Monte Carlo filters for non-linear state estimation

被引：57

作者：

Bolviken, E

Acklam, PJ

Christophersen, N

Stordal, JM

机构：

[1] Univ Oslo, Dept Math, N-0316 Oslo, Norway

[2] Univ Oslo, Dept Informat, N-0316 Oslo, Norway

[3] Norwegian Def Res Estab, Kjeller, Norway

来源：

AUTOMATICA | 2001年 / 37卷 / 02期

关键词：

extended Kalman filter; Monte Carlo filter; rejection sampling; measurement saturation;

D O I：

10.1016/S0005-1098(00)00151-5

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The application of Monte Carlo techniques to Bayesian state estimation is discussed. A simple theory for the Monte Carlo uncertainty is developed showing that the number of Monte Carlo replications does not in principle have to be large. A recursive on-line algorithm based on rejection sampling is given and improved versions suggested. The methods are illustrated on a non-linear pendulum with measurement saturation. (C) 2000 Elsevier Science Ltd. All rights reserved.

引用

页码：177 / 183

页数：7

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