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. DOI: 10.13272/j.issn.1671-251x.2023100066
Citation: 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. DOI: 10.13272/j.issn.1671-251x.2023100066

Underground personnel positioning system based on 5G+UWB and inertial navigation technology

  • 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.
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