非视距条件下移动站定位的Kriging估计

J.Y. Huang, Z.X. Chen, Q. Wan, W.L. Yang
{"title":"非视距条件下移动站定位的Kriging估计","authors":"J.Y. Huang, Z.X. Chen, Q. Wan, W.L. Yang","doi":"10.1109/ICCCAS.2007.6250846","DOIUrl":null,"url":null,"abstract":"Estimation of mobile station location is made difficult by nonsymmetric contamination of measured data caused by NLOS propagation effects. In this paper, a novel algorithm based on kriging method is proposed to reduce the effects of NLOS propagation on the location error. Simulation results show that the proposed algorithm clearly outperforms two other algorithms (non-parametric kernel method and parametric least square method) and comes close to meeting Cramer Rao lower bound (CRLB).","PeriodicalId":218351,"journal":{"name":"2007 International Conference on Communications, Circuits and Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Kriging estimator for mobile station positioning under non-line-of-sight (NLOS) conditions\",\"authors\":\"J.Y. Huang, Z.X. Chen, Q. Wan, W.L. Yang\",\"doi\":\"10.1109/ICCCAS.2007.6250846\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Estimation of mobile station location is made difficult by nonsymmetric contamination of measured data caused by NLOS propagation effects. In this paper, a novel algorithm based on kriging method is proposed to reduce the effects of NLOS propagation on the location error. Simulation results show that the proposed algorithm clearly outperforms two other algorithms (non-parametric kernel method and parametric least square method) and comes close to meeting Cramer Rao lower bound (CRLB).\",\"PeriodicalId\":218351,\"journal\":{\"name\":\"2007 International Conference on Communications, Circuits and Systems\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-07-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Communications, Circuits and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCAS.2007.6250846\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Communications, Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCAS.2007.6250846","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

由于NLOS的传播效应造成测量数据的不对称污染,使得移动站的位置估计变得困难。本文提出了一种基于kriging方法的新算法,以减小非近距离los传播对定位误差的影响。仿真结果表明,该算法明显优于其他两种算法(非参数核方法和参数最小二乘法),接近满足Cramer Rao下界(CRLB)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kriging estimator for mobile station positioning under non-line-of-sight (NLOS) conditions
Estimation of mobile station location is made difficult by nonsymmetric contamination of measured data caused by NLOS propagation effects. In this paper, a novel algorithm based on kriging method is proposed to reduce the effects of NLOS propagation on the location error. Simulation results show that the proposed algorithm clearly outperforms two other algorithms (non-parametric kernel method and parametric least square method) and comes close to meeting Cramer Rao lower bound (CRLB).
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