System of Indicators for Assessing the Efficiency of Information Transmission and Processing Systems of Combat Unmanned Aerial Vehicles

Keywords: combat unmanned aerial vehicles, data transmission systems, information processing, performance indicators, integral efficiency index, communication networks, relay systems, efficiency modeling

Abstract

Purpose. The purpose of this study is to develop an optimization mathematical model aimed at enhancing the efficiency of information transmission and processing systems for combat unmanned aerial vehicles (UAVs). The model is based on an integral efficiency indicator D, which represents a generalized quantitative assessment of the communication system’s performance, integrating multiple technical and operational parameters into a single criterion.

Method. The model treats the integral indicator D as the objective function to be maximized. The variables are not the technical parameters themselves but the control parameters of the system, such as transmitter power, number of relays, flight altitude, energy consumption level, and channel robustness. Each partial performance indicator is normalized and integrated into a unified efficiency score. The interpretation of results is performed using the Harrington desirability scale.

Findings. A mathematical model for integral evaluation of the efficiency of combat UAV communication and data processing systems was developed and tested through computer simulation. The obtained dependencies between relay distance, signal-to-noise ratio (SNR), and the integral efficiency index D confirmed the model’s adequacy. Implementation of the proposed optimization method increased the integral indicator by an average of 20–25%, demonstrating improved link stability and energy efficiency under realistic operational conditions.

Theoretical implications. The research expands the theoretical foundations of performance evaluation in military communication networks by demonstrating how a set of heterogeneous technical parameters can be aggregated into a single integral criterion. The proposed approach can serve as a conceptual basis for developing universal efficiency assessment models applicable to other dual-use information and communication systems.

Originality / Value. The originality of the study lies in the systematic integration of six fundamental performance indicators into a single dimensionless efficiency index D, which possesses both quantitative and qualitative interpretability. The proposed methodology combines physical communication parameters (such as throughput, delay, SNR, and reliability) with evaluative criteria of resilience and energy efficiency, thus providing a comprehensive assessment of UAV communication systems under combat conditions.

Future research. Future work should focus on implementing a software module for automated real-time evaluation of the proposed efficiency indicators, integrated into swarm UAV control systems. Another promising direction is the development of adaptive weighting algorithms for the indicators depending on mission type, electromagnetic environment, and the dynamics of combat operations.

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References

Kysliuk M. A. General principles of building communication systems for unmanned aerial vehicles. – Scientific News of NTUU “KPI”, 2020, No. 2, pp. 15–22. – Available from : https://ela.kpi.ua/server/api/core/bitstreams/bd44ee50-cc1c-4caf-b0c3-b361ba22412f/content

Kompaniiets O. M. A comprehensive system of indicators for assessing the efficiency of UAV swarm management. – Weapons and Military Equipment Systems, 2021, No. 1(65), pp. 112–118. – Available from : https://journal-hnups.com.ua/index.php/soivt/article/view/1815

Kharchenko V. P., Havryliuk O. V., Kovalenko S. V. Methodology for assessing the efficiency of military communication systems. – Science and Defense, 2022, No. 2, pp. 45–53. – Available from : https://ndu.edu.ua/nauka-i-oborona

Harrington E. C. The Desirability Function. – Industrial Quality Control Journal, 1965, Vol. 21, No. 10, pp. 494–498. – Available from : https://www.scirp.org/reference/referencespapers?referenceid=1542744

Bekmezci I., Sahingoz O. K., Temel Ş. Flying ad-hoc networks (FANETs): A survey. – Ad Hoc Networks Journal, 2013, Vol. 11, No. 3, pp. 1254–1270. – DOI: https://doi.org/10.1016/j.adhoc.2012.12.004

Abdelmoneum M., El-Sayed H. Multi-Criteria Performance Evaluation of UAV Communication Networks. – IEEE Access, 2022, Vol. 10, pp. 55328–55339. – Available from : https://ieeexplore.ieee.org/document/9738425

Sharma V., You I., Atiquzzaman M. Secure and Efficient Communication Architecture for UAV Swarms in 5G Networks. – IEEE Network, 2020, Vol. 34, No. 5, pp. 178–184. – DOI: https://doi.org/10.1109/MNET.011.1900620

Zhou C., Cheng X., Wu D. Energy-efficient routing for UAV swarms with relay coordination. – Computer Networks, 2021, Vol. 191, Article 108015. – DOI: https://doi.org/10.1016/j.comnet.2021.108015

Khan A., Yau K. L. A., Noor R. M. A Survey on Unmanned Aerial Vehicle Networks for Civil Applications. – IEEE Access, 2020, Vol. 8, pp. 57575–57604. – DOI: https://doi.org/10.1109/ACCESS.2020.2982300

Yanmaz E., Yahyanejad S., Rinner B. Drone Networks: Communications, Coordination, and Sensing. – Ad Hoc Networks, 2022, Vol. 120, Article 102554. – DOI: https://doi.org/10.1016/j.adhoc.2021.102554


Abstract views: 204
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Published
2025-10-31
How to Cite
Tarasenko, O. (2025). System of Indicators for Assessing the Efficiency of Information Transmission and Processing Systems of Combat Unmanned Aerial Vehicles. Social Development and Security, 15(5), 315-324. https://doi.org/10.33445/sds.2025.15.5.25
Section
Social Sciences