Globally Optimal Multisensor Distributed Random Parameter Matrices Kalman Filtering Fusion with Applications

Globally Optimal Multisensor Distributed Random Parameter Matrices Kalman Filtering Fusion with Applications

This paper proposes a new distributed Kalman filtering fusion with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering. It is proved that under a mild condition the fused state estimate is equivalent to the centralized Kalman filtering using all sensor...

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Bibliographic Details
Main Authors: Donghua Wang, Enbin Song, Jie Zhou, Dandan Luo, Yunmin Zhu, Yingting Luo
Format: Article
Language:English
Published: MDPI AG 2008-12-01
Series:Sensors
Subjects:
Random parameters matrices
Kalman filtering
Centralized fusion
Distributed fusion
Online Access:http://www.mdpi.com/1424-8220/8/12/8086/

Internet

http://www.mdpi.com/1424-8220/8/12/8086/

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