Kalman filtering for beginners

The inner workings of the Kalman filter are derived. No optimization nor matrix algebra is employed.

For the very beginners. Only basic understanding of the concept of a probability density function is required. This is my way to introduce students to the information fusion performed in the Kalman filter. My recommendation is to read this handout prior to exploring my models on KF/EKF for DC and AC speed-sensorless drives. Enjoy!