基于足部UWB/IMU传感器融合的无基础设施室内行人跟踪

Zhuoqi Zeng, Steven Liu, Wei Wang, Lei Wang
{"title":"基于足部UWB/IMU传感器融合的无基础设施室内行人跟踪","authors":"Zhuoqi Zeng, Steven Liu, Wei Wang, Lei Wang","doi":"10.1109/ICSPCS.2017.8270492","DOIUrl":null,"url":null,"abstract":"Accurate indoor human localization without requiring any pre-installed infrastructure is essential for many applications, such as search and rescue in fire disaster areas or human social interaction. Ultra-wideband (UWB) is a very promising technology for accurate indoor positioning with pre-installed receivers. An infrastructure-free methodology, called Pedestrian Dead-Reckoning (PDR), which uses an inertial measurement unit (IMU), can also be used for position estimation. In this approach, the drift errors of IMU in each step length estimation are compensated based on zero-velocity update (ZUPT), zero angular rate update (ZARU) and heuristic heading drift reduction (HDR) algorithms. An accurate step detection can be achieved by relying on the data provided by accelerometers and gyroscopes. In order to further improve the accuracy, a novel approach, which combines IMU PDR and UWB ranging measurements by Extended Kalman filter (EKF) without any pre-installed infrastructure, is proposed. All the components in this approach, the IMU, the mobile station (MS) and the receiver of the UWB are mounted on the feet. The biases in the IMU measurements, which cause inaccurate step length estimation, can be compensated by range measurements provided by UWB. The performance of the normal PDR with EKF is evaluated as comparison to the proposed approach. The real test results show that the proposed approach with EKF is the most effective way to reduce the error.","PeriodicalId":268205,"journal":{"name":"2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Infrastructure-free indoor pedestrian tracking based on foot mounted UWB/IMU sensor fusion\",\"authors\":\"Zhuoqi Zeng, Steven Liu, Wei Wang, Lei Wang\",\"doi\":\"10.1109/ICSPCS.2017.8270492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Accurate indoor human localization without requiring any pre-installed infrastructure is essential for many applications, such as search and rescue in fire disaster areas or human social interaction. Ultra-wideband (UWB) is a very promising technology for accurate indoor positioning with pre-installed receivers. An infrastructure-free methodology, called Pedestrian Dead-Reckoning (PDR), which uses an inertial measurement unit (IMU), can also be used for position estimation. In this approach, the drift errors of IMU in each step length estimation are compensated based on zero-velocity update (ZUPT), zero angular rate update (ZARU) and heuristic heading drift reduction (HDR) algorithms. An accurate step detection can be achieved by relying on the data provided by accelerometers and gyroscopes. In order to further improve the accuracy, a novel approach, which combines IMU PDR and UWB ranging measurements by Extended Kalman filter (EKF) without any pre-installed infrastructure, is proposed. All the components in this approach, the IMU, the mobile station (MS) and the receiver of the UWB are mounted on the feet. The biases in the IMU measurements, which cause inaccurate step length estimation, can be compensated by range measurements provided by UWB. The performance of the normal PDR with EKF is evaluated as comparison to the proposed approach. The real test results show that the proposed approach with EKF is the most effective way to reduce the error.\",\"PeriodicalId\":268205,\"journal\":{\"name\":\"2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPCS.2017.8270492\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPCS.2017.8270492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

在不需要任何预先安装的基础设施的情况下,准确的室内人员定位对于许多应用至关重要,例如火灾灾区的搜索和救援或人类社会互动。超宽带(UWB)是一种非常有前途的技术,用于预先安装接收器的精确室内定位。一种无需基础设施的方法,称为行人航位推算(PDR),它使用惯性测量单元(IMU),也可用于位置估计。该方法基于零速度更新(ZUPT)、零角速度更新(ZARU)和启发式航向漂移减小(HDR)算法对IMU在各步长估计中的漂移误差进行补偿。依靠加速度计和陀螺仪提供的数据,可以实现精确的步长检测。为了进一步提高测量精度,提出了一种结合IMU PDR和UWB测距的扩展卡尔曼滤波(EKF)方法,该方法无需任何预装基础设施。这种方法中的所有组件,IMU,移动站(MS)和UWB接收器都安装在脚上。IMU测量中的偏差导致步长估计不准确,可以通过超宽带提供的距离测量来补偿。将带EKF的普通PDR的性能与所提出的方法进行比较。实际测试结果表明,结合EKF的方法是减小误差的最有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Infrastructure-free indoor pedestrian tracking based on foot mounted UWB/IMU sensor fusion
Accurate indoor human localization without requiring any pre-installed infrastructure is essential for many applications, such as search and rescue in fire disaster areas or human social interaction. Ultra-wideband (UWB) is a very promising technology for accurate indoor positioning with pre-installed receivers. An infrastructure-free methodology, called Pedestrian Dead-Reckoning (PDR), which uses an inertial measurement unit (IMU), can also be used for position estimation. In this approach, the drift errors of IMU in each step length estimation are compensated based on zero-velocity update (ZUPT), zero angular rate update (ZARU) and heuristic heading drift reduction (HDR) algorithms. An accurate step detection can be achieved by relying on the data provided by accelerometers and gyroscopes. In order to further improve the accuracy, a novel approach, which combines IMU PDR and UWB ranging measurements by Extended Kalman filter (EKF) without any pre-installed infrastructure, is proposed. All the components in this approach, the IMU, the mobile station (MS) and the receiver of the UWB are mounted on the feet. The biases in the IMU measurements, which cause inaccurate step length estimation, can be compensated by range measurements provided by UWB. The performance of the normal PDR with EKF is evaluated as comparison to the proposed approach. The real test results show that the proposed approach with EKF is the most effective way to reduce the error.
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
期刊最新文献
Frequency offset tolerant demodulation for low data rate and narrowband wireless sensor node Multi-channel speech enhancement in driving environment Dual window selective median switching filter SAR video generation of MIMO video SAR with beat frequency division FMCW Receiver cooperative MIMO-OFDM capacity with quantization error and spatial correlation
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1