"Curtis L. Olson" <[EMAIL PROTECTED]> wrote:
> Martin Spott wrote:
>> With other words: Kalman filters enable you exact guessing of the
>> picture where mathematical equations don't do the job because you have
>> too many unknown parameters compared to the number of input sources.
>> I believe the autopilot mailing list archive contains a lot of useful
>> explanations to kalman filtering,

> I'm probably wrong, but I got the impression that maybe one person over on 
> the autopilot list (Aaron?) understood Kalman filters well enough to 
> actually impliment them in a real world system. :-)

I dont't think you're wrong  ;-)

> I like your explanation better than mine though, except I'm not sure about 
> "exact guessing."  Maybe I would say "good/best guessing" about the future 
> given noisy and changing inputs, and some knowledge about the error 
> tolerances of the guess.  And like you say, the guess is much better than 
> you could generally get with a simple mathematical relationship.

More than that. I did a lot of 'research' on my own to build a cheap
AHRS (Autonomous Heading and Reference System) over the years (for the
tilt rotor project). I had the aim to generate a system that gets a
"red button" for the pilot. In case the pilot hits this button the
aircraft would stop immediately and remain at the current position.

You can build a pretty cheap system to determine the direction of
gravity using a handful piezo acceleration sensors - as long as you
don't neet to take horizontal acceleration into count. You can easily
build a system that tells you the horizontal acceleration - as long as
your aircrafts z-axis is parallel to the direction of gravity. You
definitely can't resolve this with mathematical equations (I believe i
know a bit about solving complex mathematical equations) and I have the
impression that this is the point where kalman filters come into play,

Martin.
-- 
 Unix _IS_ user friendly - it's just selective about who its friends are !
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