Practical nonlinear filtering with the method of virtual measurements

被引:0
|
作者
Daum, F
机构
关键词
nonlinear filter; optimal filter; estimation; Kahman filter; recursive filter; exact nonlinear filter; discrete time filter;
D O I
10.1117/12.279530
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The method of virtual measurements (MOVM) will be described for designing nonlinear filters. The new nonlinear filter theory generalizes the Kalman filter, and in some important applications, the performance of the new filter is vastly superior to the extended Kalman filter (EKF). Unlike the EKF, the new theory does not use linearization. The new design approach, MOVM, can be applied to exact nonlinear filters as well as nonlinear approximate filters. Several examples are given in which the performance of the new nonlinear filter is compared with the extended Kalman filter.
引用
收藏
页码:400 / 416
页数:17
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