Consensus-Based Distributed Multiple Model UKF for Jump Markov Nonlinear Systems

被引：142

作者：

Li, Wenling ^{[1
,2
]}

Jia, Yingmin ^{[1
,2
]}

机构：

[1] Beihang Univ BUAA, Res Div 7, Beijing 100191, Peoples R China

[2] Beihang Univ BUAA, Dept Syst & Control, Beijing 100191, Peoples R China

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2012年 / 57卷 / 01期

关键词：

Consensus theory; distributed estimation; jump Markov nonlinear system (JMNLS); unscented Kalman filter (UKF); AVERAGE CONSENSUS; SENSOR NETWORKS; ALGORITHMS; FILTERS;

D O I：

10.1109/TAC.2011.2161838

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This note studies the problem of distributed estimation for jump Markov nonlinear systems (JMNLSs) in a not fully connected sensor network. Based on the consensus theory, a distributed unscented Kalman filter (UKF) is first derived for nonlinear systems without jumping parameters and then it is extended to develop a distributed multiple model UKF for JMNLSs. The proposed filtering algorithm is illustrated via a simulation example involving tracking a maneuvering target.

引用

收藏

页码：230 / 236

页数：7

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