Krein space approach to robust H∞ filtering for GNSS/SINS integrated navigation system with missing measurements

被引：0

作者：

Che, Yanting ^{[1
]}

Wang, Qiuying ^{[2
]}

Gao, Wei ^{[1
]}

Yu, Fei ^{[1
]}

Feng, Jin ^{[1
]}

机构：

[1] College of Automation, Harbin Engineering University, Harbin

[2] College of Information and Communication Engineering, Harbin Engineering University, Harbin

来源：

Journal of Computational and Theoretical Nanoscience | 2015年 / 12卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Integrated navigation system; Kalman filtering; Krein space; Linear uncertain systems; Missing signal;

D O I：

10.1166/jctn.2015.4735

中图分类号：

学科分类号：

摘要：

In this paper, Krein space approach to robust H∞ filtering for uncertain systems with missing measurement is developed. The unavailablesystem measurements may occur at any time with a known conditional probability distribution. The parameter uncertainties are allowed to be norm-bounded. The purpose of this problem is to minimize a second-order form through Krein-space robust estimation such that, for all parameter uncertainties and all random missing observations, the estimated states are bounded in an ellipsoidal set. M-P inverse has to be introduced to design Krein space formal system. Then Riccati-styled recursion is obtained in the Krein space state-space structure. It is shown that the objective quadratic form is minimized if a necessary and sufficient condition is satisfied. Finally, the numerical examples illustrate the performance of the proposed filter. Copyright © 2015 American Scientific Publishers. All rights reserved.

引用

页码：5906 / 5915

页数：9

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