Forget DJI’s Aeroscope and other drone tracking applications, as [mks_highlight color=”#ffff00″]Artificial Intelligence (AI)[/mks_highlight] may be all that is needed to pinpoint a drone pilot’s location.
Mark Anderson writes for IEEE Spectrum:
[mks_highlight color=”#ffff00″]Gera Weiss[/mks_highlight], professor of computer science at the Ben-Gurion University of the Negev in Beersheba, Israel commented that his research team tested their drone tracking algorithm using Microsoft Research’s open-source drone and autonomous vehicle simulator [mks_highlight color=”#ffff00″]AirSim[/mks_highlight]. The group presented their work at the Fourth International Symposium on Cyber Security, Cryptology, and Machine Learning at Ben-Gurion University earlier this month.
The minute[mks_highlight color=”#ffff00″]details[/mks_highlight] of rogue [mks_highlight color=”#ffff00″]drone’s movements[/mks_highlight] in the air may unwittingly reveal the drone pilot’s location—possibly enabling authorities to bring the drone down before, say, it has the opportunity to disrupt air traffic or cause an accident. And it’s possible without requiring expensive arrays of radio triangulation and signal-location antennas.
So says a team of [mks_highlight color=”#ffff00″]Israeli researchers[/mks_highlight] who have trained an AI drone-tracking algorithm to reveal the drone operator’s whereabouts, with a [mks_highlight color=”#ffff00″]better than 80 percent accuracy level[/mks_highlight].
Depending on the specific terrain at any given Airport, a pilot operating a drone near a camouflaging patch of forest, for instance, might have an unobstructed view of the runway. But that location might also be a long distance away, possibly making the operator more prone to errors in precise tracking of the drone. Whereas a pilot operating nearer to the runway may not make those same tracking errors but may also have to contend with big blind spots because of their proximity to, say, a parking garage or control tower.
And in every case, he said, simple geometry could begin to reveal important clues about a pilot’s location, too. When a drone is far enough away, motion along a pilot’s line of sight can be harder for the pilot to detect than motion perpendicular to their line of sight. This also could become a significant factor in an AI algorithm working to discover pilot location from a particular drone flight pattern.
The sum total of these various terrain-specific and terrain-agnostic effects, then, could be a giant finger pointing to the operator. This AI application would also be unaffected by any relay towers or other signal spoofing mechanisms the pilot may have put in place.
The team claims an [mks_highlight color=”#ffff00″]accuracy rate of 83%[/mks_highlight] in discovering the drone pilot’s location. You can read the entire article here.
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