Innovative Concept of Augmented Reality Training for Countering UAVs
DOI:
https://doi.org/10.3849/aimt.01965Keywords:
AR, augmented reality, training, UAV, unmanned aerial vehicles, counter-droneAbstract
Contemporary armed conflicts are characterized by the increasing use of unmanned aerial vehicles (UAVs). One key approach is firearm-based defense. This paper presents the concept of an innovative trainer based on augmented reality (AR) technology. The system integrates a virtual environment generated by the Unreal Engine in real-time (including realistic models of drones and firearms) with real-world maps displayed through HoloLens 2 glasses. The paper covers the technical design and implementation, enabling battlefield simulation. The prototype includes features such as dynamic training scenario generation, real-time user position synchronization, and realistic UAV behavior simulation. Findings highlight AR’s potential in military training while addressing challenges like GPS integration and cross-environment synchronization. The system demonstrates selected capabilities for the future of military training.
References
ADAMSKI, M. Effectiveness Analysis of UCAV Used in Modern Military Conflicts. Aviation, 2020, 24(2), pp. 66–71. https://doi.org/10.3846/aviation.2020.12144
XIAONING, Z. Analysis of Military Application of UAV Swarm Technology. In: 2020 3rd International Conference on Unmanned Systems (ICUS). Harbin: IEEE, 2020, pp. 1200–1204. https://doi.org/10.1109/ICUS50048.2020.9274974
MODEBADZE, V. The Importance of Drones in Modern Warfare and Armed Conflicts. KutBilim Journal of Social Sciences and Arts, 2021, 1(2), pp. 89–98. e-ISSN 2791-6340
LAMMERS, D., et al. Airborne! UAV Delivery of Blood Products and Medical Logistics for Combat Zones. Transfusion, 2023, 63(S3), pp. 96–104. https://doi.org/10.1111/trf.17329
CRIOLLO, L., C. MENA-ARCINIEGA and S. XING. Classification, Military Applications, and Opportunities of Unmanned Aerial Vehicles. Aviation, 2024, 28(2), pp. 115–127. https://doi.org/10.3846/aviation.2024.21672
FAN, Y., H. LOU and S. YU. Review of the Development Status of UAV Countermeasures. In: Seventh Asia Pacific Conference on Optics Manufacture and 2021 International Forum of Young Scientists on Advanced Optical Manufacturing. Hong Kong: SPIE, 2022. https://doi.org/10.1117/12.2613542
TYURIN, V., O. MARTYNIUK, V. MIRNENKO, P. OPEN’KO and I. KORENIVSKA. General Approach to Counter Unmanned Aerial Vehicles. In: 2019 IEEE 5th International Conference Actual Problems of Unmanned Aerial Vehicles Developments. Kiev: IEEE, 2019, pp. 75–78. https://doi.org/10.1109/APUAVD47061.2019.8943859
MELNICHUK, A., E.A. KUZINA and N.K. YURKOV. Methods and Means for Countering Unmanned Aerial Vehicles. In: 2020 International Conference on Industrial Engineering, Applications and Manufacturing. Sochi: IEEE, 2020. https://doi.org/10.1109/ICIEAM48468.2020.9112082
GUITTON, M.J. Fighting the Locusts: Implementing Military Countermeasures Against Drones and Drone Swarms. Scandinavian Journal of Military Studies, 2021, 4(1), pp. 26–36. https://doi.org/10.31374/sjms.53
WYDER, P.M., et al. Autonomous Drone Hunter Operating by Deep Learning and All-onboard Computations in GPS-denied Environments. PLoS One, 2019, 14(11), e0225092. https://doi.org/10.1371/journal.pone.0225092
IBEOBI, S. and X. PAN. Study of Electromagnetic Pulse (EMP) Effect on Surveillance Unmanned Aerial Vehicles (UAVs). Journal of Mechanical Engineering Automation and Control Systems, 2021, 2(1), pp. 44–53. https://doi.org/10.21595/jmeacs.2021.21926
CHAMOLA, V., P. KOTESH, A. AGARWAL, N.N. GUPTA and M. GUIZANI. A Comprehensive Review of Unmanned Aerial Vehicle Attacks and Neutralization Techniques. Ad Hoc Networks, 2020, 111, 102324. https://doi.org/10.1016/j.adhoc.2020.102324
ZMYSŁOWSKI, D., P. SKOKOWSKI and J.M. KELNER. Anti-drone Sensors, Effectors, and Systems – A Concise Overview. TransNav, 2023, 17(2), pp. 455–461. https://doi.org/10.12716/1001.17.02.23
MIRNENKO, V., S. NOVICHENKO, O. DOSKA, P. OPEN’KO, O. AVRAMENKO and V. KURBAN. Methodology for Assessing the Level of Threats When Using Small Arms Against Unmanned Aerial Vehicles. Advances in Military Technology, 2022, 17(1), pp. 107–120. https://doi.org/10.3849/aimt.01486
SÖKMEN, A.Z. and H. CANBOLAT. Counter-UAV Systems. Global Journal of Engineering and Technology, 2023, 2(8), pp. 32–36. ISSN 2583-3359
DUDUSH, A., V. TYUTYUNNIK, I. TROFYMOV, S. BORTNOVS’KIY and S. BONDARENKO. State of the Art and Problems of Defeat of Low, Slow and Small Unmanned Aerial Vehicles. Advances in Military Technology, 2018, 13(2), pp. 157–171. https://doi.org/10.3849/aimt.01233
SHAOHUI, X., et al. Development of a Shooting Strategy to Neutralize UAV Swarms Based on Multi-Shot Cooperation. Journal of Physics: Conference Series, 2023, 2460, 012035. https://doi.org/10.1088/1742-6596/2460/1/012035
ŚWIDERSKI, W. and T. GŁOGOWSKI. Analysis of Possibilities for Evaluation of Training Simulators Efficiency on the Basis of “SNIEZNIK” System. Problemy Techniki Uzbrojenia, 2019, 151(3), pp. 31–43. https://doi.org/10.5604/01.3001.0013.7303
TUTA, J., L. LUIĆ and Ž. CAR. A Conceptual Model of Augmented Virtual and Reality in Cadet Training. In: 2019 3rd European Conference on Electrical Engineering and Computer Science (EECS). Athens: IEEE, 2019, pp. 128–133. https://doi.org/10.1109/EECS49779.2019.00035
ŚWIDERSKI, W., T. GŁOGOWSKI, P. HŁOSTA and S. STĘPNIAK. IR Detection of Impact Places of Projectiles in the Training System “ŚNIEŻNIK”. Problems of Mechatronics Armament Aviation Safety Engineering, 2018, 9(2), pp. 99–110. https://doi.org/10.5604/01.3001.0012.1104
BASSA, B., K. DROŻDŻAL, M. KONOPACKI, K. KLICKI and N. DANIEL. Augmented Reality (AR) as a Visualization Tool for a Missile Launch: a Conceptual Example Using the GROM Man-Portable Air-Defense System. Problems of Mechatronics Armament Aviation Safety Engineering, 2024, 15(3), pp. 107–120. https://doi.org/10.5604/01.3001.0054.7514
SHIN, K., H. LEE and J. OH. Introduction to the Extended Reality-based LVCG Military Training System for Small Units at Korea Military Academy. Journal of Peace and War Studies, 2021, Special ed. ISSN 2641-8428
M4A4 Counter Strike 2 [online]. [viewed 2025-01-30]. Available from: https://sketchfab.com/3d-models/m4a4-counter-strike-2-222fd3948aab45eb9d0cbced9c80308a
Drone Free 3D Model [online]. [viewed 2025-01-30]. Available from: https://www.cgtrader.com/free-3d-models/vehicle/industrial-vehicle/drone-d79e19a3-4ae8-44c1-999d-d81de12734d1
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