DocumentCode
1832865
Title
Distributed ensemble Kalman filter for multisensor application
Author
Kazerooni, M. ; Shabaninia, Faridoon ; Vaziri, M. ; Vadhva, S.
Author_Institution
Shiraz Univ., Shiraz, Iran
fYear
2013
fDate
14-16 Aug. 2013
Firstpage
732
Lastpage
735
Abstract
In this paper, a distributed ensemble Kalman filter (DEnKF) is proposed for sensor fusion in a sensor network. To solve data fusion problem in distributed sensor network, consensus filter is implemented. To estimates nodes´ states, each node uses local and neighbors´ information rather than the information from all nodes in the network. So, due to this property, this proposed algorithm is applicable to large scale problem. Simulation results demonstrate the effectiveness of DEnKF algorithm.
Keywords
Kalman filters; sensor fusion; DEnKF; consensus filter; data fusion problem; distributed ensemble Kalman filter; distributed sensor network; large scale problem; multisensor application; sensor fusion; Covariance matrices; Educational institutions; Estimation; Filtering algorithms; Information filters; Kalman filters; consensus filter; distributed ensemble Kalman filter; sensor fusion;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Reuse and Integration (IRI), 2013 IEEE 14th International Conference on
Conference_Location
San Francisco, CA
Type
conf
DOI
10.1109/IRI.2013.6642544
Filename
6642544
Link To Document