It appears to be more a theoretical work, as far as they had published several scientific papers on the topic. I doubt it may have any practical implementation in low-cost VNA FW code.
Their last paper about 2-port systems analysis might trigger some discussion on the topic, but the subject seems too complicated to dive deep into details
I tend to agree with some of the comments posted in that chain. It would have been very helpful had they started with a clear description of the problem they are trying to solve. This should have been able to be boiled down to a paragraph.
Minimize the errors introduced by existing known models. Provide an approach that allows the error model to run more efficiently. Decouple the error model from the hardware used. As an example. I'm not suggesting these align with their goals.
One person was attempting to follow along which has helped me. Several pages into it, they still seem unsure what the goals are, which is my take when reading it.
With their emphasis on the NanoVNA, I would assume the are suggesting their models offer some benefits. At least for the single port error model they presented, it would be easy enough to experiment with.
I use this as base for calibrations.
Also add calibration standard suport, for this part i use various sources.
I had to deduce some formulas myself and optimize the calculations. Since initially they were very cumbersome for calculations (a large number of calculations in complex numbers is quite resource-intensive for the microcontroller, especially since hardware support for floating point numbers is disabled in V2/V2Plus/V2Plus4, since not all GD32F303 processors have this module. The processor in Lite is faster and there support is always on).
For thru calibtaiton most good result show ISOLN/THRU calibration as on H/H4. It allow good remove leakage from measured data.
Thanks for the post. Did you choose to follow their work because of it requiring less resources (memory, CPU...), or did it provide a more accurate result? Both? If you tried other methods when making the choice what model to use, I would be very interested in seeing any metrics you collected along the way.