Parametric identification of the error model for the aircraft inertial navigation system

{"title":"Parametric identification of the error model for the aircraft inertial navigation system","authors":"","doi":"10.36652/0869-4931-2021-75-7-317-321","DOIUrl":null,"url":null,"abstract":"The problem of increasing the accuracy at estimating the inertial navigation systems errors by using identifying the parameters of the model is investigated. A scheme for correcting navigation systems with an estimation algorithm is presented. The accuracy of the errors estimation for the inertial navigation system by using the nonstationary adaptive Kalman filter when the average frequency of the gyroscope random drift changes is determined. A simple method for parametric identification of the change average frequency of a random drift by using a tuning coefficient is proposed. The results analysis of the estimation algorithm modeling by using the data of laboratory experiments with the serial navigation system Ts-060K is carried out. In the models of the estimation algorithm different average frequency values of the random drift change are used.\n\nKeywords\naircraft; inertial navigation system; estimation algorithm; parametric identification; average frequency of random gyroscope drift; tuning factor; estimation accuracy","PeriodicalId":309803,"journal":{"name":"Automation. Modern Techologies","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automation. Modern Techologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36652/0869-4931-2021-75-7-317-321","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The problem of increasing the accuracy at estimating the inertial navigation systems errors by using identifying the parameters of the model is investigated. A scheme for correcting navigation systems with an estimation algorithm is presented. The accuracy of the errors estimation for the inertial navigation system by using the nonstationary adaptive Kalman filter when the average frequency of the gyroscope random drift changes is determined. A simple method for parametric identification of the change average frequency of a random drift by using a tuning coefficient is proposed. The results analysis of the estimation algorithm modeling by using the data of laboratory experiments with the serial navigation system Ts-060K is carried out. In the models of the estimation algorithm different average frequency values of the random drift change are used. Keywords aircraft; inertial navigation system; estimation algorithm; parametric identification; average frequency of random gyroscope drift; tuning factor; estimation accuracy
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
飞机惯性导航系统误差模型的参数辨识
研究了利用模型参数辨识来提高惯性导航系统误差估计精度的问题。提出了一种用估计算法校正导航系统的方案。确定了陀螺仪随机漂移平均频率变化时,用非平稳自适应卡尔曼滤波估计惯性导航系统误差的精度。提出了一种利用调谐系数对随机漂移变化平均频率进行参数辨识的简单方法。利用Ts-060K串行导航系统的实验室实验数据,对估计算法的建模结果进行了分析。在估计算法的模型中,使用了随机漂移变化的不同平均频率值。关键词:飞机;惯性导航系统;估计算法;参数识别;随机陀螺漂移的平均频率;调整因素;估计的准确性
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
Magnetoelectric sensor for non-destructive testing Landing system for MUAV on a mobile base by using short-range radio beacons Improving the tracking quality of the weld seam butt with V-form grooving by using Kalman filter and neural network Automation the assembly process of a passenger car gearbox Compensation method of the satellite navigation system reflected signals
×
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