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金属矿山 ›› 2025, Vol. 54 ›› Issue (6): 161-167.

• 机电与自动化 • 上一篇    下一篇

结合 5G 技术和 Chan-Taylor 算法的井下人员定位研究

陈宏昌1   梁业生2   黄孝平3    

  1. 1. 广西农业工程职业技术学院机电工程学院,广西 南宁 530028;2. 广西农业职业技术大学城乡建设学院,广西 南宁 530007; 3. 桂林理工大学南宁分校电气与电子工程学院,广西 崇左 532100
  • 出版日期:2025-06-15 发布日期:2025-07-09
  • 通讯作者: 黄孝平(1973—),男,教授,硕士。
  • 作者简介:陈宏昌(1966—),男,副教授。
  • 基金资助:
    2023 年度广西职业教育教学改革研究项目( 编号:GXGZJG2023B091);2024 年度广西职业教育教学改革研究项目( 编号:GXGZJG2024A021)。 

Research on Underground Personnel Positioning Based on 5G Technique and Chan-Taylor Algorithm 

CHEN Hongchang 1   LIANG Yesheng 2   HUANG Xiaoping   

  1. 1. School of Mechanical and Electrical Engineering,Guangxi Agricultural Engineering Vocational Technical College,Nanning 530028,China;2. School of Urban and Rural Construction,Guangxi Vocational University of Agriculture,Nanning 530007,China; 3. School of Electrical and Electronic Engineering,Guilin University of Technology at Nanning,Chongzuo 532100,China
  • Online:2025-06-15 Published:2025-07-09

摘要: 矿井环境复杂多变,存在非视距(Non-Line-of-Sight,NLOS)误差传播等诸多干扰因素,传统定位方法难 以满足高精度定位需求,严重影响了井下安全生产与管理。 将 5G 技术与 Chan-Taylor 算法相结合,提出了一种矿井人 员定位新方法。 首先,对于无 NLOS 误差的数据,通过改进 Chan-Taylor 定位算法,结合残差加权策略,提高定位的准 确性和稳定性;其次,针对 NLOS 误差的影响,提出了融合 Chan 算法与粒子滤波的定位算法,有效处理非线性定位问 题,进一步提升定位精度;最后,以某矿井为例,对所提方法进行了试验。 结果表明:改进 Chan-Taylor 定位算法在单目 标和双目标仿真定位中,相较于传统算法具有更高的定位准确性和稳定性。 融合 Chan 算法与粒子滤波的定位算法在 不同轨迹及 NLOS 误差条件下,平均误差小于对比算法,定位精度更高。 结合 5G 的井下人员定位模型精度较高,误差 为 0. 2 ~ 0. 9 m,能有效满足矿井智能化建设对井下人员定位精确度与稳定性的需求。 

关键词: 井下定位,   非视距误差 , 5G 技术 , Chan-Taylor 算法

Abstract: The mine environment is complex and variable,with various interference factors such as non-line-of-sight (NLOS) propagation. Traditional positioning methods are difficult to meet the requirements for high-precision positioning and have seriously affected underground safety production and management. By combining 5G technique with the Chan-Taylor algorithm,a new method for mine personnel positioning is proposed. Firstly,for data without NLOS errors,the Chan-Taylor positioning algorithm is improved and combined with the residual weighting strategy to enhance the accuracy and stability of positioning. Secondly,for the influence of NLOS errors,a positioning algorithm integrating the Chan algorithm and particle filtering is proposed,which effectively handles the nonlinear positioning problem and further improves the positioning accuracy. Finally, taking a certain mine as an example,the proposed method was tested. The results show that the improved Chan-Taylor positioning algorithm has higher positioning accuracy and stability in single-target and dual-target simulation positioning compared to traditional algorithms. The positioning algorithm integrating the Chan algorithm and particle filtering has an average error smaller than the comparison algorithm under different trajectories and NLOS error conditions,and has higher positioning accuracy. The positioning model combining 5G technique for underground personnel positioning has a higher accuracy of 0. 2 ~ 0. 9 m, which can effectively meet the requirements of underground personnel positioning accuracy and stability for the intelligent construction of mines. 

Key words: underground positioning,non-line-of-sight error,5G technique,Chan-Taylor algorithm 

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