Title :
Sequential filtering for linear discrete-time systems with delayed measurements
Author_Institution :
School of Information Science and Technology, Taishan University, Taian Shandong 271021, P.R. China
Abstract :
This paper investigates the problems of designing optimal sequential filter for discrete-time systems with measurement time-delay. Two kinds of approaches are proposed to tackle such problems via the innovation analysis theory. The approaches, to be presented, are to convert a delay optimal sequential filtering problems into a delay-free ones. Based on the minimum mean square error estimation principle, the optimal sequential filter is designed by solving the recursive matrix equations. Two examples are given to illustrate the effectiveness of the approaches presented.
Keywords :
Covariance matrices; Delays; Discrete-time systems; Estimation; Kalman filters; Mathematical model; Innovation; Sequential Filtering; Time-Delay;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7260006