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基于UWB的矿井下人员协同定位算法

王磊1, 张文博1, 于金霞1, 贺军义1, 袁瑞甫2, 高岩2

1.河南理工大学 计算机学院， 河南 焦作  454000；2.河南理工大学 能源科学与工程学院， 河南 焦作  454000

摘要: 目的 针对矿井下定位盲区、工作面人员定位精度不足以及非视距（non-line-of-sight，NLOS）误差等问题，提出一种基于超宽带（ultra-wideband，UWB）技术的矿井人员协同定位算法，旨在显著提升定位精度，优化基站部署方案，并为矿井安全管理提供高效、可靠的技术支持。  方法 首先，算法利用矿井人员携带的移动节点作为中继节点，构建协同定位机制，通过信号中继有效降低UWB基站在井下工作面的部署密度和通信半径要求。这种设计不仅适应复杂巷道环境，减少定位盲区，还可显著提升信号覆盖范围，克服空间狭窄和基站布设受限的挑战。其次，为解决NLOS误差对定位精度的影响，算法采用两阶段误差消减策略：通过高斯模型对NLOS误差进行初步建模与校正，有效削弱由墙体、设备等障碍物引起的信号传播偏差；结合网格筛选策略，通过划分网格并剔除异常值，进一步提高定位数据的可靠性。最后，算法引入一种改进的麻雀搜索算法，通过自适应步长和动态权重机制优化全局寻优过程，显著提升收敛速度和定位精度。 结果 仿真结果表明，所提算法平均定位精度达到0.19 m，相较于同类型效果较优的相关算法具有更高的精度和稳定性，且在基站数量较少时仍能保持优异性能，计算效率满足实时需求。  结论 所提算法有效解决了井下定位的技术难题，为矿井人员的安全监控提供了高效、精准的解决方案，具有重要的理论和应用价值。

关键词:超宽带;人员辅助协同定位;通信半径;网格筛选;改进麻雀算法

doi:10.16186/j.cnki.1673-9787.2022020009

基金项目:国家自然科学基金资助项目（52174109）；河南省科技攻关项目（212102210092）

收稿日期:2022/02/08

修回日期:2022/09/05

出版日期:2025/10/14

Mine personnel cooperative location algorithm based on ultra-wideband

Wang Lei1, Zhang Wenbo1, Yu Jinxia1, He Junyi1, Yuan Ruifu2, Gao Yan2

1.School of Computer Science and Technology， Henan Polytechnic University， Jiaozuo  454000， Henan， China；2.School of Energy Science and Engineering， Henan Polytechnic University， Jiaozuo  454000， Henan， China

Abstract: Objectives To address the issues of positioning blind zones， low localization accuracy for personnel at the working face， and non-line-of-sight （NLOS） errors in underground mines， a cooperative localization algorithm based on ultra-wideband （UWB） technology was proposed. The algorithm was designed to significantly enhance positioning accuracy， optimize base station deployment， and provide efficient and reliable support for mine safety management. Methods Firstly， mobile nodes carried by mine personnel were utilized as relays to establish a cooperative localization mechanism， by which the distribution density and communication radius requirements of UWB base stations at the underground working face were effectively reduced. This design was adapted to complex tunnel environments， whereby positioning blind zones were mitigated and signal coverage was significantly improved， overcoming challenges posed by confined spaces and limited base station placement. Secondly， to address the impact of NLOS errors on positioning accuracy， a two-stage error mitigation strategy was employed： Initially， a Gaussian model was used to model and correct signal propagation distortions caused by obstacles such as walls or equipment； Subsequently， a grid screening strategy was applied to filter out residual outliers by dividing the data into grids， whereby the reliability of positioning data was further enhanced. Finally， an improved Sparrow Search Algorithm， incorporating adaptive step sizes and dynamic weighting mechanisms， was applied to optimize the screened results， by which convergence speed was significantly improved and high-precision positioning was achieved. Results Simulation results demonstrated that the proposed algorithm achieved an average localization accuracy of 0.19 meters， by which similar high-performing algorithms were surpassed in both precision and stability. Moreover， superior performance was maintained even with fewer base stations， while computational efficiency was satisfied for real-time underground positioning demands. Conclusions This UWB-based cooperative localization algorithm effectively resolved key technical challenges in mine positioning， by which a highly accurate and robust solution for personnel safety monitoring was offered with significant theoretical and practical values.

Key words: UWB; personnel assisted cooperative positioning; communication radius; mesh filter ;improved sparrow search algorithm