Agreed; ML doesn't make sense to me in the context in which they present it. Seems like they just crammed in a buzzword there.

Later in the report, it says this:

    One proposal is to use advanced algorithms to 
    search historical data captured and stored by radars

They do not mention ML in that context, but it seems like a more promising way in which they might usefully employ it.

144 _reported_ incidents. They also talk about how some of the cases going unreported. It would make sense to sieve through the radar data (I'd guess all the ATC radars are being recorded, because why not?) to look for those.

Most ATC now uses secondary radars. Those generally only pick up aircraft carrying transponders.

Good point. What about the radars used by Air Force to guard the airspace? Do they cover the interior, or only the borders?

Secondary radar == just an RX only antenna?

Transmitter also, but not powerful enough to get a useful return from an aircraft without a transponder at any significant range.

Yep that's fair enough. And satellite imagery too I guess.

ML/AI/"algorithms" are the buzzwords of the day in the public and private sectors right now.

I think one proposal is to have advanced wide-field cameras placed in "locations of interest". This would be much like an optical observatory and would generate petabytes of data.

Do you have more details on this or a source? I’m curious!

This program (FRIPON) https://www.aanda.org/articles/aa/full_html/2020/12/aa38649-... was cited here https://www.3af.fr/global/gene/link.php?doc_id=3695&fg=1 as a candidate for repurposing for UAP detection. I'm not familiar with the legitimacy of the 3af french org, so perhaps should be taken w/ a grain of salt?

Interesting!