Paper Info
Title
Optimal linear estimators for systems with multiple random measurement delays and packet dropouts
Abstract
This article is concerned with the optimal linear estimation problem for linear discrete-time stochastic systems with possible multiple random measurement delays and packet dropouts, where the largest random delay is limited within a known bound and packet dropouts can be infinite. A new model is constructed to describe the phenomena of multiple random delays and packet dropouts by employing some random variables of Bernoulli distribution. By state augmentation, the system with random delays and packet dropouts is transferred to a system with random parameters. Based on the new model, the least mean square optimal linear estimators including filter, predictor and smoother are easily obtained via an innovation analysis approach. The estimators are recursively computed in terms of the solutions of a Riccati difference equation and a Lyapunov difference equation. A sufficient condition for the existence of the steady-state estimators is given. An example shows the effectiveness of the proposed algorithms.
Year
DOI
Venue
2013
10.1080/00207721.2011.601347
Int. J. Systems Science
Keywords
Field
DocType
largest random delay,multiple random delay,packet dropout,random variable,random parameter,possible multiple random measurement,multiple random measurement delay,random delay,new model,optimal linear estimation problem,optimal linear estimator,linear discrete-time stochastic system,least mean square,random measure,discrete time,steady state,difference equation
Bernoulli distribution,Least mean squares filter,Differential equation,Lyapunov function,Random variable,Mathematical optimization,Network packet,Recursion,Mathematics,Estimator
Journal
Volume
Issue
ISSN
44
2
0020-7721
Citations 
PageRank 
References 
12
0.67
7
Authors
2
Name
Order
Citations
PageRank
Shuli Sun173452.41
Wendong Xiao221433.93