Yanbei Coal Mine, Gansu Huating Coal Power Co., Ltd.
College of Electrical and Control Engineering, Xi'an University of Science and Technology

针对煤矿井下人员定位系统在实际应用中存在因设备算力与存储资源不足导致无法使用复杂测距与定位算法，定位数据即时传输与响应性能不足，在系统部署方面人力物力损耗较大等问题，提出了一种基于5G+UWB和惯导技术的井下人员定位系统。在末端部署能耗低、抗干扰性强的UWB定位基站，定位基站与5G基站以级联的方式连接，定位基站采集UWB与惯导数据，利用5G网络回传至计算平台，在计算平台上完成定位信息的解算和存储。将基于惯导的人员位置估计作为预测值，将基于UWB的三边定位算法获取的人员位置估计作为观测值，利用卡尔曼滤波器将预测值和观测值进行融合，降低定位误差。在煤矿主体实验基地搭建测试系统，模拟真实煤矿井下环境并进行对比实验。结果表明：① 在x轴和y轴，融合惯导的卡尔曼滤波算法得出的位置信息和真实位置信息的重合度最高，说明融合惯导的卡尔曼滤波算法得出的位置信息最接近真实位置,平均误差为22.192 cm。② 5G+UWB和惯导技术组合的井下人员定位系统的位置信息和真实位置信息的重合度最高，误差为[15 cm，20 cm]，x轴最大平均误差为26 cm，y轴最大平均误差为24 cm，超过目前大多数井下人员定位系统精度。

In practical applications of coal mine personnel positioning systems, there are problems of insufficient equipment computing power and storage resources. The problems result in preventing the use of complex ranging and positioning algorithms, inadequate real-time transmission and response performance of positioning data, and significant human and material resource losses in system deployment. In order to solve the above problems, a new underground personnel positioning system based on 5G+UWB and inertial navigation technology is proposed. The system deploys UWB positioning base stations with low energy consumption and strong anti-interference capability at the end. The positioning base station is connected to the 5G base station in a cascaded manner. The positioning base station collects UWB and inertial navigation data, and uses the 5G network to transmit it back to the computing platform. The positioning information is solved and stored on the computing platform. The inertial navigation based personnel position estimation is used as the predicted value. The UWB based trilateral positioning algorithm is used to obtain personnel position estimation as the observed value. The Kalman filter is used to fuse the predicted and observed values to reduce positioning errors. The testing system is built at the main experimental base of the coal mine, simulating the real underground environment of the coal mine, and conducting comparative experiments. The results show the following points. ①In the x-axis direction and the y-axis direction, the coincidence degree between the position information obtained by the Kalman filter algorithm of the fusion inertial navigation and the real position information is the highest, indicating that the position information obtained by the Kalman filter algorithm of the fusion inertial navigation is closest to the real position, and the average error is 22.192 cm. ② The position information of the underground personnel positioning system combined with 5G + UWB and inertial navigation technology has the highest coincidence degree with the real position information, and the error is [15 cm, 20 cm], with a maximum average error of 26 cm on the x-axis and 24 cm on the y-axis, exceeding the precision of most current underground personnel positioning systems.

陕西省秦创原“科学家+工程师”队伍建设项目（2022KXJ-38）；西安市科技计划资助项目（23ZDCYJSGG0025-2022）；中国华能集团有限公司总部科技项目（HNKJ21-HF13）；天地科技股份有限公司科技创新创业资金专项重点项目（2023-TD-ZD005-004） 。

李明锋，李䶮，刘用，等. 基于5G+UWB和惯导技术的井下人员定位系统[J]. 工矿自动化，2024，50（1）：25-34.

LI Mingfeng, LI Yan, LIU Yong, et al. Underground personnel positioning system based on 5G+UWB and inertial navigation technology[J]. Journal of Mine Automation，2024，50（1）：25-34.