Ranging Based Wireless Positioning with Accurate Estimation of Bias Errors

M. Khalaf-Allah, O. Michler
{"title":"Ranging Based Wireless Positioning with Accurate Estimation of Bias Errors","authors":"M. Khalaf-Allah, O. Michler","doi":"10.23919/ENC48637.2020.9317404","DOIUrl":null,"url":null,"abstract":"In this paper, the problem of positioning a tag/receiver using range measurements is addressed. The performance of two linear least-squares estimators in terms of positioning accuracy is considered. To further improve the accuracy, we propose two measures in order to remove measurement noise and outliers, and to reduce measurement bias errors. Noise and outliers are removed by applying a recursive average filter to the measurements. Thus, the remaining errors are mainly systematic, i.e. bias errors. A direct positioning method is then developed to enable estimating the average measurement bias. These two procedures have a positive impact on the positioning accuracy as is demonstrated by the experiment. Filtering has reduced maximum errors by at least 25%. Bias reduction further decreased the mean and maximum errors by at least 66% and 42% respectively.","PeriodicalId":157951,"journal":{"name":"2020 European Navigation Conference (ENC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 European Navigation Conference (ENC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ENC48637.2020.9317404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In this paper, the problem of positioning a tag/receiver using range measurements is addressed. The performance of two linear least-squares estimators in terms of positioning accuracy is considered. To further improve the accuracy, we propose two measures in order to remove measurement noise and outliers, and to reduce measurement bias errors. Noise and outliers are removed by applying a recursive average filter to the measurements. Thus, the remaining errors are mainly systematic, i.e. bias errors. A direct positioning method is then developed to enable estimating the average measurement bias. These two procedures have a positive impact on the positioning accuracy as is demonstrated by the experiment. Filtering has reduced maximum errors by at least 25%. Bias reduction further decreased the mean and maximum errors by at least 66% and 42% respectively.
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
基于测距的无线定位与准确估计偏差
本文讨论了利用距离测量来定位标签/接收器的问题。考虑了两种线性最小二乘估计器在定位精度方面的性能。为了进一步提高测量精度,我们提出了两种方法来去除测量噪声和异常值,并减小测量偏差。通过对测量值应用递归平均滤波器来去除噪声和异常值。因此,剩余的误差主要是系统误差,即偏倚误差。然后开发了一种直接定位方法来估计平均测量偏差。实验结果表明,这两种方法对定位精度有积极的影响。过滤将最大误差降低了至少25%。减少偏置进一步使平均误差和最大误差分别降低至少66%和42%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Towards centimeter accurate positioning with smartphones Japanese GNSS Future System Evolution in the 2020–2030 Perspective High-Performance Pulsed Laser-Pumped Rb Clock for GNSS Evaluation of Network Real Time Kinematics contribution to the accuracy/productivity ratio for UAS-SfM Photogrammetry BIM-based simulation of intelligent transportation systems
×
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