Yes, if it only needs to work at single frequency. Optimal plating thickness is about 1.57 times skin depth. Of course it would be much worse at lower frequencies than the design frequency.

The peak is caused by reflection from the internal boundary. With non-conductive material the reflection is maximized and the peak is the highest.

This 55 A drone ESC has three nice looking SMD busbars to handle the high current.

If worse conductor is plated on top, the effect is opposite. The effective conductivity of the layered metals can be worse than thick bad conductivity metal.

With 1 µm copper plating on thick nickel, the effective conductivity is better than if the trace was made fully from copper.

Did you know that adding a thin plating of good conductor on badly conductive material in RF transmission line can have lower loss at RF than trace made fully of either material by itself? Thought this was a bug in my solver at first, but it's a real physical effect.

2D Transmission Line Field Solver 2D transmission line field solver

Browser based 2D field solver I've been writing for a while is now up. It calculates characteristic impedance and losses for many common and less common transmission lines.

I've been writing online transmission line field solver for a while. It will calculate impedance and loss for many PCB transmission lines. Supports solder mask, S-parameter export and more. Missing just last polishing and testing.

Radar Backprojection Image Formation Synthetic aperture radar backprojection image formation simulator working in your browser

Quick weekend project: Online radar image formation simulator that works in your browser.

Vivaldi antenna on FR4 PCB with corrugations and director.

Measured S11

Made this simple Vivaldi antenna. It's designed to work from 5.5 to 6.0 GHz and matching looks good at that band.

This is getting quite expensive for a hobby project.

GitHub - Ttl/torchbp: Fast C++ Pytorch extension for differentiable synthetic aperture radar image formation and autofocus library on CPU and GPU Fast C++ Pytorch extension for differentiable synthetic aperture radar image formation and autofocus library on CPU and GPU - Ttl/torchbp

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

Synthetic aperture radar autofocus and calibration 3D trajectory position error estimation autofocus, antenna pattern normalization, and polarimetric calibration for drone mounted SAR radar.

New blog post: Synthetic aperture radar autofocus and calibration.

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

Synthetic aperture radar vs Gopro.

Uncalibrated SAR image

Same image after antenna pattern normalization and polarimetric calibration.

Wrote code for SAR image antenna pattern normalization and polarimetric calibration (channel imbalance and crosstalk). Image looks very nice now.

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

Polarimetric synthetic aperture radar image

Camera photo of the same area.

I implemented a new SAR autofocus algorithm and now the image generation is both better and faster. It's about as well focused as it can be now.

Fixed some bugs in my SAR processing code and now fast factorized backprojection generates a visually identical picture to the normal backprojection, but over 10 times faster. That's huge because normal backprojection was already extremely quick and there's still room for optimization with FFBP.

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.

Global backprojection vs fast factorized backprojection image quality. The biggest difference is larger sidelobes on the brightest target in the FFBP image.

Found motivation to write some SAR processing code. Fast factorized backprojection generates several small polar format images and then interpolates them to one big image. It's faster, but has slightly worse image quality due to all the interpolations.

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.

Dual directional bridge coupler PCB.

Thru, coupled, and isolated port S21 with other ports terminated.

I made this new dual directional bridge coupler using 1 mm diameter coaxial cable. It's a little bit better than the previous one I made using 2 mm coaxial cable and much more annoying to solder.

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

Bought this thru with 3.5mm RF connectors. It's air filled with just a thin see-thru membrane holding the center pin in place.

Two test PCBs with 3.5 mm and SMA connectors

3.5 mm connector close up

3.5 mm and SMA connector S-parameters with 11 mm line

3.5 mm and SMA connector time domain response with 11 mm long line

Some new RF connector test PCBs. Nameless low-cost solderless 3.5 mm connector on the left and CONSMA003.062 clone on the right. Both work okay.

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.

Bought this VNA calibration kit with 3.5 mm connectors. Looks good considering the 60€ price tag.

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