定位精度高于WLS算法,更加适用于煤矿井下人员定位。

     

  • 图  1  矿井DS−TWR测距模型

    Figure  1.  Mine DS-TWR ranging model

    图  2  实验环境与自制定位设备

    Figure  2.  Experimental environment and self-made positioning equipment

    图  3  CHAN与WLS算法定位结果(静态实验)

    Figure  3.  Positioning results of CHAN and WLS algorithms (static experiment)

    图  4  CHAN与WLS算法误差对比(静态实验)

    Figure  4.  Comparison of errors between CHAN and WLS algorithms(static experiment)

    图  5  CHAN与WLS算法的误差CDF曲线(静态实验)

    Figure  5.  Error CDF curves of CHAN and WLS algorithms (static experiment)

    图  6  CHAN与WLS算法定位结果(动态实验)

    Figure  6.  Positioning results of CHAN and WLS algorithms (dynamic experiment)

    图  7  CHAN与WLS算法误差对比(动态实验)

    Figure  7.  Comparison of errors between CHAN and WLS algorithms(dynamic experiment)

    图  8  CHAN与WLS算法的误差CDF曲线(动态实验)

    Figure  8.  Error CDF curves of CHAN and WLS algorithms (dynamic experiment)

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出版历程
  • 收稿日期:  2022-02-20
  • 修回日期:  2022-06-05
  • 网络出版日期:  2022-04-06

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