Wavelet-Based Method for Fog Signal Denoising

Yue Zu, Jinchu Cao
{"title":"Wavelet-Based Method for Fog Signal Denoising","authors":"Yue Zu, Jinchu Cao","doi":"10.12720/JOACE.1.2.86-90","DOIUrl":null,"url":null,"abstract":"Fiber-Optic Gyroscope (FOG) has been widely used to measure the angle rate of vehicle in recent years. Being as unpredictable and unmeasured error, random drift generated from FOG instability create seriously bad influence on precision of FOG output, as well as Inertial Navigation System (INS). Although wavelet-based technique has made considerable progress in FOG signal denoising, almost all the achievements are based on off-line analysis that gives little contribution to practical application. This paper presents a revised plan on account of previous research on real time denoising, explaining the computational complexity reduction from theory. Through simulation and static FOG experiment using time-frequency analysis and Allan Variance as the performance evaluation standard, the denoising effectiveness compared to using traditional method has been proofed improving to a large extent. ","PeriodicalId":239044,"journal":{"name":"Journal of Automation and Control Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Automation and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12720/JOACE.1.2.86-90","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

Fiber-Optic Gyroscope (FOG) has been widely used to measure the angle rate of vehicle in recent years. Being as unpredictable and unmeasured error, random drift generated from FOG instability create seriously bad influence on precision of FOG output, as well as Inertial Navigation System (INS). Although wavelet-based technique has made considerable progress in FOG signal denoising, almost all the achievements are based on off-line analysis that gives little contribution to practical application. This paper presents a revised plan on account of previous research on real time denoising, explaining the computational complexity reduction from theory. Through simulation and static FOG experiment using time-frequency analysis and Allan Variance as the performance evaluation standard, the denoising effectiveness compared to using traditional method has been proofed improving to a large extent. 
基于小波的雾信号去噪方法
近年来,光纤陀螺仪被广泛用于测量车辆的角速度。光纤陀螺不稳定产生的随机漂移是一种不可预测、不可测量的误差,对光纤陀螺输出精度和惯性导航系统精度造成严重影响。尽管基于小波的技术在雾场信号去噪方面取得了长足的进步,但几乎所有的成果都是基于离线分析,对实际应用贡献不大。本文在借鉴前人实时去噪研究的基础上,提出了一种改进方案,从理论上阐述了降低计算复杂度的方法。通过以时频分析和Allan方差作为性能评价标准的仿真和静态FOG实验,证明了该方法的去噪效果较传统方法有较大提高。
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 求助全文
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:604180095
Book学术官方微信
小红书