NEPS: “Narrowband Efficient Positioning System” for delivering resource efficient GNSS receivers

Ido Nevat, Ory Eger, G. Peters, F. Septier
{"title":"NEPS: “Narrowband Efficient Positioning System” for delivering resource efficient GNSS receivers","authors":"Ido Nevat, Ory Eger, G. Peters, F. Septier","doi":"10.1109/ISSNIP.2014.6827605","DOIUrl":null,"url":null,"abstract":"We present a new architecture to perform localization (position estimation) in GNSS systems, termed NEPS (Narrowband Efficient Positioning System). The NEPS architecture is composed of three components: a low powered cheap receiver; a communication system which transmits the measurements; and a processing unit which receives the distorted observations (due to quantisation and imperfect transmission medium) and performs the position estimation algorithm. The NEPS is a stand-alone system which is designed to incorporate the quantised measurements as well as the imperfect communication channels between receiver and the backend in order to perform inference on the user's position. Compared with a conventional system, the NEPS consumes less bandwidth, requires lower power consumption and provides faster reporting rates. We derive the joint Maximum Likelihood (ML) for the position and the receiver's clock offset. We then develop an efficient algorithm to solve the resulting non-convex oinferenceptimisation problem. Furthermore, we derive a theoretical performance lower bound on the achievable accuracy via Cramér-Rao lower bound (CRLB). Simulation results show that the performance of the NEPS ML position estimator is close to the theoretical performance bound.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSNIP.2014.6827605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

We present a new architecture to perform localization (position estimation) in GNSS systems, termed NEPS (Narrowband Efficient Positioning System). The NEPS architecture is composed of three components: a low powered cheap receiver; a communication system which transmits the measurements; and a processing unit which receives the distorted observations (due to quantisation and imperfect transmission medium) and performs the position estimation algorithm. The NEPS is a stand-alone system which is designed to incorporate the quantised measurements as well as the imperfect communication channels between receiver and the backend in order to perform inference on the user's position. Compared with a conventional system, the NEPS consumes less bandwidth, requires lower power consumption and provides faster reporting rates. We derive the joint Maximum Likelihood (ML) for the position and the receiver's clock offset. We then develop an efficient algorithm to solve the resulting non-convex oinferenceptimisation problem. Furthermore, we derive a theoretical performance lower bound on the achievable accuracy via Cramér-Rao lower bound (CRLB). Simulation results show that the performance of the NEPS ML position estimator is close to the theoretical performance bound.
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
NEPS:窄带高效定位系统,用于提供资源高效的GNSS接收器
我们提出了一种在GNSS系统中执行定位(位置估计)的新架构,称为NEPS(窄带高效定位系统)。NEPS架构由三个部分组成:低功耗廉价接收器;传送测量值的通信系统;以及接收失真观测值(由于量化和传输介质不完善)并执行位置估计算法的处理单元。NEPS是一个独立的系统,旨在结合量化测量以及接收器和后端之间不完善的通信通道,以便对用户的位置进行推断。与传统系统相比,NEPS的带宽消耗更少,功耗更低,上报速率更快。我们导出了位置和接收机时钟偏移的联合最大似然(ML)。然后,我们开发了一个有效的算法来解决由此产生的非凸交互优化问题。在此基础上,通过cram r- rao下界(CRLB)推导出了可实现精度的理论性能下界。仿真结果表明,NEPS ML位置估计器的性能接近理论性能界。
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
Wireless sensors networks for Internet of Things Efficient sequential-hierarchical deployment strategy for heterogeneous sensor networks Development of silicon photonics dual disks resonators as chemical sensors An efficient power control scheme for a 2.4GHz class-E PA in 0.13-μm CMOS Action recognition from motion capture data using Meta-Cognitive RBF Network classifier
×
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