The Kalman filter is a feedback system. A Simulink model is developed to view this more clearly. From the feedback blocks, it is clear the normal Kalman filter is a linear time-variant system. By replacing the time-varying filter gain with its steady-state values, a simple linear time-invariant version of Kalman filter is provided in Simulink as well. Examples show that all these models provide similar performance.
Yi Cao (2020). Learning the Kalman Filter: A Feedback Perspective (https://www.mathworks.com/matlabcentral/fileexchange/18628-learning-the-kalman-filter-a-feedback-perspective), MATLAB Central File Exchange. Retrieved .
thanks very much
thank you for this example A+
Thank you for your sharing, thanks very much!
HI, YICao, I'm grad to see that the typo has removed quickly.
Now I have a question about the sampling period in your example 2:predict the position and velocity of a moving train.
For some latency or some other reasons in reality, I can't keep the sample period as a constant value. for example, I measurement the position at the time: 0.1, 0.3, 0.7, 0.8....... This means that the Equation : X(k) = AX(k-1) + BU(k-1) + W(k-1). the Matrix A is not a constant(time-variance) . So, can I still use the kalman filter? or I could use some non-linear method. Thank you.
Thank you yh Zhang. The typo has been corrected now. It may take a few days to be online.
Hi, YI Cao, I have found a bug in your tutorials, when I want to send the bug to your email address, but all were were be rejected.
the formula(5) Kk = Pk|k-1 * C^T * Sk^-1 ( Change A to C)
This is a great tutorial about Kalman filter, since there are many articles on the "matlab file exchange" talking about kalman filter. Your tutorial had made a summary and a survey which is very important for the beginners like me. Also, you add your some news view of kalman filter. Thank you very much!
Inspired by: Learning the Kalman Filter in Simulink v2.1
Find the treasures in MATLAB Central and discover how the community can help you!Start Hunting!