DocumentCode
3170888
Title
On reduced order parallel filters for state estimation
Author
Rice, T.R. ; Bush, W. ; Alouani, A.T.
Author_Institution
US Naval Surface Warfare Center, Dahlgren, VA, USA
fYear
1990
fDate
1-4 Apr 1990
Firstpage
706
Abstract
A class of global Kalman filters which were implemented using two parallel reduced-order filters is discussed. It is shown that the optimal state estimate is a linear combination of the states of the reduced-order filters. This approach gives the optimal solution and is computationally more attractive than the use of a global Kalman filter
Keywords
Kalman filters; filtering and prediction theory; parallel algorithms; state estimation; global Kalman filters; optimal state estimate; reduced order parallel filters; Acceleration; Concurrent computing; Filters; Gaussian noise; Noise measurement; Q measurement; State estimation; Symmetric matrices; Target tracking; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Southeastcon '90. Proceedings., IEEE
Conference_Location
New Orleans, LA
Type
conf
DOI
10.1109/SECON.1990.117908
Filename
117908
Link To Document