DocumentCode
401602
Title
Multisensor state fusion estimation with correlated measurement noise
Author
Jin, Xue-Bo ; Sun, You-xian
Author_Institution
Coll. of Informatics & Electron., Zhejiang Inst. of Sci. & Technol., Hangzhou, China
Volume
2
fYear
2003
fDate
2-5 Nov. 2003
Firstpage
1000
Abstract
Based on matrix theory, a new decomposed state fusion estimation algorithm is presented, and the covariance matrix of correlated measurement noise is successfully parallel decomposed. The algorithm is optimal for a special data fusion system, in which the covariance matrix of correlated measurement noise is a Pei-Radman matrix and observation matrices are identical.
Keywords
correlation methods; covariance matrices; sensor fusion; state estimation; Pei-Radman matrix; correlated measurement noise; covariance matrix; data fusion system; matrix theory; multisensor state fusion estimation; observation matrices; Covariance matrix; Erbium; Intelligent sensors; Matrix decomposition; Noise measurement; Sensor fusion; Sensor phenomena and characterization; Sensor systems; State estimation; Sun;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/ICMLC.2003.1259627
Filename
1259627
Link To Document