These are chat archives for rlabbe/Kalman-and-Bayesian-Filters-in-Python

Jan 2018
Roger Labbe
Jan 29 21:39
@maluethi , sorry, I haven't logged in here for a long time.
I intend to add a section on just this topic in a few day. In the meantime, I suggest looking up 'mahalanobis distance', which is a measure of how far a measurement is from the KF's prior. You can use this to 'gate' your data - discard data that is "too far away". Theory says throw away anything > 3 std, but in practice you may find 4,5, even 6 std to be a better gating distance
If you throw the data away, you just don't call update for that time period. You will thus call predict twice in a row, and your estimate will gain uncertainty because you did 2 predictions in a row
that's the general idea. The search term "kalman filter gating" is also a fruitful search.