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 <[email protected]> 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 <[email protected]> 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 <[email protected]> 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 >>>> >>>> >>>> _______________________________________________ >>>> [email protected] mailing list >>>> UNSUBSCRIBE and account-management -> >>>> http://lists.puredata.info/listinfo/pd-list >>>> >>>> >>>> _______________________________________________ >>>> [email protected] mailing list >>>> UNSUBSCRIBE and account-management -> >>>> http://lists.puredata.info/listinfo/pd-list > > _______________________________________________ > [email protected] mailing list > UNSUBSCRIBE and account-management -> > http://lists.puredata.info/listinfo/pd-list -- Pedro Lopes (HCI Researcher / MSc) contact: [email protected] website: http://web.ist.utl.pt/pedro.lopes / http://pedrolopesresearch.wordpress.com/ | http://twitter.com/plopesresearch _______________________________________________ [email protected] mailing list UNSUBSCRIBE and account-management -> http://lists.puredata.info/listinfo/pd-list
