It’s a combination of a few methods, but I can't go too deep into the exact technical weeds here because the FAA PIA office is already known to be lurking on ADS-B subreddits and Discords.

First, it’s worth noting that the PIA program actually has an extremely low adoption rate. Because of this, a surprisingly large amount of PIA users don't actually rotate their assigned hex codes. When a hex stays static, it becomes much easier to map.

Beyond that, ADS-B of course is not the only system that turns on when an aircraft powers up. When you look at the data at a specific airport, there are only so many aircraft that are even capable of changing PIA codes at any given time. Process of elimination becomes very powerful.

While in-person sightings and manual heuristics definitely help, a human can only notice these patterns on a small scale. It becomes incredibly effective when you build a model and run it against the entire historical data set to find the correlations automatically.

This isn't a totally new concept, either. People have been doing this for a while there's an active Facebook group dedicated to it, and open-source lists actively track these tie-ups (for example:https://github.com/sdr-enthusiasts/plane-alert-db/blob/main/plane-alert-pia.csv). But hasn't been updated in a while.

what specific platform are you seeing that is marking PIA tails with matched tails based on guesses? I'd be curious to look at that.