DocumentCode :
1442013
Title :
Interval Kalman filtering
Author :
Chen, Guanrong ; Wang, Jianrong ; Shieh, Leang S.
Author_Institution :
Houston Univ., TX, USA
Volume :
33
Issue :
1
fYear :
1997
Firstpage :
250
Lastpage :
259
Abstract :
The classical Kalman filtering technique is extended to interval linear systems with the same statistical assumptions on noise, for which the classical technique is no longer applicable. Necessary interval analysis, particularly the notion of interval expectation, is reviewed and introduced. The interval Kalman filter (IKF) is then derived, which has the same structure as the classical algorithm, using no additional analysis or computation from such as H-mathematics. A suboptimal IKF is suggested next, for the purpose of real-time implementation. Finally, computer simulations are shown to compare the new interval Kalman filtering algorithm with the classical Kalman filtering scheme and some other existing robust Kalman filtering methods.
Keywords :
H control; Kalman filters; linear systems; robust control; uncertain systems; H-mathematics; interval Kalman filtering; interval analysis; interval expectation; linear systems; real-time implementation; robust estimation methods; statistical assumptions; suboptimal IKF; uncertain systems; Algorithm design and analysis; Computer simulation; Filtering algorithms; Kalman filters; Linear systems; Military computing; Nonlinear filters; Random variables; Recursive estimation; Robustness; Vectors;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/7.570759
Filename :
570759
Link To Document :
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