DocumentCode
3182402
Title
Optimal estimation for multisensor data fusion system with correlated measurement noise
Author
Jin, Xue-Bo ; Sun, You-Xian
Author_Institution
Nat. Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China
Volume
2
fYear
2002
fDate
26-30 Aug. 2002
Firstpage
1641
Abstract
Based on the matrix theory, the covariance matrix of correlated measurement noise is successfully parallel decomposed and the linear observation models are transformed to new observation models. Then optimal data fusion estimation algorithms are presented. When measurement noise is uncorrelated, the results are reduced to the optimal algorithms with uncorrelated measurement noise.
Keywords
covariance matrices; matrix decomposition; parameter estimation; random noise; sensor fusion; correlated measurement noise; covariance matrix; linear observation models; matrix decomposition; multisensor data fusion; optimal estimation; parallel decomposition; Covariance matrix; Erbium; Laboratories; Noise measurement; Noise reduction; Sensor fusion; Sensor systems; State estimation; Sun; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 2002 6th International Conference on
Print_ISBN
0-7803-7488-6
Type
conf
DOI
10.1109/ICOSP.2002.1180114
Filename
1180114
Link To Document