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Team scans drones of different shapes and sizes to counter terrorist attack risk

Professional Engineering

Measuring a drone's Radar Cross Section in Aalto University's anechoic chamber (Credit: Vasilii Semkin)
Measuring a drone's Radar Cross Section in Aalto University's anechoic chamber (Credit: Vasilii Semkin)

Radar data from drone scans has been publicly released to help counter the privacy and security threats from unmanned aircraft, with researchers hoping the information could form the basis of a future database.

Based at Aalto University in Finland, UCLouvain in Belgium and New York University, the team gathered extensive radar measurement data, aiming to improve the detection and identification of unmanned aerial vehicles (UAVs) amid concern about malicious use such as potential terrorist attacks.

Researchers measured various commercially-available and custom-built drones’ Radar Cross Sections (RCS), which indicate how targets reflect radio signals. RCS signatures can help identify the size, shape and material of a drone.

“We measured drones' RCS at multiple 26-40GHz millimetre-wave frequencies to better understand how drones can be detected, and to investigate the difference between drone models and materials in terms of scattering radio signals,” said research author Vasilii Semkin. “We believe that our results will be a starting point for a future uniform drone database.”

The publicly-accessible measurement data could be used in the development of radar systems, as well as machine learning algorithms for more complex identification. This would increase the probability of detecting UAVs and reducing false detections.

“There is an urgent need to find better ways to monitor drone use. We aim to continue this work and extend the measurement campaign to other frequency bands, as well as for a larger variety of drones and different real-life environments,” said Semkin.

“We are developing millimetre-wave wireless communication technology, which could also be used in sensing the environment like a radar. With this technology, 5G-base stations could detect drones, among other things,” said professor Ville Viikari from Aalto University.

The research was published in IEEE Access.

The measurement data is online here.


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