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On the convergence of the unscented Kalman filter
by
Daid, Assia
, Busvelle, Eric
, Aidene, Mohamed
in
Approximation
/ Automatic
/ Continuous time systems
/ Control theory
/ Convergence
/ Engineering Sciences
/ Extended Kalman filter
/ High gain
/ Nonlinear observers
/ Nonlinear systems
/ Random variables
/ Sensors
/ Unscented Kalman filter
/ Unscented Kalman observer
2021
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On the convergence of the unscented Kalman filter
by
Daid, Assia
, Busvelle, Eric
, Aidene, Mohamed
in
Approximation
/ Automatic
/ Continuous time systems
/ Control theory
/ Convergence
/ Engineering Sciences
/ Extended Kalman filter
/ High gain
/ Nonlinear observers
/ Nonlinear systems
/ Random variables
/ Sensors
/ Unscented Kalman filter
/ Unscented Kalman observer
2021
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Do you wish to request the book?
On the convergence of the unscented Kalman filter
by
Daid, Assia
, Busvelle, Eric
, Aidene, Mohamed
in
Approximation
/ Automatic
/ Continuous time systems
/ Control theory
/ Convergence
/ Engineering Sciences
/ Extended Kalman filter
/ High gain
/ Nonlinear observers
/ Nonlinear systems
/ Random variables
/ Sensors
/ Unscented Kalman filter
/ Unscented Kalman observer
2021
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Journal Article
On the convergence of the unscented Kalman filter
2021
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Overview
A convergence analysis of the modified unscented Kalman filter (UKF), used as an observer for a class of nonlinear deterministic continuous time systems, is presented. Under certain conditions, the extended Kalman filter (EKF) is an exponential observer for non-linear systems, i.e., the dynamics of the estimation error is exponentially stable. It is shown that unlike the EKF, the UKF is not an exponentially converging observer. A modification of the UKF – the unscented Kalman observer – is proposed, which is a better candidate for an observer.
This paper is a first step towards a proof of the global convergence of the high-gain version of the UKO.
Publisher
Elsevier Ltd,Elsevier Limited,Elsevier
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