Garmin Filters or Kalman Filters

Hello people, 

I ran a few experiments on calculating displacement using the accelerometers only, and to no surprise the reading, and the calculated displacement never matched the actual displacement, I suspect due to noise.

I tried to remove as much noise as possible by moving the watch stationary, vertically up a wall to a height, and then back down again to the start position.

Has anyone use the filter features in the Math class with success to filter accelerometer noise?

And, it looks like the IIR filter is or can be setup similarly to a Kalman filter since it has fed forwards filters?

Has anyone used it like this, or am I better off just setting up a stand alone Kalman?

Initially I am hoping to remove the higher frequency noise, but possibly also minor hand motion in a later step

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  • yes I check the example but have had some difficulties to understand how it works !.

     as for the tool for FIR parameters, I have had great difficulties to match what those tools output to what garmin need !

  • Hi, I fully understand, during my studies we culculated the filter parameters in detail, but I had difficulties to remember (was not my favour subject :| )

    You need to know how the characteristics of sensor are to filter out noise successfully. In my perspective, the FIR coefficients are ok to filter out (I think Garmin knew what they did as they distributed the example), and this was your question originally. You should play around the thresholds defined in the example, which is for identifying strokes out of the filtered data.

  • well, since it's a long time I've tryied that, maybe I will go and take another look !