Формування системи виявлення і розпізнавання безпілотних літальних апаратів
Вантажиться...
Файли
Дата
Назва журналу
Номер ISSN
Назва тому
Анотація
The problematic issues of combating unmanned aerial vehicles (UAVs) are investigated. It is determined that due to the
cheapness and large-scale production capabilities, the enemy has begun to actively use UAVs such as kamikaze strike
drones and drones with drops (bombers), in particular FPV-drones. It is proved that the level of threat of such UAVs —
battlefield drones is determined not only by their ability to select priority targets, and build an optimal trajectory even at the
stage of attacking the target, but also by the difficulty of counteracting such means of destruction. For the most part, the
problem of countering drones is related to the difficulty of their timely detection. Without solving this problem, the most modern means of fire destruction are unable to reliably counteract such a threat. It is proposed that, along with the classical
detection methods, namely: acoustic, optical, radio engineering, radar, to use such detection methods as aerial and agent
reconnaissance. The essence of this method is to determine the launch sites of drones, which allows to destroy enemy
UAVs with mortar and small arms fire before the use of drones or to warn and target the detection system regarding the
possible direction of use of drones and even their types. The basic principles of the formation of a detection and recognition
system are defined and substantiated, which will allow to take into account the characteristics of drones as air targets, timely
detect them and provide information to fire and electronic warfare. As the experience of the Russian-Ukrainian war shows, a
system for detecting and recognizing air threats to troops and objects on the battlefield should be formed on the following
principles: a combination of means in which detection methods are implemented and organizational measures for the use of
these means; the ability to monitor and analyze the state and trends of the battlefield, planning options for using the system
in accordance with the current or projected situation; constant collection of information on the movement of enemy UAVs,
places of deployment.
Опис
Тип документа
Мова
ISSN
Бібліографічний опис
Бабич А. П., Кібіткін С. О., Георгієв Ю. В., Белзецький Р. С. Формування системи виявлення і розпізнавання безпілотних літальних апаратів // Вісник Вінницького політехнічного інституту. 2024. № 5. С. 109-114.
Схвалення
Рецензія
Доповнено
Цитується в
Список використаної літератури (8)
- ATP-3.3.8.1., Minimum training requirements for unmanned aircraft systems (UAS) operators and pilots. May 2019. 37 p.[Electronic resource]. Available: https://standards.globalspec.com/std/14246865/atp-3-3-8-1.
- V. Kartashov, V. Oleynikov, O. Zubkov, and S. Sheiko, “Optical Detection of Unmanned Air Vehicles on a Video Stream in a Real-Time,” in 2019International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo), Odessa, Ukraine, 2019, pp. 1-4. https://doi.org/10.1109/UkrMiCo47782.2019.9165362.
- S. Adavanne, G. Parascandolo, P. Pertila, T. Heittola, and T. Virtanen, “Sound event detection in multichannel audio us-ing spatial and harmonic features,” in 2016 Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE2016), Budapest, Hungary, 2016, pp. 1-5, https://doi.org/10.48550/arXiv.1706.02293.
- E. Çakır, G. Parascandolo, T. Heittola, H. Huttunen, and T. Virtanen, “Convolutional recurrent neural networks for poly-phonic sound event detection,” IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), vol. 25, no. 6, pp. 1291-1303, June. 2017. https://doi.org/10.1109/TASLP.2017.2690575.
- A. M. Zelnio, “Detection of small aircraft using an acoustic array,” MSEgr, Wright State University, 2009, 55 p.
- V. M. Kartashov, S. I. Babkin, E. G. Tolstykh, and N. G. Lepeha, “Systematic errors in measurement of meteorological variables in correlation processing radioacoustic sounding system signals,” Telecommunications and Radio Engineering, vol. 75, no. 9, pp. 835-843, January, 2016. https://doi.org/ 10.1615/TelecomRadEng.v75.i9.80.
- N. U. A. Tahir, Z. Zhang, M. Asim, C. Junhong, and M. ELAffendi, “Object Detection in Autonomous Vehicles under Adverse Weather: A Review of Traditional and Deep Learning Approaches,” Algorithms, vol. 17 (3), no. 103, pp. 1-36, Febru-ary, 2024. https://doi.org/10.3390/a17030103.
- AARTOS DDS. [Електронний ресурс]. Режим доступу: https://drone-detection-system.com/aartos-dds/product-overview/ . Дата звернення 05. 08. 2024.