Fine Tuning Kalman Filter Using Simulink Design Optimization
7 次查看(过去 30 天)
显示 更早的评论
I would like to tune my Kalman filter (Q and R matrices) using design optimization toolbox. I introduce the estimated signal and add a signal property to the optimizer. The signal property is Track Reference Signal with proper Time Vector and Amplitude. Although, the initial values of Q and R are relatively good, the second estimated signal ends up being zero. I wonder how I can prevent that, or in general tune my filter more optimaly.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/230435/image.png)
0 个评论
回答(1 个)
Kaashyap Pappu
2019-8-8
A similar query regarding the Q and R matrices’ optimization was addressed and elaborated upon here. It is important to model the noise characteristics prior to Kalman Filtering to obtain the Q and R matrices for better performance.
0 个评论
另请参阅
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!