[jcims]

To an extent, but depending on the sampling rate and frequency and your ability to control the area being observed, there is still a lot of information available for modeling and biometric identification. In the extreme you can detect things like heartbeat, rate of breathing, etc.

For example, I have a CDM324 24Ghz radar module here on my desk. I set it up to 'watch' me type this comment from across the keyboard. This is an extremely simple module that I have powered by a bench power supply and the IF routed directly to the audio input on my desktop. It was sampled with audacity and amplified a bit to help with visibility. Towards the end of the recording I'm expecting a flat spot followed by regular motion followed by 'noise' as I pause motionless for ~10 seconds or so, then take about 5-6 exaggerated breaths, then resume typing.

This is with zero design, the wrong frequency for the job, and next to zero signal conditioning.

(post: i've included a zoomed in image of the 'motion demonstration' to show still/breathing/typing, then zoomed in on typing to show the detail, then a spectrogram and waveform of me reaching up to scratch my ear.)

https://imgur.com/a/0JmENYu

Bonus: yo check out my soundcloud - This is what the doppler signal actually sounds like:

Scratching my ear - https://soundcloud.com/buckrunner2/scratch

Talking directly at the module - https://soundcloud.com/buckrunner2/talking

[AdamH12113]

“Privacy” seems to be a marketing term here; what they really mean is that you can’t take naked pictures with it.

[samatman]

Which is also nonsense of course, the pornotron of TSA fame is mm wave radar.

[krasin]

The difference is the number of transmitters / receivers. TSA uses an array of them (from top to bottom) with narrow beams and they also rotate them and ask you to not move, so that effectively their number is considerably higher (ten of thousands), when reconstructing the image. Additionally, they use a higher frequency (160-400GHz), which additionally helps with resolution. See [1] and [2].

If we limit the number of transmitters / receivers to 3/4, the image reconstruction becomes impossible, similar how you would not really make a real photo from a few color sensors stationary looking at a scene, while a linear array of them that moves around an object would make a perfect scanner. It's a non-ideal analogy, but the best I can offer.

1. http://mt-fedfiles.blogspot.com/p/tsa-frequency-updates.html

2. https://www.3dbodyscanning.org/cap/papers/2017/17263mcmakin....

[visarga]

You can reconstruct the images with neural networks even if you have little signal to guide.

[akimball]

This is true in the sense that NNs offer a convenient way to estimate a distribution of hidden values conditionalized upon visible values. That is an approximation of what is usually understood by "a reconstruction". I would argue that a reconstruction per se would only include parts for which the credible interval could be systematically bounded within a suitable tolerance threshold.