I built a mmWave material classification radar

(gauthier-lechevalier.com)

64 points | by GL26 2 hours ago

9 comments

  • jcims 7 minutes ago
    Very cool idea.

    I'm sure this can be annoying when people do this, but I can't help myself lol. I wonder if you could operate in a different modality and find discontinuities in material properties rather than use it as a classifier. For some reason skin cancer detection popped into my head, but general purpose inspection/detection cases for any discontinuities might be pretty helpful. Depending on the resolution/size of the field it's inspecting a realtime camera overlay might be interesting for correlation sake.

    • GL26 2 minutes ago
      the FMCW tech makes it impossible to have a resolution inferior to 2.5 cm, (so if two layers are appart, you can't physically tell them appart using physical classical modeling techniques with DSP). However, you can use AI to enhance the performance of the system, and make what you are saying possible. The downside of AI is that you need tons of data, which is expensive to get.
  • amirhirsch 1 hour ago
    Very cool! Six years ago I worked on a mmWave (76-81GHz) imaging radar with a Rotman lens Tx and Rx. Designed as a LiDAR replacement, but we could see pipes in walls, or detect concealed weapons at ~1km.
    • mlmonkey 1 hour ago
      Do you have a writeup about the project? I'd love to read more about it.
    • GL26 1 hour ago
      How many tx and rx antennas did you have ? (I don’t know if it was clear, my stack was 57-64 GHz, 2TX , 3RX)
      • amirhirsch 1 hour ago
        32 port Tx (vertical pancake beams) x 16 port Rx (horizontal pancake), something like 60 by 30 degrees. the entire thing used FPGA transceivers as one-bit DAC/ADC, Complementary Golay Code waveforms with one-bit correlation in the FPGAs (two VCU128s) -- digital logic was essentially the same as a binarized neural network, I squeezed a ton of popcnt performance out of those chips using both DSPs and LUTs
  • tim-tday 1 hour ago
    So thankful the author posted this. We often learn more from failure than success. Learning from the failures of others is how we can move forward. The lessons learned at the bottom of the article are gold.
    • GL26 48 minutes ago
      thank you so much for your feedback, it was hard to admit defeat, but at the end looking back at what I built, the parts where I learnt about RF, and just struggled, refactoring the code for the sim (thank god cc is not good enough to understand real world physics functionning for now) were the most satisfying moments
    • EtienneDeLyon 46 minutes ago
      Was this AI comment necessary?

      If you'd like to learn more about the module:

      https://www.ti.com/tool/IWRL6432BOOST

  • Havoc 21 minutes ago
    Kinda crazy that it worked but got no commercial interest. Hopefully someone suitable here sees it and can intervene

    Does it also work through other materials. i.e. through a drywall etc.

    • lukeinator42 11 minutes ago
      It's a cool technology, but for it to gain commercial interest it needs to solve a problem better than the status quo. What problem is it solving and for who? If I was to buy that mmwave radar device it would probably cost more than the $60 test, and I would want assurances that it is as accurate as existing tests.
  • nilsherzig 46 minutes ago
    love the background music in combination with the flying fishes wallpaper in the first video haha

    very cool project

    • GL26 22 minutes ago
      hahaha ! oops didn't mute the video, would blast trap music when I was alone in the lab x)
  • JellyPlan 55 minutes ago
    Hugged to death but I'd love to see this!
  • GL26 53 minutes ago
    My netlify crashed fixing the website rn
    • GL26 50 minutes ago
      just fixed it, hope it works
  • arikrahman 1 hour ago
    That's awesome. I built one for a capstone back in the day and know how tough it is to get onboarded. Kudos.
  • marking-time 1 hour ago
    Terrific project!
    • GL26 47 minutes ago
      thanks :) !!