Last summer, I got a couple of these little USB GNSS chips, a notch above the usual consumer quality but a notch (and $200) below the RTK-capable kind: https://mou.sr/4hrR4PY
One of them has been sitting on the top of the curtain rod over my desk, carefully wedged in place with magnets and a makeshift ground plane.
Its output goes straight to a postgres database on a small always-on computer. Its SSD failed a few months ago, so I lost a chunk of data, but basically it’s just recording the chip’s output. Under my roof, you might note.
But it’s been a year, so I tested the main thing I wanted to see. If I aggressively remove outliers, average across long time periods, and eyeball a few load-bearing parameters just right – so I want to be clear that I’m not claiming rigor, only that it’s good enough for me personally – the data shows a velocity of 27.5 mm/year west, 14.4 mm/year north. (This is on the order of 1 nanometer/second.)
This makes me happy because it’s pretty comparable to the trend from a nearby science-quality GNSS receiver: https://sideshow.jpl.nasa.gov/post/links/EBMD.html
@vruba what’s that discontinuity in 2016?
@migurski I suspect hardware maintenance but I’m not sure.
@vruba Very cool! If you transform the data points with PROJ from their observed epoch to a standard epoch (e.g. ITRF2014@2010) do they all line up?
@dmahr That’s a great question and probably actually a good way to explain this one day when it’s more complete: “See how this distribution, in naïve WGS 84, is visibly stretched compared to this other distribution that knows about drift?”
So I think I’m borderline resolving the continental drift signal with $50 of hardware under a roof.