Collaborators from Aalto University in Finland, New York University (NYU) and UCLouvain in Belgium have developed radar technology for better monitoring and identifying drones.

Amid increased use of drone technology for applications as varied as aerial photography, rescue missions, law enforcement, fire fighting, shipping, delivery and mapping to name just a few, collaborating researchers are seeking ways to keep the public safe from suspicious drones, particularly those with the potential to be used to carry out terrorist threats, by identifying how individual drones reflect radio signals based on their make, model, shape and material composition — a measure called the drone’s Radar Cross Section (RCS).

By measuring drones’ RCS at 26 to 40 GHz millimeter wave (mmWave) frequencies, the research team discovered that different drone’s will scatter radio signals uniquely based on its RCS signature, thereby improving methods for detecting and identifying suspicious drones and potentially thwarting attacks conducted via drone.

The measurement tool, which is publicly available, could one day be used to help construct radar systems and machine learning algorithms for drone detection.

The research appears in IEEE Access.

For more information on the technology, watch the accompanying video that appears courtesy of Aalto University.

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