首页 | 本学科首页   官方微博 | 高级检索  
     

基于新息和残差的自适应UKF算法
引用本文:周卫东,乔相伟,吉宇人,孟凡彬. 基于新息和残差的自适应UKF算法[J]. 宇航学报, 2010, 31(7): 1798-1804. DOI: 10.3873/j.issn.1000-1328.2010.07.015
作者姓名:周卫东  乔相伟  吉宇人  孟凡彬
作者单位:(哈尔滨工程大学自动化学院,哈尔滨 150001)
摘    要:针对先验噪声统计特性与实际不符引起卡尔曼滤波精度下降的情况,提出了一种基于新息和

关 键 词:无迹卡尔曼滤波  自适应卡尔曼滤波  协方差匹配  新息  残差  
收稿时间:2009-09-22

An Innovation and Residual-Based Adaptive UKF Algorithm
ZHOU Wei-dong,QIAO Xiang-wei,JI Yu-ren,MENG Fan-bin. An Innovation and Residual-Based Adaptive UKF Algorithm[J]. Journal of Astronautics, 2010, 31(7): 1798-1804. DOI: 10.3873/j.issn.1000-1328.2010.07.015
Authors:ZHOU Wei-dong  QIAO Xiang-wei  JI Yu-ren  MENG Fan-bin
Affiliation:ZHOU Wei-dong,QIAO Xiang-wei,JI Yu-ren,MENG Fan-bin(Department of Automation,Harbin Engineering University,Harbin 150001,China)
Abstract:Considering that the prior statistics noise of a Kalman filter does not agree with its real behavior,an adaptive unscented Kalman filter algorithm based on innovation and residual sequences is proposed to on-line estimate the statistics noise property. First,the observation noise covariance matrix is real-time tracked through innovation sequence. Then the real time variation of process noise covariance is on line estimated based on the orthogonal principle between innovated sequence and residual sequence es...
Keywords:Unscented Kalman filter(UKF)  Adaptive Kalman filter  Covariance match  Innovation  Residual  
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《宇航学报》浏览原始摘要信息
点击此处可从《宇航学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号