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  5. Analysis of the possible radio and television systems on-board equipment of unmanned aerial vehicle

Analysis of the possible radio and television systems on-board equipment of unmanned aerial vehicle

Yа. Kozhushko, O. Hrichanuk, M. Samorok, O. Balabuha
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Description: The article proposes options for the use of observation tools that are advisable to consider as the equipment of an un-manned aerial vehicle (UAV). Presents technical means and solutions that already exist and are used in other states. At the pre-sent time, due to the constant growth of the enemy's ability to mask, to constantly improve existing positions and shelters, there is a need for expanding the spectrum of observation. It is shown that the use of multi-spectral data is comprehensive, realistic and can be applied on board the UAV and will increase the amount of information received. At present, due to the constant growth of the enemy's ability to disguise, to continuously improve existing positions and shelters, it is necessary to expand the spectrum of observation. On the other hand, the large amount of information observed over a long period of time, in intensive conditions of combat, leads to the fatigue of the operator, and in the future in the passage of possible goals or in the interpretation of errone-ous goals as real. Providing the consumer with reliable and maximally accurate information leads to the need for constant im-provement of equipment and structures for its extraction. It should be noted that the concept of a common and time- consuming space of use of various means of integration integrated into a single intelligence system with a further fire defeat is, de facto, a new standard in the development of high-precision intelligence and lesion systems that fully fits into the concept of network-centricity fighting action. Alsow, it is shown that the use of neural networks in the processing of information on board can allow the detection of hidden, recognition of false and real objects, reduce the operator's working time and improve the efficiency of his work, and in the subsequent case, the time of decision on the object being observed.

Keywords: unmanned aerial vehicle, combined systems, remote sensing of the earth, camera, infrared camera, neural net-work


1. Tancyra, A.B. (2016), “Analiz metodiv compleksyvannya riznospectralnykh zobrazhenn z vykorystannyam yniversalnogo pokaznyka yakosti” [Аnalysis of methods different spectral image fusion with using universal quality score], Science and Technology of the Air Force of Ukraine, No. 4(25), pp. 152-156.
2. Alimiev, A.M., Ivashchuk, B.M. and Karlow, D.V. (2016), “Tendenciyi rozvy`tku aerokosmichny`x zasobiv sposterezhennya” [Trends in aerospace monitoring], KNAFU, Kharkiv, 132 p.
3. Ruifang, Ye., Tanran, Wu and Xiangyu, Ren (2013), The future development of foreign military electronic warfare UAVs, Aerospace Electronic Warfare, Vol. 2, pp. 12-15.
4. Antufeev, V.I., Bykov, V.I. and Grichanuk, A.M. (2005), “Metod korrekcii perspektivnykh iskajeniy tekyshih izobrajeniy v radiometricheskih sistemah navigacii” [Correction method for perspective distortion of current images in radiometric navigation systems], Information Processing Systems, No. 4(44), pp. 7-15.
5. The official site of UKRSPECSYSTEMS (2016), USG-302 Proffesional edition, available at: www.ukrspecsystems. com/usg-302/ (accessed 1 October 2018).
6. The official site of ITC.UA (2017), “Google sozdala dostupnyy nabor kompyuternogo zreniya AIY Vision Kit na baze Raspberry Pi” [Google has created an affordable set of computer vision AIY Vision Kit based on Raspberry Pi], available at: www.itc.ua/news/google-sozdala-dostupnyiy-nabor-kompyuternogo-zreniya-aiy-vision-kit-na-baze-raspberry-pi/ (accessed 1 October 2018).
7. The official site of 3DNEWS.RU (2017), “USB-brelok Movidius Neural Compute Stick nadelit funkciyami mashinnogo obucheniya lyuboj PK” [The Movidius Neural Compute Stick USB Keyfob will provide machine learning for any PC], available at: www.3dnews.ru/955777?from=related-grid&from-source=957694 (accessed 1 October 2018).
8. The official site of 9111.RU (2018), “Dron i nejroset' pomogut opredelit' vidovoj sostav lesa” [Drone and neural network will help determine the species composition of the forest], available at: www.9111.ru/questions/777777777338284/ (accessed 1 October 2018).
9. The official site of RIEGL (2010), “Vozdushnyj lazernyj skaner RIEGL LMS-Q240i” [Air laser scanner RIEGL LMS-Q240i], available at: www.riegl.ru/Vozdushnoe-lazernoe-skanirovanie/vozdushnyj-lazernyj-skaner-riegl-lms-q240i.html (accessed 1 October 2018).
10. The official site of HISTORIC.RU (2012), “Lazernyj radar mozhet revolyucionizirovat' arheologiyu” [Laser radar can revolutionize archeology], available at: www.historic.ru/news/item/f00/s18/n0001841/index.shtml (accessed 1 October 2018). 11. The official site of BBC (2018), “Arheologi obnaruzhili v dzhunglyah Gvatemaly desyatki tysyach postroek” [Archaeologists have discovered tens of thousands of buildings in the jungles of Guatemala], available at: www.bbc.com/russian/news-42924059 (accessed 1 October 2018).
12. The official site of TOPWAR.RU (2011), “Novyj datchik na bespilotnike – gibel' suhoputnyh vojsk” [The new sensor on the drone – the death of ground forces], available at: www.topwar.ru/8225-novyy-datchik-na-bespilotnike-gibel-suhoputnyh-voysk.html (accessed 1 October 2018).

 Kozhushko, Ya.M., Hrychaniuk, O.M., Samorok, M.H. and Balabukha, O.S. (2018), “Analiz mozhlyvoho bortovoho osnashchennia radiotekhnichnymy ta televiziinymy systemamy bezpilotnoho litalnoho aparatu” [Analysis of the possible radio and television systems on-board equipment of unmanned aerial vehicle], Scientific Works of Kharkiv National Air Force University, Vol. 4(58), pp. 37-42. https://doi.org/10.30748/zhups.2018.58.05.