Noise Moment and Parameter Estimation of State-Space Model

被引：4
|
作者：
Kost, Oliver [1 ]
Dunik, Jindrich
Straka, Ondrej
机构：
[1] Univ West Bohemia, Fac Sci Appl, Dept Cybernet, Univ 8, Plzen 30614, Czech Republic
来源：
IFAC PAPERSONLINE | 2018年 / 51卷 / 15期
关键词：
Noise moments estimation; Noise parameter estimation; State-space models; COVARIANCE MATRICES;
D O I：
10.1016/j.ifacol.2018.09.107
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 paper deals with the estimation of the moments and parameters of the state and measurement noises of a system described by a linear time-varying state-space model. In particular, a novel correlation measurement difference method is designed. The method is based on a statistical analysis of an augmented measurement prediction error leading to a system of linear matrix equations enabling higher-order noise moments estimation. The estimated moments, shown to converge to the true values, are then used for noise parameters computation. The theoretical results are discussed and illustrated in a numerical example. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：891 / 896
页数：6
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