Алгоритм визначення пріоритетів засобам радіоелектронної боротьби для подавлення конкретного радіоелектронного об’єкту

Formulation of the problem in general. This article presents a novel algorithm for prioritising electronic warfare assets to suppress specific radio electronic objects, considering the similarity of their technical characteristics with those of the identified targets and real-time operational constraints. Research methods. When writing the article, the technique of formalised similarity analysis was applied, which allows assessing the potential effectiveness of the impact of electronic warfare means on the receiving paths of detected electronic means. The proposed approach includes a pre-filtering algorithm and forming a proximity matrix based on regulatory compatibility coefficients. Literature review. The review of recent studies highlights the growing need for adaptive and data-driven coordination strategies in modern electronic warfare. Emerging concepts involving AI and quantum communications and threat ranking models confirm the relevance of multi-criteria decision-making methods and justify the development of new prioritisation algorithms for dynamic environments. Research results. The article proposes an algorithm for ranking electronic warfare assets relative to each detected target, using a composite similarity score. The algorithm accounts for frequency overlap, sector geometry, signal strength at the emission source, resource availability, and feasibility of group engagement. A numerical case study illustrates the step-by-step implementation and resulting priority vector. Research novelty. The proposed algorithm describes a new way of prioritising electronic warfare assets, which allows the choice of assets to adapt to dynamic changes in the combat situation. For the first time, the formalised similarity analysis method is applied to transform technical parameters into a metric of interaction effectiveness. Theoretical and practical significance. The results have practical value for battlefield-level command and control systems. The model enhances operational management capabilities by improving the efficiency of electronic warfare resource deployment, especially in high-density electromagnetic environments. Conclusions and future work. The developed prioritisation algorithm improves the coordination and deployment of electronic warfare systems. Future work may explore the integration of learning-based adjustments to similarity scoring and the development of a software prototype for automated electronic warfare decision support.