Optimal and Self-correcting Covariance Intersection Fusion Kalman Filters
Optimal and Self-correcting Covariance Intersection Fusion Kalman Filters
- Neue Suche nach: Zhang, Peng
- Neue Suche nach: Liu, Jinfang
- Neue Suche nach: Wang, Yi
- Neue Suche nach: Martinsen, Kristian
- Neue Suche nach: Yu, Tao
- Neue Suche nach: Wang, Kesheng
- Neue Suche nach: Zhang, Peng
- Neue Suche nach: Liu, Jinfang
For the multi-sensor discrete linear time-invariant random system, the optimal covariance intersection (CI) fusion steady-state Kalman filters are presented, which have uncharted cross-covariance among the partial filtering errors. Their accuracies are higher than those of the partial optimal steady-state Kalman filters, and are lower than those of the optimal fusion Kalman filters which are fused by the cross-covariances. In the case that both the cross-covariance and the noise variances are uncharted, substituting the online consistent estimators of the noise variances into the optimal CI fusion Kalman filter, a self-correcting CI fusion Kalman filter is presented. I have proven its optimality asymptotically by the method of DESA (dynamic error system analysis) and the continuous properties of functions, i.e. the self-correcting CI Kalman fuser convergences to the optimal CI fuser in a implementation. One Monte-Carlo emulation example verifies the precision grade among the partial and fusion Kalman estimators, and the convergence of the self-correcting Kalman fuser.
Dokumentinformationen
Optimal and Self-correcting Covariance Intersection Fusion Kalman Filters
Lect. Notes Electrical Eng.
International Workshop of Advanced Manufacturing and Automation ; 2020 ; Zhanjiang, China October 12, 2020 - October 13, 2020
2021-01-23
9 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Uncharted cross-covariance , Uncharted noise variances , Covariance intersection , Convergence , Self-correcting Kalman filter Engineering , Control, Robotics, Mechatronics , Manufacturing, Machines, Tools, Processes , Engineering Economics, Organization, Logistics, Marketing , Artificial Intelligence
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