Повысит дальность обнаружения БПЛА на 40%: в НИИ «Циклон» разработали противодронную нейросеть

Разработка может применяться для охраны частных территорий и критических объектов инфраструктуры

Specialists from the Cyclone Research Institute (part of the Ruselectronics holding) have created a neural network for optical means of detecting unmanned aerial vehicles (UAVs). The development will increase the range of drone detection by 40%, the company's press service reported.

The neural network detects a drone in advance, classifies the model, and transmits data to the operator to assess the threat and take action. The innovation allows the anti-drone system to be switched to autonomous operation.

The new development is a symbiosis of several optimized neural networks. It is more effective in detecting UAVs compared to other analogues.

According to our approximate estimate, the created neural network, compared to similar IT solutions, is capable of increasing the range of UAV detection systems by approximately 40%. This technology can be used at various critical infrastructure facilities, as well as to protect private territory from illegal border violations.
Yuri Koval, Technical Director of the Central Research Institute "Cyclone"

The new UAV detector received high marks from experts. It won a prize at the "Digital Transformation Leaders" competition.

Earlier, www1.ru reported that the Tamerlan system for protecting objects from UAV attacks was created in Russia.

Read materials on the topic:

Will Detect UAVs at Extremely Low Altitudes: Ruselectronics Begins Deliveries of Multifunctional Radar

Project "Krylo" - An Analogue of NATO Systems: Chechen Developers Have Learned to Calculate Approaching Drones

AI Will Put Enemy Drones into a "Stupor": Russia Has New Complexes to Protect Objects from UAVs