Learning the Extended Kalman Filter

Version 1.0.0.0 (2,1 ko) par Yi Cao
An implementation of Extended Kalman Filter for nonlinear state estimation.
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Mise à jour 23 jan. 2008

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Note de l’éditeur : This file was selected as MATLAB Central Pick of the Week

This is a tutorial on nonlinear extended Kalman filter (EKF). It uses the standard EKF fomulation to achieve nonlinear state estimation. Inside, it uses the complex step Jacobian to linearize the nonlinear dynamic system. The linearized matrices are then used in the Kalman filter calculation.

The complex step differentiation seems improving the EKF performance particularly in accuracy such that the optimization and NN training through the EKF are better than through the UKF (unscented Kalman filter, http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=18217&objectType=FILE). Other complex step differentiation tools include the CSD Hessian available at http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=18177&objectType=FILE.

Citation pour cette source

Yi Cao (2024). Learning the Extended Kalman Filter (https://www.mathworks.com/matlabcentral/fileexchange/18189-learning-the-extended-kalman-filter), MATLAB Central File Exchange. Récupéré le .

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Version Publié le Notes de version
1.0.0.0

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