DocumentCode
2569330
Title
Multisensor distributed fusion filters for systems with stochastic system and sensor biases
Author
Jinhua, Bai ; Shuli, Sun
Author_Institution
Dept. of Autom., Heilongjiang Univ., Harbin
fYear
2008
fDate
2-4 July 2008
Firstpage
4591
Lastpage
4594
Abstract
Based on three fusion estimation algorithms weighted by matrices, diagonal matrices and scalars, the distributed information fusion Kalman filters for the state and system bias are given for multi-sensor stochastic systems with stochastic system and sensor biases, respectively. They are obtained by the fusion estimation for common components of the transferred multi-model and multi-sensor systems. Furthermore, they are decoupled. A simulation example shows the effectiveness of the algorithms.
Keywords
Kalman filters; covariance matrices; sensor fusion; stochastic systems; diagonal matrices; distributed information fusion Kalman filters; fusion estimation algorithms; multisensor distributed fusion filters; sensor biases; stochastic system; Automation; Electronic mail; Information filtering; Information filters; Kalman filters; Sensor fusion; Sensor systems; State estimation; Stochastic systems; Sun; Kalman filter; Stochastic bias; cross-covariance matrix; information fusion;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-1733-9
Electronic_ISBN
978-1-4244-1734-6
Type
conf
DOI
10.1109/CCDC.2008.4598199
Filename
4598199
Link To Document