A self-adaptive unscented Kalman filtering for underwater gravity aided navigation

Lin Wu, Jie Ma, J. Tian
{"title":"A self-adaptive unscented Kalman filtering for underwater gravity aided navigation","authors":"Lin Wu, Jie Ma, J. Tian","doi":"10.1109/PLANS.2010.5507294","DOIUrl":null,"url":null,"abstract":"In this paper, a self-adaptive unscented Kalman filtering for underwater gravity aided navigation is constructed. It is more accurate and far easier to implement than an extended Kalman filter. Then the novel navigation algorithm based on the self-adaptive unscented Kalman filter is explored. With this method submerged position fixes for autonomous underwater vehicle can be obtained from comparing gravity fields' measurements with gravity maps. Specifically, simulation results show that navigation errors can be reduced more effectively and efficiently by the presented algorithm.","PeriodicalId":94036,"journal":{"name":"IEEE/ION Position Location and Navigation Symposium : [proceedings]. IEEE/ION Position Location and Navigation Symposium","volume":"59 1","pages":"142-145"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE/ION Position Location and Navigation Symposium : [proceedings]. IEEE/ION Position Location and Navigation Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PLANS.2010.5507294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

Abstract

In this paper, a self-adaptive unscented Kalman filtering for underwater gravity aided navigation is constructed. It is more accurate and far easier to implement than an extended Kalman filter. Then the novel navigation algorithm based on the self-adaptive unscented Kalman filter is explored. With this method submerged position fixes for autonomous underwater vehicle can be obtained from comparing gravity fields' measurements with gravity maps. Specifically, simulation results show that navigation errors can be reduced more effectively and efficiently by the presented algorithm.
水下重力辅助导航的自适应无气味卡尔曼滤波
本文构造了一种水下重力辅助导航的自适应无气味卡尔曼滤波。它比扩展卡尔曼滤波器更精确,更容易实现。然后研究了一种基于自适应无气味卡尔曼滤波的导航算法。利用该方法,可以通过将引力场测量值与重力图进行比较,得到自主水下航行器的水下位置定位。仿真结果表明,该算法能更有效地降低导航误差。
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:481959085
Book学术官方微信