Distributed estimation for moving target under switching interconnection network

Author

Zhenwei Zhou ; Yiguang Hong ; Haitao Fang

Author_Institution

Key Lab. of Syst. & Control, Beijing, China

fYear

2012

Firstpage

1818

Lastpage

1823

Abstract

This paper studies the distributed estimation problem for a moving discrete-time target under switching topologies and stochastic noises. For this problem, we propose a recursive distributed estimation algorithm based on state-consensus strategy. Under well-known observability and connectivity assumptions, an upper bound and lower bound for the total mean square estimation error (TMSEE) are established, respectively, by using common Lyapunov method and Kalman filtering theory.

Keywords

Kalman filters; Lyapunov methods; discrete time systems; mean square error methods; network theory (graphs); observability; recursive estimation; stochastic processes; time-varying systems; topology; Kalman filtering theory; Lyapunov method; TMSEE; connectivity assumption; lower bound; moving discrete-time target distributed estimation problem; observability assumption; recursive distributed estimation algorithm; state-consensus strategy; stochastic noises; switching interconnection network; switching topologies; total mean square estimation error; upper bound; Estimation; Kalman filters; Noise; Noise measurement; Switches; Topology; Upper bound; Distributed estimation; Kalman filter; moving target; stability; switching topologies;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4673-1871-6

Electronic_ISBN

978-1-4673-1870-9

Type

conf

DOI

10.1109/ICARCV.2012.6485124

Filename

6485124