Distributed Fusion Estimation With Missing Measurements, Random Transmission Delays and Packet Dropouts

Author

Bo Chen ; Wen-An Zhang ; Li Yu

Author_Institution

Dept. of Autom., Zhejiang Univ. of Technol., Hangzhou, China

Volume

59

Issue

7

fYear

2014

fDate

Jul-14

Firstpage

1961

Lastpage

1967

Abstract

This technical note is concerned with the distributed Kalman filtering problem for a class of networked multi-sensor fusion systems (NMFSs) with missing sensor measurements, random transmission delays and packet dropouts. A novel stochastic model is proposed to describe the transmission delays and packet dropouts, and an optimal distributed fusion Kalman filter (DFKF) is designed based on the optimal fusion criterion weighted by matrices. Some sufficient conditions are derived such that the MSE of the designed DFKF is bounded or convergent. Moreover, steady-state DFKF is also presented for the NMFSs. An illustrative example is given to demonstrate the effectiveness of the proposed results.

Keywords

Kalman filters; estimation theory; sensor fusion; stochastic processes; MSE; NMFS; distributed Kalman filtering problem; distributed fusion estimation; missing sensor measurement; networked multisensor fusion system; optimal distributed fusion Kalman filter; optimal fusion criterion; packet dropout; random transmission delay; steady-state DFKF; stochastic model; sufficient condition; Covariance matrices; Delays; Estimation error; Kalman filters; Random variables; Stochastic processes; Distributed Kalman filtering; missing sensor measurements; networked multi-sensor fusion systems (NMFSs); packet dropouts; random transmission delays; stability analysis;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/TAC.2013.2297192

Filename

6701193