I actually found it to be such a pain in the ass to tune, it didn't even seem that great on iPhones with plain old GPS compared to a hacky bundle of heuristics. I left the code on github because why not, and it turned out over the years people have used it for various things.
GPS already use a Kalman filter to create a filtered output. You cannot apply a second filter to the output of the first and expect better results.
Specifically, the Kalman filter depends on the data having the Markov property, and that the noise is Gaussian. The output of the filter has neither property, so you are not going to get better data. You may "smooth" the data, but all you are really doing is 1) discarding useful information, and/or 2) introducing a lag into the signal.
