基于指纹膜与航迹推算的井下人员定位系统

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基于指纹膜与航迹推算的井下人员定位系统

马京, 胡青松, 宋泊明, 张申

文章导航 > 工矿自动化 > 2016 > 42(5): 19-23

马京，胡青松，宋泊明，等.基于指纹膜与航迹推算的井下人员定位系统［J］.工矿自动化，2016,42(5)：19-23.. doi: 10.13272/j.issn.1671-251x.2016.05.005

引用本文:

马京，胡青松，宋泊明，等.基于指纹膜与航迹推算的井下人员定位系统［J］.工矿自动化，2016,42(5)：19-23.. doi: 10.13272/j.issn.1671-251x.2016.05.005

MA Jing, HU Qingsong, SONG Boming, et al. Underground personnel positioning system based on fingerprint and dead-reckoning[J]. Industry and Mine Automation, 2016, 42(5): 19-23. doi: 10.13272/j.issn.1671-251x.2016.05.005

Citation:

MA Jing, HU Qingsong, SONG Boming, et al. Underground personnel positioning system based on fingerprint and dead-reckoning[J]. Industry and Mine Automation, 2016, 42(5): 19-23. doi: 10.13272/j.issn.1671-251x.2016.05.005

马京，胡青松，宋泊明，等.基于指纹膜与航迹推算的井下人员定位系统［J］.工矿自动化，2016,42(5)：19-23.. doi: 10.13272/j.issn.1671-251x.2016.05.005

引用本文:

马京，胡青松，宋泊明，等.基于指纹膜与航迹推算的井下人员定位系统［J］.工矿自动化，2016,42(5)：19-23.. doi: 10.13272/j.issn.1671-251x.2016.05.005

MA Jing, HU Qingsong, SONG Boming, et al. Underground personnel positioning system based on fingerprint and dead-reckoning[J]. Industry and Mine Automation, 2016, 42(5): 19-23. doi: 10.13272/j.issn.1671-251x.2016.05.005

Citation:

MA Jing, HU Qingsong, SONG Boming, et al. Underground personnel positioning system based on fingerprint and dead-reckoning[J]. Industry and Mine Automation, 2016, 42(5): 19-23. doi: 10.13272/j.issn.1671-251x.2016.05.005

基于指纹膜与航迹推算的井下人员定位系统

doi: 10.13272/j.issn.1671-251x.2016.05.005

马京^{1, 2},
胡青松^{2, 3},
宋泊明^{1, 2},
张申^{2, 3}

1.
中国矿业大学信息与电气工程学院，江苏徐州221008
2.
中国矿业大学物联网（感知矿山）研究中心，江苏徐州221008
3.
矿山互联网应用技术国家地方联合工程实验室，江苏徐州221008

基金项目:

国家自然科学基金项目(51204177)

江苏省自然科学基金项目(BK20151148)

中央高校基本科研业务费专项基金项目（2015XKMS097）

中图分类号: TD655.3
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出版历程
- 刊出日期: 2016-05-10

Underground personnel positioning system based on fingerprint and dead-reckoning

MA Jing^{1, 2},
HU Qingsong^{2, 3},
SONG Boming^{1, 2},
ZHANG Shen^{2, 3}

1.
School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221008, China
2.
IoT Perception Mine Research Center, China University of Mining and Technology, X

摘要: 针对RSSI指纹膜定位方法受矿井环境影响较大，而基于航迹推算的定位方法易形成误差累积的问题，设计了基于指纹膜与航迹推算的井下人员定位系统。该系统周期性采集人员的位置信息与运动姿态信息，利用K近邻和峰值检测方法求解指纹定位结果和航迹推算结果，并对定位结果进行加权融合得到目标位置。测试结果表明，该系统明显提高了定位精度和稳定性，对煤矿巷道复杂环境具有较强的适应能力。
- 井下人员定位 /
- 指纹膜 /
- 航迹推算 /
- 融合算法
Abstract: In view of problem that RSSI-based fingerprint positioning method is greatly influenced by environment of coal mine tunnel, and localization method based on dead-reckoning is easy to form accumulation of errors, underground personnel positioning system based on fingerprint and dead-reckoning was designed. The system periodically collects location and attitude information, uses KNN and peak detection method to solve result of fingerprint and dead-reckoning, and the target position was obtained by weighted fusion of the two positioning results. The test results demonstrate that the system can obviously improve positioning accuracy and stability, and has strong adaptability to the complex environment of coal mine tunnel.
- underground personnel positioning /
- fingerprint /
- dead-reckoning /
- fusion algorithm

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