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.)
So I think I’m borderline resolving the continental drift signal with $50 of hardware under a roof.
@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?”
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