Hoverfly brains mapped to detect the sound of distant drones

Date:
March 15, 2022
Source:
University of South Australia
Summary:
Researchers have reverse engineered the visual systems of hoverflies
to detect drones' acoustic signatures from almost four kilometers
away. The finding could help combat the growing use of IED-carrying
drones, including those used in Ukraine.



FULL STORY ==========================================================================
For the first time, Australian researchers have reverse engineered the
visual systems of hoverflies to detect drones' acoustic signatures from
almost four kilometres away.


========================================================================== Autonomous systems experts from the University of South Australia,
Flinders University and defence company Midspar Systems say that trials
using bio- inspired signal processing techniques show up to a 50 per
cent better detection rate than existing methods.

The findings, which could help combat the growing global threat posed
by IED- carrying drones, including in Ukraine, have been reported in
The Journal of the Acoustical Society of America.

UniSA Professor of Autonomous Systems, Anthony Finn, says that insect
vision systems have been mapped for some time now to improve camera-based detections, but this is the first time that 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.

The hoverfly's superior visual and tracking skills have been successfully modelled to detect drones in busy, complex and obscure landscapes,
both for civilian and military purposes.



========================================================================== "Unauthorised drones pose distinctive threats to airports, individuals
and military bases. It is therefore becoming ever-more critical for us to
be able to detect specific locations of drones at long distances, using techniques that can pick up even the weakest signals. Our trials using
the hoverfly-based algorithms show we can now do this," Prof Finn says.

Associate Professor in Autonomous Systems at Flinders University, Dr
Russell Brinkworth, says the ability to both see and hear small drones
at greater distances could be hugely beneficial for aviation regulators,
safety authorities and the wider public seeking to monitor ever increasing numbers of autonomous aircraft 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." Compared with traditional techniques, bio-inspired
processing improved detection ranges by between 30 and 49 per cent,
depending on the type of drone and the conditions.



========================================================================== Researchers look for specific patterns (narrowband) and/or general signals (broadband) to pick up drone acoustics at short to medium distances,
but at longer distance the signal is weaker and both techniques struggle
to achieve reliable results.

Similar conditions exist in the natural world. Dark lit regions are very
noisy but insects such as the hoverfly have a very powerful visual system
that can capture visual signals, researchers say.

"We worked under the assumption that the same processes which allow small visual targets to be seen amongst visual clutter could be redeployed
to extract low volume acoustic signatures from drones buried in noise,"
Dr Brinkworth says.

By converting acoustic signals into two-dimensional 'images' (called spectrograms), researchers used the neural pathway of the hoverfly
brain to improve and suppress unrelated signals and noise, increasing
the detection range for the sounds they wanted to detect.

Using their image-processing skills and sensing expertise, the
researchers made this bio-inspired acoustic data breakthrough thanks
to Federal Government funding through the Department of Defence's Next Generation Technologies Fund The funding partly supports technological solutions to address the weaponisation of drones which are now among
the deadliest weapons in modern warfare, killing or injuring more than
3000 enemy combatants in Afghanistan and being deployed in the current
war in Ukraine.

A video explaining the technology can be viewed here: https://youtu.be/ zAmiyaDH5oQ

========================================================================== Story Source: Materials provided by University_of_South_Australia. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Jian Fang, Anthony Finn, Ron Wyber, Russell
S. A. Brinkworth. Acoustic
detection of unmanned aerial vehicles using biologically inspired
vision processing. The Journal of the Acoustical Society of America,
2022; 151 (2): 968 DOI: 10.1121/10.0009350 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/03/220315094954.htm

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