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

The development can be used to protect private territories and critical infrastructure facilities

Specialists of 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 the drone in advance, classifies the model, and transmits data to the operator to assess the threat and take action. The new product 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 crossings.
Yuri Koval, Technical Director of the Cyclone Central Research Institute

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:

Detects UAVs at ultra-low altitudes: Ruselectronics has begun supplying 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