[PD] Simple Kalman filter

Joel Matthys jwmatthys at gmail.com
Thu Feb 28 23:31:34 CET 2013

Well, understanding the math of a Kalman filter was way beyond my pay
grade, but based on the description in
http://bilgin.esme.org/BitsBytes/KalmanFilterforDummies.aspx, a 1d
implementation reduces the complexity considerably. According to this
guide, we can assume simple float values for most of the coefficients for
most purposes.

Based on your suggestion, I think I will incorporate an "analyze mode" into
the external itself to calculate the noise parameters and set them
automatically. I'll let you know when that's in git.

On Feb 28, 2013 5:05 PM, "Charles Z Henry" <czhenry at gmail.com> wrote:

> Hey Joel
> I was very interested to see your implementation.  It's drastically
> simpler than I thought it would be.  Well, you did mention it was simple
> :)  However, I thought the math was pretty expensive to do and complex to
> program.
> I like the approach generally--you have parameters for the assumed noise
> model and methods to set them (better than trying to build a monolith that
> does both the measurement and filtering).  Do you have another patch or
> abstraction to analyze the sensor data and calculate those parameters?  If
> so, you should add it to git.
> Chuck
> On Thu, Feb 28, 2013 at 12:47 PM, Joel Matthys <jwmatthys at gmail.com>wrote:
>>  I just completed a very simple 1D Kalman filter Pd external. I haven't
>> really done any documentation on it, but it seems pretty robust for
>> cleaning up 1D sensor inputs.
>> The source is here:
>> https://github.com/jwmatthys/kalman-pd
>> Joel
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