In-Motion Initial Alignment Method for LDV-Aided SINS Based on Robust Unscented Quaternion Filter

Zhiyi Xiang, Qi Wang, Jian Zhou
{"title":"In-Motion Initial Alignment Method for LDV-Aided SINS Based on Robust Unscented Quaternion Filter","authors":"Zhiyi Xiang, Qi Wang, Jian Zhou","doi":"10.1145/3501409.3501456","DOIUrl":null,"url":null,"abstract":"With the advantages of high velocity measurement accuracy, good spatial resolution and fast dynamic response, the laser Doppler velocimeter (LDV) is expected to replace the odometer and Doppler Velocity Log to be combined with a strapdown inertial navigation system (SINS) to form a higher precision integrated navigation system. Currently, in-motion initial alignment of SINS is still a challenge. In this paper, the high precision velocity provided by LDV to aid SINS in-motion alignment. Considering that some approximation used in the alignment model and the unknown noise parameters during the filter process, an unscented quaternion H-infinite estimator (USQUHE) is proposed in this paper. Because USQUHE combines the advantages of H-infinite filter and unscented quaternion estimator, USQUHE has satisfactory robustness when processing nonlinear models. The performance of the proposed method is verified by a vehicle field test. The results show that the proposed method has higher alignment accuracy, faster convergence speed and stronger robustness than other compared methods.","PeriodicalId":191106,"journal":{"name":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","volume":"75 7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 5th International Conference on Electronic Information Technology and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3501409.3501456","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

With the advantages of high velocity measurement accuracy, good spatial resolution and fast dynamic response, the laser Doppler velocimeter (LDV) is expected to replace the odometer and Doppler Velocity Log to be combined with a strapdown inertial navigation system (SINS) to form a higher precision integrated navigation system. Currently, in-motion initial alignment of SINS is still a challenge. In this paper, the high precision velocity provided by LDV to aid SINS in-motion alignment. Considering that some approximation used in the alignment model and the unknown noise parameters during the filter process, an unscented quaternion H-infinite estimator (USQUHE) is proposed in this paper. Because USQUHE combines the advantages of H-infinite filter and unscented quaternion estimator, USQUHE has satisfactory robustness when processing nonlinear models. The performance of the proposed method is verified by a vehicle field test. The results show that the proposed method has higher alignment accuracy, faster convergence speed and stronger robustness than other compared methods.
基于鲁棒无嗅四元数滤波的ldv辅助SINS运动初始对准方法
激光多普勒测速仪(LDV)具有测速精度高、空间分辨率好、动态响应快等优点,有望取代里程计和多普勒测速仪与捷联惯导系统(SINS)结合,形成更高精度的组合导航系统。目前,捷联惯导系统的运动初始对准仍然是一个挑战。本文利用LDV提供的高精度速度辅助捷联惯导系统运动对准。考虑到对准模型中使用了一些近似,以及滤波过程中存在未知的噪声参数,本文提出了一种无气味四元数h无限估计器。由于USQUHE结合了h -∞滤波和无气味四元数估计的优点,在处理非线性模型时,USQUHE具有令人满意的鲁棒性。通过车辆现场试验验证了该方法的有效性。结果表明,该方法具有较高的对准精度、较快的收敛速度和较强的鲁棒性。
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 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