Research on the Denoising of the Beidou Carrier Signal based on EEMD Algorithm with Adaptive Reconstruction Optimizing of IMF Numbers

Wei Li, Kai Zhang, Gang Lv, Guibao Xu, A. Xu
{"title":"Research on the Denoising of the Beidou Carrier Signal based on EEMD Algorithm with Adaptive Reconstruction Optimizing of IMF Numbers","authors":"Wei Li, Kai Zhang, Gang Lv, Guibao Xu, A. Xu","doi":"10.37394/232014.2020.16.17","DOIUrl":null,"url":null,"abstract":"The Beidou carrier signal is coupled into a certain noise during propagation and reception, and these noise will directly affect the processing procedure associated with it. To deal with the problem of the influence due to the manually setting the IMF (Intrinsic Mode Function) component number for the reconstruction signal, a new measuring index that used for finding the optimal IMF components to reconstruct the signal has been designed in this paper. The index has taken the shape of the signal, signal noise ratio and correlation index into consideration. Upon on the basis, an adaptive index optimization Ensemble Empirical Mode Decomposition (AIO-EEMD) algorithm has been proposed in this paper. To verify the validity of the algorithm, four different algorithms are used to denoised the collected Beidou signal. The experiment results show that the noise reduction using the AIO-EEMD method can not only automatically obtain the optimal IMF components number, but also has a significant advantage over the other three methods.","PeriodicalId":305800,"journal":{"name":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"WSEAS TRANSACTIONS ON SIGNAL PROCESSING","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37394/232014.2020.16.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The Beidou carrier signal is coupled into a certain noise during propagation and reception, and these noise will directly affect the processing procedure associated with it. To deal with the problem of the influence due to the manually setting the IMF (Intrinsic Mode Function) component number for the reconstruction signal, a new measuring index that used for finding the optimal IMF components to reconstruct the signal has been designed in this paper. The index has taken the shape of the signal, signal noise ratio and correlation index into consideration. Upon on the basis, an adaptive index optimization Ensemble Empirical Mode Decomposition (AIO-EEMD) algorithm has been proposed in this paper. To verify the validity of the algorithm, four different algorithms are used to denoised the collected Beidou signal. The experiment results show that the noise reduction using the AIO-EEMD method can not only automatically obtain the optimal IMF components number, but also has a significant advantage over the other three methods.
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
基于自适应重构优化IMF数的EEMD算法的北斗载波信号去噪研究
北斗载波信号在传播和接收过程中会耦合成一定的噪声,这些噪声会直接影响与之相关的处理过程。针对人为设置重建信号的IMF(本征模态函数)分量数所带来的影响,本文设计了一种新的测量指标,用于寻找重建信号的最优IMF分量。该指标综合考虑了信号的形状、信噪比和相关指标。在此基础上,提出了一种自适应指标优化集成经验模态分解(AIO-EEMD)算法。为了验证算法的有效性,采用四种不同的算法对采集到的北斗信号进行去噪。实验结果表明,采用AIO-EEMD方法进行降噪不仅可以自动获得最优的IMF分量数,而且比其他三种方法具有明显的优势。
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
Robust Recursive Least-Squares Fixed-Point Smoother and Filter using Covariance Information in Linear Continuous-Time Stochastic Systems with Uncertainties Driving Aid for Rotator Cuff Injured Patients using Hand Gesture Recognition CTM Tongue Image Consulting System based on Deep Learning Technology Robust Estimators for Missing Observations in Linear Discrete-Time Stochastic Systems with Uncertainties Pattern Wafer x/y Auto Align System using Machine Vision
×
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