Estimation of Noise Means and Covariance Matrices for Linear Time-Varying Models

被引：0

作者：

Kost, Oliver ^{[1
,2
]}

Dunik, Jindrich ^{[1
,2
]}

Straka, Ondrej ^{[1
,2
]}

机构：

[1] Univ West Bohemia, Dept Cybernet, Fac Appl Sci, Univ 8, Plzen 30614, Czech Republic

[2] Univ West Bohemia, Res Ctr NTIS, Fac Appl Sci, Univ 8, Plzen 30614, Czech Republic

来源：

2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC) | 2018年

关键词：

Estimation; Identification; State-space models; Noise means; Noise Covariance Matrices; LEAST-SQUARES METHOD; IDENTIFICATION;

D O I：

暂无

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 means and covariance matrices of the noises of a linear time-varying system described by the state-space model. The proposed measurement difference method is based on a statistical analysis of differenced, linearly transformed, and shifted augmented measurement vector resulting in a system of linear matrix equations for consistent estimation of both; noise means and noise covariance matrices. The theoretical results are discussed and illustrated in a numerical example.

引用

页码：265 / 271

页数：7

共 19 条

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