Stochastic Model of Functional Behavior of Radio Electronic Complex System for Detection of Low-Flying Unmanned Aerial Vehicles

Authors

  • Bohdan Volochiy
  • Mykola Dyvak
  • Leonid Ozirkovskyy
  • Volodymyr Onyshchenko
  • Oleksandr Shkiliuk
  • Maksym Onyshchenko

DOI:

https://doi.org/10.47839/ijc.25.2.4648

Keywords:

radio electronic UAV detection complex system, acoustic UAV detection system, optoelectronic UAV detection system, operational functional behavior of the complex system, mathematical modeling, discrete-continuous stochastic model

Abstract

A radio electronic complex system for detecting low-flying unmanned aerial vehicles is considered. It includes two acoustic systems, a repeater, an optoelectronic system, and an information control system. To determine the efficiency of the radio-electronic complex system, a discrete-continuous stochastic model of its operational functional behavior is developed. The degree of adequacy of the proposed discrete-continuous stochastic model of the operational functional behavior of the radio-electronic complex system is determined by the list of functionality indicators considered for the systems comprising it. A verbal model of operational functional behavior is built based on its functional algorithm. Functional indicators for each system in the stochastic model use “the probability of detecting unmanned aerial vehicles when they are in the corresponding controlled zone” and “the average values of the time intervals from the moment of appearance of unmanned aerial vehicles in the controlled zone to the moment of their detection by the corresponding system”. The stochastic model makes it possible to calculate the values of the functionality indicators of its systems for a given value of the radio-electronic complex system’s efficiency indicator. The results of validation experiments conducted on the developed stochastic model of the functional behavior of the radio-electronic complex system for detecting low-flying unmanned aerial vehicles are provided.

References

A.H. Michel, Сounter-drone Systems, 2nd Edition, December 2019, рр. 6–37. https://www.calameo.com/read/000009779458ad0134023.

T. Pham, N. Srour, “TTCP AG-6: Acoustic detection and tracking of UAVs,” U.S. Army Research Laboratory. Proc. оf SPIE, 2004, vol. 5417, pp. 24–29, https://doi.org/10.1117/12.548194.

A. Saravanakumar, K. Senthilkumar, “Еxploitation of acoustic signature of low flying aircraft using acoustic vector sensor,” Defence Science Journal, vol. 64, no. 2, pp. 95–98, 2014. https://doi.org/10.14429/dsj.64.3924.

S. Sadasivan, M. Gurubasavaraj, and S. Ravi Sekar, “Acoustic signature of an unmanned air vehicle exploitation for aircraft localisation and parameter estimation,” Еronautical DEF SCI J, vol. 51, no. 3, pp. 279–283, 2001. https://doi.org/10.14429/dsj.51.2238.

V.I. Chyhin, M.М. Protsenko, Y.V. Shabatura, and M.V. Buhaiov, “Improvement of the method of detecting unmanned aerial vehicles based on the results of spectral analysis of acoustic signals,” Military Technical Digest, vol. 20, pp. 58–63, 2019. https://doi.org/10.33577/2312-4458.20.2019.58-63.

A.O. Herasymenko, S.Ya. Zhuk, “Analysis of the efficiency of the Kalman-type correlation algorithm for tracking of a small UAV in the presence of uncorrelated interference,” National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, visnyk NTUU KPI Seriia – Radiotekhnika Radioaparatobuduvannia, no. 87, pp. 22–29, 2021. https://doi.org/10.20535/RADAP.2021.87.22-29.

V.M. Sineglazov, “Complex structure of UAVs detection and identification,” Electronics and Control Systems, Kyiv, Aviation Computer-Integrated Complexes Department, National Aviation University, no. 3(45), рр. 28–32, 2015. https://doi.org/10.18372/1990-5548.45.9893.

T. Chung, R. Buettner. “UAV to UAV target detection 103.and pose estimation,” Naval Postgraduate School, Monterey. Department of the Navy. 2012, 89 р. https://drive.google.com/drive/folders/187GmVVh1YLRk1isl-Y5EcZkCGRknAIcZ.

A. Nesteruk, V. Nikitin, Y. Albrekht, Ł. Ścisło, D. Grela, P. Król, “Distinguishing a drone from birds based on trajectory movement and deep learning,” Sensors, vol. 26, issue 3, 755, 2026. https://doi.org/10.3390/s26030755.

S. Rudys, A. Laucys, P. Ragulis, R. Aleksiejunas, K. Stankevicius, M. Kinka, M. Razgunas, D. Brucas, D. Udris and R. Pomarnacki, “Hostile UAV detection and neutralization using a UAV system,” Drones, vol. 6, 250, pp. 1 ̶18, 2022. https://doi.org/10.3390/drones6090250.

A. Laučys, S. Rudys, M. Kinka, P. Ragulis, J. Aleksandravičius, D. Jablonskas, D. Bručas, E. Daugėla, L. Mačiulis, “Investigation of detection possibility of UAVs using low cost marine radar,” Aviation, vol. 23, issue 2: pp. 48-53, 2019. https://doi.org/10.3846/aviation.2019.10320.

S. Rudys, P. Ragulis, A. Laučys, D. Bručas, R. Pomarnacki, D. Plonis. “Investigation of UAV detection by different solid-state marine radars,” Electronics, vol. 11, 2502, pp. 1–15, 2022. https://doi.org/10.3390/electronics11162502.

V. P. Riabukha, “Radar surveillance of unmanned aerial vehicles (Review)” Radioelectronics and Communications Systems, vol. 63, no. 11, pp. 561–573, 2020. https://doi.org/10.3103/S0735272720110011.

С.D. Vyshnevsky, L.V. Beilis, & V.Y. Klimchenko, “Potential capabilities of radar systems of radio engineering troops to detect operational and tactical unmanned aerial vehicles,” Science and Technique of the Air Force of the Armed Forces of Ukraine, no. 2, pp. 92–98, 2017. http://nbuv.gov.ua/UJRN/Nitps_2017_2_21.

V. Kartashov, V. Pososhenko, V. Voronin, V. Kolesnik, A. Kapusta, N. Rybnikov & E. Pershin, “Methods for detection-recognition of radar, acoustic, optical and infrared signals of unmanned aerial vehicles,” Radiotekhnika, no. 2(205), рр. 138–153, 2021. https://doi.org/10.30837/rt.2021.2.205.15.

P. Jiang, X. Yang, Y. Wan, T. Zeng, M. Nie, Z. Liu, “DRBD-YOLOv8: A lightweight and efficient anti-UAV detection model,” Sensors, vol. 24, 7148, pp. 1–23, 2024. https://doi.org/10.3390/s24227148.

Md. Mahfuzur Rahman, S. Siddique, M. Kamal, R. Hossain Rifat and K. Datta Gupta, “UAV (unmanned aerial vehicles): diverse applications of UAV datasets in segmentation, classification, detection, and tracking,” Marufa Kamal Dept. of CSE BRAC University, Dhaka, Bangladesh, 2024, 46 р. https://doi.org/10.20944/preprints202411.0829.v1.

“Questions to ask when researching counter unmanned aerial systems,” U.S. Department of Homeland Security Science and Technology Directorate, 2019. https://www.dhs.gov/sites/default/files/publications/c-uas-responder-qs-poster_20august2020_final.pdf.

Y.G. Danik, I.V. Puleko, & M.V. Bugayev, “Detection of unmanned aerial vehicles based on the analysis of acoustic and radar signals,” Bulletin of Zhytomyr State Technological University, Series: Technical sciences, no. 4, pp. 71–80, 2014. http://nbuv.gov.ua/UJRN/Vzhdtu_2014_4_13.

F. Svanström, C. Englund and F. Alonso-Fernandez, “Real-time drone detection and tracking with visible, thermal and acoustic sensors,ˮ Proceedings of the 2020 25th International Conference on Pattern Recognition (ICPR), 2021, pp. 7265-7272, https://doi.org/10.1109/ICPR48806.2021.9413241.

W. Shi, G. Arabadjis, B. Bishop, P. Hill, R. Plasse and J. Yoder, “Detecting, tracking, and identifying airborne threats with netted sensor fence,” in book: Sensor Fusion – Foundation and Applications, 2011, pp. 139–158, https://doi.org/10.5772/17666.

Y.G. Danik, M.V. Bugayev, “Analysis of the efficiency of detection of tactical unmanned aerial vehicles by passive and active surveillance means”, Problems of creation, testing, application and operation of complex information systems, vol. 10, pp. 5–20, 2015. http://nbuv.gov.ua/UJRN/Psvz_2015_10_3.

C. Kouhestani, B. Woo, and G. Birch, “Counter unmanned aerial system testing and evaluation methodology,” Proc. SPIE 10184, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security, Defence, and Law Enforcement Applications XVI, 1018408 (5 May 2017), https://doi.org/10.1117/12.2262538.

J. Wu, S. Huang, X. Wang, Y. Kou, W. Yang, “Study on the performance of laser device for attacking miniature UAVs,” Optics, vol. 5, pp. 378–391, 2024. https://doi.org/10.3390/opt5040028.

T. Zhang, R. Lu, X. Yang, X. Xie, J. Fan and B. Tang, “UAV hunter: A net-capturing UAV system with improved detection and tracking methods for anti-UAV defense,” Drones, vol. 8, 573, p. 1-20, 2024. https://doi.org/10.3390/drones8100573.

Y. Mekdad, A. Acar, A. Aris, A. El Fergougui, M. Conti, R. Lazzeretti, and S. Uluagac, “Exploring jamming and hijacking attacks for micro aerial drones,” Proceedings of the IEEE Conference on ICC. Paper Florida International University, March 2024, 6 p. https://doi.org/10.1109/ICC51166.2024.10623000.

H. Fesenko, O. Illiashenko, V. Kharchenko, K. Leichenko, A. Sachenko, L. Scislo, “Methods and software tools for reliable operation of flying LiFi networks in destruction conditions,” Sensors, vol. 24, issue 17, 5707, 2024. https://doi.org/10.3390/s24175707.

O. Shkiliuk, B. Volochiy, and I. Petliuk, “Discrete-continuous stochastic model of behavior algorithm of surveillance and target acquisition system,” Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications, Integration, Harmonization and Knowledge Transfer, volume II, Kherson, Ukraine, June 12-15, 2019, pp. 761-776. https://www.scopus.com/pages/publications/85069468310.

Yu. Salnyk, B. Volochiy, and V. Onishchenko, “Stochastic model of the reaction the unattended ground sensor system based on {3+3} scheme,” Proceedings of the 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET-2020), Lviv-Slavske, Ukraine, February 25-29, 2020, pp. 496-501. https://doi.org/10.1109/TCSET49122.2020.235482.

Yu.P. Salnyk, B.Yu. Volochiy, “Stochastic model of functional behavior of the security system of a critical infrastructure facility,” Modern Information Systems, vol. 5, no. 1, Kharkiv, National Technical University “Kharkiv Polytechnic Institute”, 2021, pp. 18-33, https://doi.org/10.20998/2522-9052.2021.1.03.

Downloads

Published

2026-06-30

How to Cite

Volochiy, B., Dyvak, M., Ozirkovskyy, L., Onyshchenko, V., Shkiliuk, O., & Onyshchenko, M. (2026). Stochastic Model of Functional Behavior of Radio Electronic Complex System for Detection of Low-Flying Unmanned Aerial Vehicles. International Journal of Computing, 25(2), 210-222. https://doi.org/10.47839/ijc.25.2.4648

Issue

Section

Articles