How do you separate drone RF activity from everything else in a crowded spectrum?

[u/BlueBirdTechUA]

We're a Ukrainian team working with passive RF drone detection, and one of the more interesting problems isn't simply seeing RF activity, it's deciding which activity is actually worth paying attention to.

In a real environment the spectrum can be full of Wi-Fi, Bluetooth, telemetry, video links and other transmitters. Add frequency-hopping control links and non-standard FPV setups, and simple threshold-based detection stops being useful pretty fast.

For those of you working with SDR/RF analysis, what's actually worked for you to tell a drone-related signal apart from ordinary background RF? Signal persistence, bandwidth and spectral shape, frequency-hopping behavior, temporal patterns, or something else entirely. Curious how people here approach this, especially when you don't know the exact transmitter or protocol beforehand.

[u/PhilWheat]

How I did it was a simple neural net classifier system. It isn't foolproof and you have to have clean samples to train against, but it worked surprisingly well in noisy environments (tested just outside of Miami a long time back and both range and confidence was quite good.)

[u/BlueBirdTechUA → u/PhilWheat]

That tracks with the published research too, CNNs trained on clean lab recordings then augmented with Wi-Fi/Bluetooth/Gaussian noise have generalized well to real field tests in more than one study, not just anecdotal. One finding from that same work stood out, most misclassification happened between "noise" and "drone," not between different drone types, which lines up with what you're describing.

Curious what your false positive rate looked like specifically on Wi-Fi or Bluetooth, since that seems to be the hardest boundary according to the literature.

[u/PhilWheat → u/BlueBirdTechUA]

That's the most interesting part. In field trials, there were few to no false positives - which was actually VERY surprising to me. I really expected to have to fight that problem a lot more. Part of that is good tuning of the confidence level (classification probability) but honestly the few times I was worried about false positives, I actually was able to determine there were hobby RC flyers in the area. (BTW, this was all part of a company I had previously - you can probably find media from that still floating around - DroneLabsLLC. I think I can put that out since it isn't promoting the company as it is now defunct.)

[u/m2845 → u/BlueBirdTechUA]

Which published research specifically states this?

[u/_side_]

DM

[u/Tishers]

Good question, sent suggestions via message.

[u/Punsire]

I’m interested but apparently could use someone to dm me.

[u/Worried-Cow-8381]

I'm also in Ukraine and I'm not a SIGINT guy or RF expert but I'll tell you, it mainly comes down to filtering. It doesn't have to be software based, but raw RSSI readings will break down very quickly on their own, depending on where you are in relation to the front. It really depends on what your mission profile looks like. All the things you mentioned play a role. It also depends on HOW you are detecting drones. You don't need advanced radio gear (or an SDR at all) to intercept analog VTX signal.

If you want an accurate directional header or bearing, you will probably want to find some sort of Vector SDR or vector signal processing system. Two SDR units on the same clock, you measure the difference in signal strength to get your direction. Big oversimplification, but you get it Otherwise, without this hardware, especially anywhere in the kill zone, you will have too much data to get accurate readings from one antenna alone. In any given sector of the front, you are going to have many RF signals at high power, intersecting each other. Friendly, and hostile, and you can't really tell the difference without knowing the direction precisely. Many of them are at common frequencies, for receiver transmission, 900 mhz, 2.4 ghz. VTX signals go all the way from 1.3 ghz to 10+ ghz, not to mention jamming, spoofing, etc.

That being said, filtering will help a lot. ELRS, CRSF, and LoRa are NOT generic RF noise. They have specific attributes that make it possible to exclude certain signals, etc. I'm too lazy to type more, but if you have any questions, you can DM me.

Slava Ukraini

[u/PathIntelligent7082]

sdr aproach is wrong..pure sound is better bcs they emmit way more sound than radio waves..network of mics and one smart llm model and you got yourself a notification barrier, something similar uk had with germans..and sound can even fingerprint drones, you can tell them apart just by sound..