Recently I got into vehicle models and filtering in general and immediately faced with the following question.
I have the recorded GPS data from car driving on a highway. However, there is a substantial level of noise present, so I decided to filter this $(x, y)$ data. Currently I am using Kalman filtering (the extended one - bicycle model of the vehicle is assumed) for this purpose, but I somehow have a feeling that Kalman is more suited for online estimation/filtering. I have also tried various other approaches, including median and Savitzky–Golay filters, but they do not take dynamic model into the account which I think is the important information to use while filtering this data.
So, my question is: Is there an alternative to Kalman filter, where model dynamics can be specified, which is more suited for this purpose?
I just once again want to emphasize that I have solely measured time sequence (fixed interval) with $x, y$ coordinates and data needs to be filtered after drive is over (offline usage).
Thank you for your help and I apologize if my question is not stated well - this is my first post:)