基于MEMS传感器的矿山井下救灾人员定位系统设计与应用研究

Yue Zhao, Jianyong Wang, Chengyong Duan
{"title":"基于MEMS传感器的矿山井下救灾人员定位系统设计与应用研究","authors":"Yue Zhao, Jianyong Wang, Chengyong Duan","doi":"10.1117/12.2639253","DOIUrl":null,"url":null,"abstract":"In order to solve the problem of low positioning accuracy of disaster relief personnel and rescue efficiency when a disaster occurs in a coal mine, this paper proposes a disaster relief personnel positioning system for coal mine based on Micro-Electro-Mechanical System (MEMS) sensor. The proposed system uses the MPU9150 inertial sensor to obtain measurement data and the CC2530 microprocessor as the main control chip for data acquisition and processing. In the proposed system, the Pedestrian Dead Reckoning (PDR) algorithm is used to determine the step size based on the fusion expression between the walking frequency variance and acceleration, and the quaternion method is used to estimate pedestrian orientation angle. In order to reduce the error caused by the drift of the accelerometer and gyroscope, the extended Kalman filter is employed to correct the original data. The experimental results show that the positioning error of the proposed system is less than 1.6 m in 100 m. Thus, the proposed method can achieve high accuracy in the disaster relief personnel positioning in an underground coal mine.","PeriodicalId":336892,"journal":{"name":"Neural Networks, Information and Communication Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Design and application research of mine underground disaster relief personnel positioning system based on MEMS sensor\",\"authors\":\"Yue Zhao, Jianyong Wang, Chengyong Duan\",\"doi\":\"10.1117/12.2639253\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the problem of low positioning accuracy of disaster relief personnel and rescue efficiency when a disaster occurs in a coal mine, this paper proposes a disaster relief personnel positioning system for coal mine based on Micro-Electro-Mechanical System (MEMS) sensor. The proposed system uses the MPU9150 inertial sensor to obtain measurement data and the CC2530 microprocessor as the main control chip for data acquisition and processing. In the proposed system, the Pedestrian Dead Reckoning (PDR) algorithm is used to determine the step size based on the fusion expression between the walking frequency variance and acceleration, and the quaternion method is used to estimate pedestrian orientation angle. In order to reduce the error caused by the drift of the accelerometer and gyroscope, the extended Kalman filter is employed to correct the original data. The experimental results show that the positioning error of the proposed system is less than 1.6 m in 100 m. Thus, the proposed method can achieve high accuracy in the disaster relief personnel positioning in an underground coal mine.\",\"PeriodicalId\":336892,\"journal\":{\"name\":\"Neural Networks, Information and Communication Engineering\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Networks, Information and Communication Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2639253\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Networks, Information and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2639253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

为了解决煤矿发生灾害时救灾人员定位精度低、救援效率低等问题,本文提出了一种基于微机电系统(MEMS)传感器的煤矿救灾人员定位系统。该系统采用MPU9150惯性传感器获取测量数据,CC2530微处理器作为主控芯片进行数据采集和处理。在该系统中,基于步行频率方差与加速度的融合表达式,采用行人航迹推算(PDR)算法确定步长,采用四元数法估计行人方向角。为了减小加速度计和陀螺仪漂移带来的误差,采用扩展卡尔曼滤波对原始数据进行校正。实验结果表明,该系统在100 m内的定位误差小于1.6 m。因此,该方法在煤矿井下救灾人员定位中具有较高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and application research of mine underground disaster relief personnel positioning system based on MEMS sensor
In order to solve the problem of low positioning accuracy of disaster relief personnel and rescue efficiency when a disaster occurs in a coal mine, this paper proposes a disaster relief personnel positioning system for coal mine based on Micro-Electro-Mechanical System (MEMS) sensor. The proposed system uses the MPU9150 inertial sensor to obtain measurement data and the CC2530 microprocessor as the main control chip for data acquisition and processing. In the proposed system, the Pedestrian Dead Reckoning (PDR) algorithm is used to determine the step size based on the fusion expression between the walking frequency variance and acceleration, and the quaternion method is used to estimate pedestrian orientation angle. In order to reduce the error caused by the drift of the accelerometer and gyroscope, the extended Kalman filter is employed to correct the original data. The experimental results show that the positioning error of the proposed system is less than 1.6 m in 100 m. Thus, the proposed method can achieve high accuracy in the disaster relief personnel positioning in an underground coal mine.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信