Distributed fusion cubature Kalman filters for nonlinear systems

Summary This paper is concerned with the distributed fusion estimation problem for multisensor nonlinear systems. Based on the Kalman filtering framework and the spherical cubature rule, a general method for calculating the cross‐covariance matrices between any two local estimators is presented for...

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Bibliographic Details
Published inInternational journal of robust and nonlinear control Vol. 29; no. 17; pp. 5979 - 5991
Main Authors Hao, Gang, Sun, Shuli
Format Journal Article
LanguageEnglish
Published Bognor Regis Wiley Subscription Services, Inc 25.11.2019
Subjects
Algorithms
Covariance matrix
cross‐covariance
cubature Kalman filter
distributed fusion
Kalman filters
Mathematical analysis
Matrix methods
multisensor
nonlinear system
Nonlinear systems
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Summary:Summary This paper is concerned with the distributed fusion estimation problem for multisensor nonlinear systems. Based on the Kalman filtering framework and the spherical cubature rule, a general method for calculating the cross‐covariance matrices between any two local estimators is presented for multisensor nonlinear systems. In the linear unbiased minimum variance sense, based on the cross‐covariance matrices, a distributed fusion cubature Kalman filter weighted by matrices (MW‐CKF) is presented. The proposed MW‐CKF has better accuracy and robustness. An example verifies the effectiveness of the proposed algorithms.
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.4709