Generalized Parallel Algorithm of Extended Kalman Filtering

被引：0

作者：

Guo, Jia ^{[1
]}

Wu, Shu-xing ^{[1
]}

Wang, Zhao-qiang ^{[1
]}

Li, Xue-li ^{[1
]}

机构：

[1] Beijing Informat Technol Coll, Beijing, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON INFORMATICS, CONTROL AND AUTOMATION (ICA 2015) | 2015年

关键词：

State estimation; Nonlinear system; Extended Kalman filtering; Parallel algorithm;

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 most popular state estimation method for nonlinear systems is perhaps the extended Kalman filtering (EKF). In this paper, we propose a generalized parallel algorithm of EKF. This method apply two EKF in parallel and exchange their estimates after each iteration. Numerical example with simulation demonstrates the effectiveness of this method over EKF.

引用

页码：236 / 239

页数：4

共 6 条

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QIAO, XZ
CHEN, GR
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