Hi @GavXYZ,
I’ve moved this here because I think it deserves its own topic.
As some insights from my understanding:
It’s the same hardware, and both firmware versions have the same features and communicate using the same protocol, so it’s not that one is dumber per se, just that it doesn’t maintain as high a level of accuracy.
Accuracy reduction could be achieved by adding random noise, or rounding/truncating every measurement to fewer significant figures.
My understanding is that it applies to the velocity data (which is the primary output of a DVL), and since Water Linked describe it as “long term accuracy” I assume it refers to the average velocity error for several measurements taken over an extended period of time.
As an example of that, if the DVL takes 5000 measurements during a dive then some of them could individually be incorrect from the true velocity by more than the long term accuracy amount, but in aggregate they should average out to be within it.
I would expect that to also be reflected by the “figure of merit” (e.g. \sum_{i=1}^n\frac{fom_i}{|\vec{v_i}|\cdot n}\leq accuracy_\text{stated}), although that’s not guaranteed, and it’s not guaranteed that measurements with a low figure of merit are correct - they’re just higher confidence, as expressed by the device.
Unfortunately that’s not a possible relation to make because even with completely accurate instantaneous velocity measurements there is still time between the measurements where the velocity can change, as well as error in the IMU’s sensors, and both of those get integrated over so the vehicle’s position estimate error is technically unbounded.
From a practical perspective that error growth can be subdued to some extent by taking measurements at a higher frequency (so when the DVL is close to the surface it’s measuring off then the position estimate error should grow less quickly), as well as by avoiding known sources of noise and uncertainty (e.g. having a significant amount of inertia reduces the velocity change between measurements, while going near large metallic structures can cause issues with a compass, which can throw off the heading estimates, and operating over a soft or very jagged bottom surface can make it harder for the DVL to get a strong lock and accurate measurements).
Fundamentally though, any estimate that is determined through integration over measurements will eventually grow a significant “drift” error unless it has some external reference that can correct it, even if only occasionally (e.g. for positioning that would generally be through a surface GPS or USBL/UGPS system of some sort, or through manually specifying the vehicle position based on some external GPS reading (like is normally done at the start of a DVL dive, to set the starting location)).