On the optimality of recursive unbiased state estimation with unknown inputs

被引：51

作者：

Kerwin, WS

Prince, JL

机构：

[1] Univ Washington, Dept Radiol, Seattle, WA 98195 USA

[2] Johns Hopkins Univ, Dept Elect & Comp Engn, Baltimore, MD 21218 USA

来源：

AUTOMATICA | 2000年 / 36卷 / 09期

关键词：

Kalman filters; optimal estimation; minimum variance; unbiased estimation;

D O I：

10.1016/S0005-1098(00)00046-7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For system models with unknown inputs, state estimates may be obtained using linear minimum-variance unbiased estimation. Here, a proof is presented showing that the optimal solution over the class of all linear unbiased estimates may be written in the form of a linear recursive filter, thereby validating previous work in this area. (C) 2000 Elsevier Science Ltd. All rights reserved.

引用

页码：1381 / 1383

页数：3

共 4 条

[1] Unbiased minimum variance estimation for systems with unknown exogenous inputs [J].