Technologies for creating intelligent radar location and technical intelligence systems in the conditions of radio electronic countermeasures

Abstract

The work is devoted to solving the urgent scientific and applied problem of creating intelligent radar and technical intelligence systems capable of operating effectively in conditions of active electronic countermeasures, high signal density, multi-beam propagation and targeted interference. The article considers a comprehensive approach to building such systems based on the integration of software-defined radio technologies (SDR), cognitive spectrum management methods, adaptive signal processing and deep machine learning algorithms.
A multi-level architecture of an intelligent system is proposed, which includes a sensor level of signal collection and pre-processing, an analytical level of spectral-temporal analysis and classification, and a cognitive level of decision-making and adaptation of work parameters. The application of neural network models for automated detection of radiation types, reinforcement learning algorithms for dynamic frequency resource management and multi-position methods for localization of radio radiation sources using data fusion procedures is justified.
It is shown that the integration of these technologies provides a significant increase in the resistance of systems to broadband and pulsed interference, a decrease in the reaction time to changes in the electronic environment, an increase in the accuracy of signal classification and an increase in the reliability of determining the coordinates of radiation sources. The results obtained form a scientific and methodological basis for the creation of new generation technical intelligence systems, oriented towards application in conditions of modern military and hybrid threats.