Drones are getting more stealthy, and detection technology is struggling to keep up. Scientists turned to hoverfly brains for help

Last week, a Russian-made drone reportedly carrying an “air bomb” flew at least 560 kilometers over Croatia, Hungary and Romania – all members of NATO – entirely undetected by air defenses.

It was just the latest urgent reminder that as drones get more stealthy, drone detection technology is struggling to keep up.

At the same time, the war in Ukraine has shown us the power of drones, visible in the grainy birds-eye videos of missile strikes on Russian tanks.

In recent years, cheap and easily available drones have shut down entire airports and even been used in assassination attempts on national leaders.

This has fired global interest in new and better ways to detect these tiny flying machines.

Now researchers from the University of South Australia and Flinders University are reporting a marked improvement in detection ranges, thanks to an unlikely source: the hoverfly.

By painstakingly measuring and modeling the neurology of the hoverfly’s vision system, they’ve built an algorithm that extends detection ranges by up to 50 per cent, the researchers say.

The findings were published in The Journal of the Acoustical Society of America.

How do you map a hoverfly’s brain?

Very slowly, and with a very sharp electrode.

For well over a decade, Russell Brinkworth, an expert in autonomous systems at Flinders University, has been assembling a model of the hoverfly’s brain. But why the hoverfly?

“Flies are much smaller and less complicated than people,” he said.

Flies’ aeronautical flair partly rests on their rapid visual processing of the world around them.

Though their brains are small, each one still has a million neurons.

And these neurons are in turn tiny – smaller than can be resolved under a light microscope.

“They’re smaller than you could possibly see,” Dr Brinkworth said.

To map the brain, the researchers used a probe that had to be even smaller than a neuron, and could only record the activity of one neuron at a time.

Over many years, Dr. Brinkworth and his colleagues shined lights in flies’ eyes and recorded the response of individual neurons.

Eventually, they had a mathematical model of how hoverfly brains process visual signals, said Anthony Finn, an expert on sensor processing at the University of South Australia.

“Essentially what we’re talking about here is an algorithm,” he said.

How to find a drone 4km away

This bio-inspired model proved to be better than existing ones at processing and making sense of visual signals, from resolving glare and finding objects in scenes that are very bright or very dark, to discerning targets against cluttered backgrounds, Professor Finn said.

The next step was to see if the visual model worked with acoustic signals.

“We took the signal processing concepts of the vision system and then applied them to the acoustic area,” he said.

“Instead of processing, say, an individual pixel, you are processing an individual frequency channel.”

The algorithm worked just as well on acoustic signals.

“That was really surprising, even to us who thought it should make a difference,” Dr Brinkworth said.

In one instance, they were able to detect and locate a drone 4km away.

They saw the same 50 per cent improvement when using the algorithm to process visual and infrared signals.