編集メモ: 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.
引用
Yi Cao (2025). Learning the Extended Kalman Filter (https://www.mathworks.com/matlabcentral/fileexchange/18189-learning-the-extended-kalman-filter), MATLAB Central File Exchange. に取得済み.
MATLAB リリースの互換性
プラットフォームの互換性
Windows macOS Linuxカテゴリ
- Control Systems > System Identification Toolbox > Online Estimation >
- Mathematics and Optimization > Optimization Toolbox > Systems of Nonlinear Equations >
タグ
謝辞
ヒントを得たファイル: Learning the Kalman Filter
ヒントを与えたファイル: Learning the Unscented Kalman Filter, Unconstrained Optimization using the Extended Kalman Filter, Neural Network training using the Extended Kalman Filter
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!バージョン | 公開済み | リリース ノート | |
---|---|---|---|
1.0.0.0 | Update example with block-comment lines |