Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

Optimal linear estimation for systems with multiplicative noise uncertainties and multiple packet dropouts

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ma, J. ; Sch. of Electron. Eng., Heilongjiang Univ., Harbin, China ; Sun, S.

This study is concerned with the optimal linear estimation problem for linear discrete-time stochastic systems with multiplicative noise uncertainties in state and measurement matrices and with multiple packet dropouts from a sensor to an estimator. Based on the projection theory, the optimal linear estimators including filter, predictor and smoother are derived in the linear minimum variance sense. In the absence of stochastic uncertainties and/or packet dropouts, the corresponding results can be obtained as the special cases of the proposed estimators. Steady-state property is also analysed. A sufficient condition for the existence of the steady-state estimators is obtained. They can be computed offline. So they have the reduced online computational cost. Simulation examples are given to demonstrate the effectiveness of the proposed estimators.

Published in:

Signal Processing, IET  (Volume:6 ,  Issue: 9 )