Developers from TsNII "Burevestnik" have proposed a new radar detection system that should not lose an aerial target during sharp maneuvers. The complex combines three types of surveillance tools: radar, optoelectronic, and sound-ranging, with their data integrated by a central control system.

The main feature is that the algorithm considers not only the target's coordinates. The model uses four key motion parameters: position, velocity, acceleration, and jerk. Additionally, the system takes into account the type and characteristic size of the aircraft, atmospheric conditions, and the aerodynamic model.

A nonlinear Kalman filter is used to refine the trajectory, and a neural network approximates the results of physical flight modeling when weather and turbulence change. Neural network algorithms are also used for visual target recognition.

The system is capable of automatically transferring tracking between sensors. If a target leaves the zone of one post, the CSU searches for the nearest available surveillance tool and transmits the data to it. In this case, the operating zones of the sensors must overlap to prevent track loss.

Another feature is the ability to reduce the need for constant radio emission. The complex can include passive optoelectronic devices and remote radars distributed across the territory.