Python, C++, and CUDA. github.com/Ttl/torchbp

SAR image is processed offline. It's just a hobby project.

It's 10 seconds of data (10,000 radar pulses) and it takes about a minute to process.

I also implemented generalized phase gradient autofocus earlier this week. I haven't seen any open source implementations of it before. It works quite well with this kind of short range SAR image, but my earlier minimum entropy optimization method still gives better results.

Just some random ones I had lying around. The bigger one is labeled: "XRRH6*10*3"

That's the measured S21 from input to the isolated port when the other ports are terminated. Reflection of the termination is not de-embedded, but it's better than -25 dB over the whole frequency range.

It works really well. Loss is low and matching is excellent.

It would require hole and threads in the case for the connector making the case more expensive. Connector would also need to be soldered to the PCB while attached to the case, not very handy for a prototype.

It's this one: www.aliexpress.com/item/1005006.... Calibration coefficients are not included.

It's a very nice looking chip, but too expensive. Sure if someone else pays.

That could work in some situations, but I don't think it will work here. The connection between SMA connector and the case is not tightened so it wouldn't be compressed. Mating surface also isn't a full circle, just the upper part of the connector.

I thought this might be an issue during design. The proper fix would be to use a bulkhead SMA connector but that complicates the mechanical design and I didn't think it was worth the trouble.