Title
Stability conditions for multi-sensor state estimation over a lossy network.
Abstract
This paper studies a networked state estimation problem for a spatially large linear system with a distributed array of sensors, each of which offers partial state measurements. A lossy communication network is used to transmit the sensor measurements to a central estimator where the minimum mean square error (MMSE) state estimate is computed. Under a Markovian packet loss model, we provide necessary and sufficient conditions for the stability of the estimator for any diagonalizable system in the sense that the mean of the state estimation error covariance matrix is uniformly bounded. In particular, the stability conditions for the second-order systems with an i.i.d. packet loss model are explicitly expressed as simple inequalities in terms of the largest open-loop pole and the packet loss rate.
Year
DOI
Venue
2015
10.1016/j.automatica.2014.12.022
Automatica
Keywords
Field
DocType
Networked state estimation,Distributed sensing,Packet loss,Minimum mean square error,Kalman filtering
Mathematical optimization,Diagonalizable matrix,Linear system,Control theory,Packet loss,Minimum mean square error,Stability conditions,Kalman filter,Covariance matrix,Mathematics,Estimator
Journal
Volume
Issue
ISSN
53
C
0005-1098
Citations 
PageRank 
References 
6
0.45
15
Authors
3
Name
Order
Citations
PageRank
Tianju Sui1235.14
Keyou You283150.16
Minyue Fu31878221.17