DocumentCode
3266683
Title
Distributed Fusion Estimation Based on Pseudo-measurement for Multi-sensor System
Author
Jin Xue-bo ; Jing-Jing, Du ; Lei-lei, Wang
Author_Institution
Coll. of Inf. & Electron., Zhejiang Sci-Tech Univ., Hangzhou, China
Volume
1
fYear
2009
fDate
6-7 June 2009
Firstpage
297
Lastpage
300
Abstract
By considering the relation between local fusion estimation and fusion center, in this paper the estimation from local fusion nodes is regarded as a pseudo-measurement. Then the distributed estimation algorithm is turned to be two-level centralized fusion estimation and the new optimal distributed fusion estimation algorithm is obtained with Kalman filtering form, which in general only centralized estimation method has. Simulations show the developed algorithm has the excellent estimation performance. By the developed algorithm, the distributed multisensor system can be unified with centralized system and make it possible that applying the abundant research result of centralized system to distributed multisensor system.
Keywords
Kalman filters; estimation theory; sensor fusion; Kalman filtering; distributed fusion estimation algorithm; distributed multisensor system; fusion center; local fusion nodes; pseudo-measurement; simulation; two-level centralized fusion estimation; Computational intelligence; Distributed computing; Educational institutions; Filtering algorithms; Informatics; Kalman filters; Multisensor systems; Noise measurement; Robustness; State estimation; centralized fusion estimation; distributed fusion estimation; fusion center; local fusion estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3645-3
Type
conf
DOI
10.1109/CINC.2009.95
Filename
5231131
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