[PD] is there a kalman filter for pd? (if not I could probably provide one, if I make it :) )

[Cyrille Henry]

hello,

i had a look time ago about kalman (1D). from what i remember, this filter is useful if you can model the input signal. if you can't, and use it as a generic filter, then it is not better than a simple 1 pole filter.

in 2D (or more), it should be not very different than a 2D mass-spring network.

this remind me that i have to update physical model filter in mapping and puremapping libs...

cheers
C


Le 17/12/2012 19:17, Pedro Lopes a écrit :
> Got it working, but just realized that some of you need a 1D kalman,
> and I was working on a 2D kalman. A cool version could accept params
> [kalman <dim> <other params>]
>
> Nothing works within pd yet, but lets see if I have time for that. I
> will also play around with some 1D implementations.
>
> best,
> p
>
> On Fri, Dec 14, 2012 at 2:06 PM, katja <katjavetter at gmail.com> wrote:
>> Thanks for the suggestion, Cyrille. I've been playing around with
>> median filters in a different context (spectral processing), but
>> completely forgot about them.
>>
>> With the variometer, the problem is to isolate very low frequencies
>> (the pressure gradient you want to detect) from DC (constant
>> atmospheric pressure at certain height) and sensor noise frequencies.
>> And you want to see results with accuracy and little delay. In fact it
>> needs a very sharp minimum-phase filter. Maybe a median filter can
>> 'preprocess' the signal in some way. Anyway it gives a new
>> perspective.
>>
>> Katja
>>
>>
>>
>> On Fri, Dec 14, 2012 at 1:27 PM, Cyrille Henry <ch at chnry.net> wrote:
>>> for sensors data, depending of the noise, it can be useful to begin with a
>>> median filter.
>>> a median on the 7 last sample add 3 sample delay, but often remove lot's of
>>> noise.
>>>
>>> you can find them in mapping or puremapping libs.
>>> cheers
>>> cyrille
>>>
>>>
>>> Le 14/12/2012 11:38, katja a écrit :
>>>
>>>> Patrick, the barometer sensor samplerate is ~50 Hz and I did the
>>>> butterworth filter with regular Pd objects, not as external (see
>>>> attached).
>>>>
>>>> In the Pd patch I modeled sensor noise (resolution 3 Pascal according
>>>> to datasheet) and pressure gradient, simulating vertical speed through
>>>> the air. The aim is to get 0.1 m/s accuracy in vertical speed reading.
>>>> Theoretically, this would be almost possible with the butterworth. But
>>>> our real sensor has much more noise than 3 Pascal resolution.
>>>> Therefore I'm still interested in better filters.
>>>>
>>>> Katja
>>>>
>>>>
>>>> On Wed, Dec 12, 2012 at 6:29 PM, patrick <puredata at 11h11.com> wrote:
>>>>>
>>>>> hi Katja,
>>>>>
>>>>> did you ported this filter:
>>>>> https://github.com/lebipbip/le-BipBip/blob/master/filter.c
>>>>>
>>>>> to an pd external? if yes could you share it? not sure if it would help
>>>>> my
>>>>> situation (noisy accelerometer 1 axis), but i would like to give it a
>>>>> shot.
>>>>>
>>>>> thx
>>>>>
>>>>>
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