Title
Robust finite-horizon filtering for stochastic systems with missing measurements
Abstract
In this letter, we consider the robust finite-horizon filtering problem for a class of discrete time-varying systems with missing measurements and norm-bounded parameter uncertainties. The missing measurements are described by a binary switching sequence satisfying a conditional probability distribution. An upper bound for the state estimation error variance is first derived for all possible missi...
Year
DOI
Venue
2005
10.1109/LSP.2005.847890
IEEE Signal Processing Letters
Keywords
Field
DocType
Robustness,Filtering,Stochastic systems,Uncertain systems,Upper bound,State estimation,Filters,Time varying systems,Measurement uncertainty,Probability distribution
Mathematical optimization,Conditional probability distribution,Upper and lower bounds,Filter (signal processing),Stochastic process,Filtering problem,Robustness (computer science),Kalman filter,Probability distribution,Mathematics
Journal
Volume
Issue
ISSN
12
6
1070-9908
Citations 
PageRank 
References 
69
5.21
7
Authors
4
Name
Order
Citations
PageRank
Zidong Wang111003578.11
Fuwen Yang2105174.00
Daniel W.C. Ho35311285.38
Xiaohui Liu411518.03