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Received:October 19, 2010Revised:October 19, 2010
基金项目:This work was supported by the Natural Science Foundation of China (No. 60874062), the Program for New Century Excellent Talents in University (No. NCET-10-0133) and that in Heilongjiang Province (No.1154-NCET-01).
Optimal linear estimators for systems with random measurement delays
Shuli SUN,Tian TIAN
(School of Electronic Engineering, Heilongjiang University)
This paper is concerned with the optimal linear estimation problem for linear discrete-time stochastic systems with random measurement delays. A new model that describes the random delays is constructed where possible the largest delay is bounded. Based on this new model, the optimal linear estimators including filter, predictor and smoother are developed 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. The steady-state estimators are also investigated. A sufficient condition for the convergence of the optimal linear estimators is given. A simulation example shows the effectiveness of the proposed algorithms.
Key words:  Optimal linear estimation  Random measurement delays  Innovation analysis approach  Riccati difference equation  Lyapunov difference equation