On 12/17/2014 05:07 PM, Keith Packard wrote:
> Effectively yes, but each of these are done in the context of the
> physical model which is the predictive part of the Kalman filter. A
> Kalman filter is a way of estimating the state of a hidden Markov chain
> using noisy sensors along with a model of the Markov system
> itself. We're running predictive Newtonian model of the rocket assuming
> a constant acceleration (which is a good estimate near apogee), and then
> constantly correcting the model based on sensor input.


I would be interested in learning more about the above from a
theory/math (not coding) point of view. Do you have a list of resources
that would be a good starting point?

Thanks

Steve

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Steven Saner <[email protected]> KD0IJP
Andover, Kansas USA
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