you can find the first chapter of Maybeck's book on the web (pdf warning)
www.cs.unc.edu/~welch/media/pdf/maybeck_ch1.pdf

You can get bogged down for years in this subject.  When I want to do
something quick and dirty, I use a least squares filter.  I think
that's in Maybeck's first chapter, but I forget.  The truth is, in
most real applications the gains are tuned by human intuition until
the filters work.
Eric


On Wed, Aug 17, 2011 at 4:18 PM, Dave <[email protected]> wrote:
>
> I have an application that I believe could greatly benefit from a Kalman
> Filter.    Kalman filters are oftentimes used for guidance systems and
> that is what I need it for - except that I am guiding a boat!
> However the same filter I understand can also be used to predict
> (estimate) velocity and position based upon what would normally be
> considered incomplete information.  One example I heard what that a
> Kalman filter can
> be used to predict velocity when used with low count encoders - as in
> low count encoders used on servo motors.
>
> If you do a look up of "Kalman filter" on Youtube you can get an idea of
> their flexibility.
>
> Does anyone have any experience with Kalman filters?    I have searched
> the web for a simple explanation and John Crenshaw of embedded magazine
> started a series of articles in the March 2011 edition  (sort of a
> Kalman filter for dummies) but he stopped short of publishing the second
> article which gets into the actual filter software explanation.
>
> I found a "primer" on the web that I downloaded.  It is a PDF document
> that is 189 pages long!
>
> Where do I start with this??
>
> I get the feeling that if I just grab some source code and implement
> something it won't work since the filter has to be "setup" to allow the
> software to properly predict or estimate a value.
>
> Thanks,
>
> Dave
>
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