Re: Glitch/inconsistency detection in navigation data


Marcel Müller wrote:
However, the data might contain glitches (jumps) or other
inconsistencies
that need to be sorted out before feeding them to the Kalman filter.

It depends on what you call a glitch.

If you are talking about several non-plausible points, try to check
agains physical constraints like maximum velocity (1st derivative) or
maximum acceleration/deceleration (2nd derivative). However, in any case
you need the time. So either delta-t between two points must be always
the same or you need tuples of {x,y,z,t}.

I am aware that at least certain Kalman filters exploit that kind of
prior information. I tend to try and use as little prior info as
possible,
and rather use signal statistics. But if we in the end have to go
the physics route, then so be it. I'll just like to explore statistics-
only first.

Rune

.