Credits: UAS Vision
For the first time, Australian researchers reverse-engineered hoverfly’s’ visual capabilities to identify
drones’ audio signals from over four kilometres away.
The findings were published in The Journal of the Acoustical Society of America, and they might assist tackle the expanding worldwide threat presented by IED-carrying drones, particularly in Ukraine.
Trials utilizing bio-inspired signal processing techniques reveal up to a 50 percent greater detection rate than previous approaches, according to autonomous systems specialists from the University of South Australia, Flinders University, and defence company Midspar Systems.
According to Anthony Finn, a UniSA Professor of Autonomous Systems, insect vision systems have been mapped for some time to enhance camera-based detections, but this is the first time bio-vision has been applied to acoustic data.
“Bio-vision processing has been shown to greatly increase the detection range of drones in both visual and infrared data. However, we have now shown we can pick up clear and crisp acoustic signatures of drones, including very small and quiet ones, using an algorithm based on the hoverfly’s visual system,” Prof Finn says.
Dr Russell Brinkworth, Associate Professor in Autonomous Systems at Flinders University, believes that being able to see and hear small drones from a greater distance could be extremely useful for aviation regulators, safety authorities, and the general public in monitoring the ever-increasing number of autonomous aircraft operating in sensitive airspace.
“We’ve witnessed drones entering airspace where commercial airlines are landing and taking off in recent years, so developing the capacity to actually monitor small drones when they’re active near our airports or in our skies could be extremely beneficial towards improving safety. The impact of UAVs in modern warfare is also becoming evident during the war in Ukraine, so keeping on top of their location is actually in the national interest. Our research aims to extend the detection range considerably as the use of drones increases in the civilian and military space.”
Bio-inspired processing boosted detection ranges by 30 to 49 percent compared to standard approaches, depending on the type of drone and the conditions.
At short to medium distances, researchers hunt for particular patterns (narrowband) and/or generic signals (broadband) to pick up drone acoustics, but the signal is weaker at greater distances, and both methodologies fail to generate consistent findings.
Similar circumstances can be found in nature. Researchers explain that while dark light areas are incredibly loud, insects like the hoverfly have a very sophisticated visual system that can collect visual signals.
