Cognitive regional airspace surveillance and control systems

Abstract

The article presents a conceptual approach to building a unified radar field based on a cognitive architecture integrating artificial intelligence technologies. The necessity of transitioning from traditional airspace control systems to a cognitive system capable of learning, adaptation, and prediction is substantiated. A key element is the parallel implementation of an artificial intelligence cluster that enables real-time data processing without interfering with the existing control loops of the situation center. The AI module functions as an intelligent extension, reducing the cognitive load on operators and enhancing the resilience of the airspace control system to modern threats, including mass unmanned aerial vehicle attacks and electronic interference. The approach emphasizes the possibility of evolutionary implementation without interrupting the operation of existing systems, as well as compatibility with a multisensory infrastructure. The proposed solution forms the foundation for a sustainable, scalable, and intelligent next-generation airspace security system.