I am new to Kalman filter and am enjoying playing with it. However, I generated some random velocities and acceleration and Kalman filter (with the covariance matrices I have chosen) is comparable with lowpass filtering.
So I thought maybe both lowpass filtering and Kalman filter could be combined, however this completely ruins the assumption of white Gaussian noise. My numerical experiments indicates that Kalman filter does not bring anything interesting after LP filtering for the cases I tried.
What are good preprocessing practices, if any, before applying a Kalman filter?