DocumentCode :
836521
Title :
On complementary models and fixed-interval smoothing
Author :
Weinert, Howard L. ; Desai, Uday B.
Author_Institution :
John Hopkins University, Baltimore, MD, USA
Volume :
26
Issue :
4
fYear :
1981
fDate :
8/1/1981 12:00:00 AM
Firstpage :
863
Lastpage :
867
Abstract :
A new algorithm is derived for the standard fixed-interval linear smoothing problem in which the signal is generated by a state model. The structure of this new algorithm allows the smoothed estimate to be easily updated in response to a change in the initial state covariance matrix 
, since, unlike in existing algorifiuns, the relevant Riccati equation is entirely independent of . The derivation of the algorithm is based on properties of complementary models.
, since, unlike in existing algorifiuns, the relevant Riccati equation is entirely independent of . The derivation of the algorithm is based on properties of complementary models.Keywords :
Least-squares methods; Linear systems; Smoothing methods; Covariance matrix; Differential equations; History; Least squares approximation; Random processes; Random variables; Riccati equations; Signal generators; Smoothing methods; State estimation;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1981.1102735
Filename :
1102735
Link To Document :
