Underground Personnel Positioning Method Based on Self-training and NLOS Suppression
[Purposes] The research of precise location of underground personnel in coal mine is of great significance to protect their life safety. The ultra-wideband signal is susceptible to non-lineof- sight (NLOS) interference, which will seriously affects the positioning accuracy. [Methods] In order to sol...
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Editorial Office of Journal of Taiyuan University of Technology
2024-11-01
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| Series: | Taiyuan Ligong Daxue xuebao |
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| Online Access: | https://tyutjournal.tyut.edu.cn/englishpaper/show-2353.html |
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| author | SHAO Xiaoqiang HAN Zehui MA Bo YANG Yongde YUAN Zewen LI Xin |
| author_facet | SHAO Xiaoqiang HAN Zehui MA Bo YANG Yongde YUAN Zewen LI Xin |
| author_sort | SHAO Xiaoqiang |
| collection | DOAJ |
| description | [Purposes] The research of precise location of underground personnel in coal mine is of great significance to protect their life safety. The ultra-wideband signal is susceptible to non-lineof- sight (NLOS) interference, which will seriously affects the positioning accuracy. [Methods] In order to solve the problem that the existing supervised learning methods for NLOS identification and suppression require long time, labor intensive feature, and high cost became of the needs to obtain training data and label allocation, a method for underground personnel positioning based on self-training and suppression of NLOS is proposed, and a new general data fusion framework is designed. First, PDR and map information are combined to remove infeasible positions, and multi-granularity mesh filters are used to estimate the position and heading, and the map information is fully utilized to generate weak labels. Second, through multi-sensor data fusion, the weak label is iteratively improved, and training samples are generated to realize autonomous collection of training data. Finally, the data of map, inertial sensor, and ultra-wideband measurement are fused by Bayesian estimation to infer the location. [Findings] Through the simulation tests in the downhole environment, the results show that for complex downhole scenes, the root-mean-square error of NLOS decreases from the original 1.02 to 0.32 m, the ranging error is improved by 69%, and the positioning result with the positioning error less than 0.3 m can be increased from 49% to 89%. Thus, the effectiveness of the proposed method for locating underground personnel is proved. |
| format | Article |
| id | doaj-art-1d132eeb5d6e43bfb58feaef0cbfdedd |
| institution | OA Journals |
| issn | 1007-9432 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Editorial Office of Journal of Taiyuan University of Technology |
| record_format | Article |
| series | Taiyuan Ligong Daxue xuebao |
| spelling | doaj-art-1d132eeb5d6e43bfb58feaef0cbfdedd2025-08-20T02:06:58ZengEditorial Office of Journal of Taiyuan University of TechnologyTaiyuan Ligong Daxue xuebao1007-94322024-11-015561053106210.16355/j.tyut.1007-9432.202307511007-9432(2024)06-1053-10Underground Personnel Positioning Method Based on Self-training and NLOS SuppressionSHAO Xiaoqiang0HAN Zehui1MA Bo2YANG Yongde3YUAN Zewen4LI Xin5College of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, China[Purposes] The research of precise location of underground personnel in coal mine is of great significance to protect their life safety. The ultra-wideband signal is susceptible to non-lineof- sight (NLOS) interference, which will seriously affects the positioning accuracy. [Methods] In order to solve the problem that the existing supervised learning methods for NLOS identification and suppression require long time, labor intensive feature, and high cost became of the needs to obtain training data and label allocation, a method for underground personnel positioning based on self-training and suppression of NLOS is proposed, and a new general data fusion framework is designed. First, PDR and map information are combined to remove infeasible positions, and multi-granularity mesh filters are used to estimate the position and heading, and the map information is fully utilized to generate weak labels. Second, through multi-sensor data fusion, the weak label is iteratively improved, and training samples are generated to realize autonomous collection of training data. Finally, the data of map, inertial sensor, and ultra-wideband measurement are fused by Bayesian estimation to infer the location. [Findings] Through the simulation tests in the downhole environment, the results show that for complex downhole scenes, the root-mean-square error of NLOS decreases from the original 1.02 to 0.32 m, the ranging error is improved by 69%, and the positioning result with the positioning error less than 0.3 m can be increased from 49% to 89%. Thus, the effectiveness of the proposed method for locating underground personnel is proved.https://tyutjournal.tyut.edu.cn/englishpaper/show-2353.htmlintelligent coal minepersonnel positioninguwbnlos mitigationself-training |
| spellingShingle | SHAO Xiaoqiang HAN Zehui MA Bo YANG Yongde YUAN Zewen LI Xin Underground Personnel Positioning Method Based on Self-training and NLOS Suppression Taiyuan Ligong Daxue xuebao intelligent coal mine personnel positioning uwb nlos mitigation self-training |
| title | Underground Personnel Positioning Method Based on Self-training and NLOS Suppression |
| title_full | Underground Personnel Positioning Method Based on Self-training and NLOS Suppression |
| title_fullStr | Underground Personnel Positioning Method Based on Self-training and NLOS Suppression |
| title_full_unstemmed | Underground Personnel Positioning Method Based on Self-training and NLOS Suppression |
| title_short | Underground Personnel Positioning Method Based on Self-training and NLOS Suppression |
| title_sort | underground personnel positioning method based on self training and nlos suppression |
| topic | intelligent coal mine personnel positioning uwb nlos mitigation self-training |
| url | https://tyutjournal.tyut.edu.cn/englishpaper/show-2353.html |
| work_keys_str_mv | AT shaoxiaoqiang undergroundpersonnelpositioningmethodbasedonselftrainingandnlossuppression AT hanzehui undergroundpersonnelpositioningmethodbasedonselftrainingandnlossuppression AT mabo undergroundpersonnelpositioningmethodbasedonselftrainingandnlossuppression AT yangyongde undergroundpersonnelpositioningmethodbasedonselftrainingandnlossuppression AT yuanzewen undergroundpersonnelpositioningmethodbasedonselftrainingandnlossuppression AT lixin undergroundpersonnelpositioningmethodbasedonselftrainingandnlossuppression |