I have a set of data for a car position, velocity and acceleration.
% my data
time
car_x
car_velocity
car_acc
The problem is that these arrays have error and I need to fix the error of them. The requirements is that
There are unreasonable error bumps on my car position according to the photo. These bumps cause unnecessary jags on acceleration. An idea is to use a low-pass filter on car position however, low-pass filter deforms my signal when a real sudden change happens.
At the same time, when we calculate the double derivation of the position it should not be very far from the original
car_accsignal.
How to implement such filtering?
Note:
currently due to errors, the double integral of acceleration diverges from the position in an unstable way (two times integration of a small error diverges over time).
I tried many corrections on car position and made it nice. However the double derivation of it had very high frequency oscillation with high amplitude.
