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The Convergence of the Extended Kalman Filter [PDF]
, 2007 We demonstrate that the extended Kalman filter converges locally for a broad class of nonlinear systems. If the initial estimation error of the filter is not too large then the error goes to zero exponentially as time goes to infinity. To demonstrate this, we require that the system be $C^2$ and uniformly observable with bounded second partial ...
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Diphtheria transmission prediction by extended Kalman filter
MethodsXDiphtheria transmission in West Java becomes our concern in this paper. The findings of this article are implementation of isolation and estimation technique of parameters using extended Kalman filter on the model of diphtheria transmission.
Mohammad Ghani
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CHOICE EFFECT OF INPUT ACTION MODELS ON MEASURING ACCURACY FOR EXTENDED KALMAN FILTERS
Доклады Белорусского государственного университета информатики и радиоэлектроники, 2019 Choice effect of input action models on measuring accuracy for Extended Kalman filters is considered. Recommendations about practical application of Extended Kalman filter modifications are listed.
P. A. Khmarski, A. S. Solonar
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Polynomial extended Kalman filter
IEEE Transactions on Automatic Control, 2005This work presents a polynomial version of the well-known extended Kalman filter (EKF) for the state estimation of nonlinear discrete-time stochastic systems. The proposed filter, denoted polynomial EKF (PEKF), consists in the application of the optimal polynomial filter of a chosen degree mu to the Carleman approximation of a nonlinear system. When mu
GERMANI, Alfredo +2 more
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An interlaced extended Kalman filter
IEEE Transactions on Automatic Control, 1999The aim of the paper is to propose an estimation algorithm, called Interlaced Extended Kalman Filter (IEKF), for a class of discrete-time nonlinear systems. The vector state of the system is assumed to be partitionable into \(m\) parts (subsystems), whose dynamic equations are supposed to be affine for each of the corresponding part (subsystem).
Luigi Glielmo +2 more
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Robust extended Kalman filtering
IEEE Transactions on Signal Processing, 1999Summary: Linearization errors inherent in the specification of an extended Kalman filter (EKF) can severely degrade its performance. This correspondence presents a new approach to the robust design of a discrete-time EKF by application of the robust linear design methods based on the \(H_\infty\) norm minimization criterion.
Einicke, G., White, L.
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Modified extended Kalman filtering
IEEE Transactions on Automatic Control, 1994The authors propose a modification of the extended Kalman filtering algorithm for the following system: \[ dX_ t= f(t, X_ t) dt+ \varepsilon_ 1 \sigma_ 1 (t)dV_ t, \qquad dy_ t= h(t, X_ t) dt+ \varepsilon_ 2 \sigma_ 2 (t) dW_ t, \] where \((V_ t)\) and \((W_ t)\) are independent Brownian motions, \((X_ t)\in \mathbb{R}^ n\) and \((y_ t)\in \mathbb{R ...
Nasir U. Ahmed, S. M. Radaideh
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Extended Kalman filter for extended object tracking
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017In this work, we present a novel method for tracking an elliptical shape approximation of an extended object based on a varying number of spatially distributed measurements. For this purpose, an explicit nonlinear measurement equation is formulated that relates the kinematic and shape parameters to a measurement by means of a multiplicative noise term.
Shishan Yang, Marcus Baum
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Kalman filtering in extended noise environments
IEEE Transactions on Automatic Control, 2005This note introduces an extended environment for Kalman filtering that considers also the presence of additive noise on input observations in order to solve the problem of optimal (minimal variance) estimation of noise-corrupted input and output sequences.
DIVERSI, ROBERTO +2 more
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