Paper Info
Title
Optimal Linear Estimators for Systems With Finite-Step Correlated Noises and Packet Dropout Compensations.
Abstract
This paper is concerned with the optimal estimation problem for discrete-time stochastic systems with finite-step auto- and cross-correlated noises and multiple packet dropouts induced by the unreliable networks. When a packet transmitted from the sensor to the data processing center is lost, its predictor is used as the compensation. The optimal linear estimators including filter, predictor and smoother that depend on the packet arriving rate are proposed in the linear minimum variance sense via an innovative analysis approach. They are computed in terms of the solutions of some auto- and cross-covariance matrices. A tracking system example is given to demonstrate the effectiveness of the proposed algorithms.
Year
DOI
Venue
2016
10.1109/TSP.2016.2576420
IEEE Trans. Signal Processing
Keywords
Field
DocType
Noise measurement,Covariance matrices,Loss measurement,Estimation error,Data processing,Signal processing algorithms,Technological innovation
Minimum-variance unbiased estimator,Data processing,Noise measurement,Computer science,Control theory,Matrix (mathematics),Network packet,Tracking system,Optimal estimation,Estimator
Journal
Volume
Issue
ISSN
64
21
1053-587X
Citations 
PageRank 
References 
18
0.66
10
Authors
3
Name
Order
Citations
PageRank
Shuli Sun173452.41
Tian Tian212017.90
Honglei Lin3679.27