首页 | 本学科首页   官方微博 | 高级检索  
     检索      

一种新的混合迭代UKF
引用本文:常国宾,许江宁,胡柏青,纪兵.一种新的混合迭代UKF[J].武汉大学学报(信息科学版),2012,37(6):701-703.
作者姓名:常国宾  许江宁  胡柏青  纪兵
作者单位:海军工程大学电气与信息工程学院,武汉市解放大道717号,430033
基金项目:国家自然科学基金资助项目,东南大学微电子机械系统教育部重点实验室开放基金资助项目
摘    要:从统计线性回归的角度对无味变换(unscented transformation,UT)进行分析,推导了迭代无味卡尔曼滤波(iterated unscented Kalman filter,IUKF)。针对IUKF计算量大的问题,结合弦线迭代法和IUKF,得到了一种新的混合迭代无味卡尔曼滤波器。数值仿真的结果表明,新滤波算法的精度优于扩展卡尔曼滤波、迭代扩展卡尔曼滤波和无味卡尔曼滤波,并可以有效降低IUKF的计算量。

关 键 词:非线性滤波  迭代无味卡尔曼滤波  弦线法  单变量非平稳增长模型

A New Kind of Hybrid Iterated Unscented Kalman Filter
CHANG Guobin,XU Jiangning,HU Baiqing,JI Bing.A New Kind of Hybrid Iterated Unscented Kalman Filter[J].Geomatics and Information Science of Wuhan University,2012,37(6):701-703.
Authors:CHANG Guobin  XU Jiangning  HU Baiqing  JI Bing
Institution:1(1 Institute of Electrical and Information Engineering,Naval University of Engineering, 717 Jiefang Road,Wuhan 430033,China)
Abstract:Unscented transformation is analyzed through the viewpoint of statistical linear regression,and iterated unscented Kalman filter(IUKF) is derived.The so-called hybrid iterated unscented Kalman filter is presented by incorperating secant method into IUKF in order to cope with the high-computation-cost problem.New filtering method is introduced into the example of univariate nonstationary growth model.Simulation results show that new method outperforms extended Kalman filter,iterated extended Kalman filter and unscented Kalman filter.The computation cost can be reduced relative to IUKF.
Keywords:nonliner filter  IUKF  secant method  univariate nonstationary growth model
本文献已被 CNKI 万方数据 等数据库收录!
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