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Justification of the choice of radiation sources for a computer vision system in the problem of automatic landing of unmanned aerial vehicles
A.M. Ageev 1, V.G. Bondarev 1, V.V. Protsenko 1

Federal State Official Military Educational Institution of Higher Education "Military Educational and Scientific
Centre of the Air Force of N.E. Zhukovsky and Y.A. Gagarin Air Force Academy" (Voronezh) the Ministry
of Defence of the Russian Federation, 394064, Voronezh, Russia, Staryh Bolshevikov 54а

 PDF, 1706 kB

DOI: 10.18287/2412-6179-CO-875

Pages: 239-245.

Full text of article: Russian language.

An expedient spectral range of radiation sources for use in the automatic landing system of unmanned aerial vehicles has been substantiated. A method is proposed for synchronizing the photoexposure of the computer vision system and radiation from landmarks for the unambiguous determination of their mutual position. Results of the experimental studies are presented.

unmanned aerial vehicle, landing system, infrared range, contrast reference point, laser radiation, pulse mode.

Ageev AM, Bondarev VG, Protsenko VV. Justification of the choice of radiation sources for a computer vision system in the problem of automatic landing of unmanned aerial vehicles. Computer Optics 2022; 46(2): 239-245. DOI: 10.18287/2412-6179-CO-875.


  1. GOST R 51747-2001. Microwave radio beacon instrument approach landing system for air vehicles. Main parameters and methods of measuring [In Russian]. Moscow: "Gosstandart Rossii" Publisher; 2001.
  2. Zhiharev VP, Zazerskij LK, Ershov GA, Krivoruchko YT. Problems of promising instrumental approach tools for aircraft development [In Russian]. Radiopromyshlennostj 2015; 4: 107-118.
  3. Bartenev VA, Grechkoseev AK, Kozorez DA. Modern and perspective informational global navigation satellite technologies in high-precision navigation tasks. Moscow: «Fizmatlit» Publisher; 2014.
  4. OPATS. The laser-based automatic landing systems for UAVS. Source: <https://www.ruag.ch/sites/default/files/2021-03/210226_Factsheet_OPATS.pdf>.
  5. The Russian Federation has developed its own laser system for the automatic landing of UAVs LSOK. Source: <https://en.topwar.ru/121261-v-rf-razrabotana-sobstvennaya-lazernaya-sistema-avtomaticheskoy-posadki-bespilotnikov-lsok.html>.
  6. Logvin AI, Volkov AV. Algorithms for automatic recognition of an aerodrome on video images [In Russian]. Scientific Bulletin of MSTU GA 2015; 213: 115-117.
  7. Fan YM, Ding M, Cao YF. Vision algorithms for fixed-wing unmanned aerial vehicle landing system. Sci China Technol Sci 2017; 60(3): 434-443.
  8. Zhang L, Cheng Y, Zhai ZJ. Real-time accurate runway detection based on airborne multi-sensors fusion. Defence Sci J 2017; 67(5): 542-550.
  9. Benini AJ, Rutherford M. Real-time, GPU-based pose estimation of a UAV for autonomous takeoff and landing. Proc Third Int IEEE Conf on Signal-Image Technologiesand Internet-Based System 2007: 972-978.
  10. Abu-Jbara K, Alheadary W, Sundaramorthi G, Claudel C. A robust vision-based runway detection andtracking algorithm for automatic UAV landing. Proc 2015 Int Conf on Unmanned Aircraft Systems (ICUAS) 2015: 1148-1157.
  11. Ageev AM, Belyaev VV, Bondarev VG, Procenko VV. Automatic landing systems for unmanned aerial vehicles: problems and solutions [In Russian]. Voennaya Mysl' 2020; 4: 130-136.
  12. Ageev AM, Bondarev VG, Ippolitov SV, Lopatkin DV, Ozerov EV, Protsenko VV, Fateev IA. Method of determining coordinates of an aircraft relative to an airstrip. Pat RF of Invent N 2706443 of November 19, 2019, Russian Bull of Inventions N32, 2019.
  13. Ageev AM, Bondarev VG, Procenko VV. Infrared local navigation system of unmanned aerial vehicles for automation of the landing mode [In Russian]. Proc 30th Int Symp on Transmission, Reception, Processing and Display of Information About Fast Processes, Moscow 2019: 32-37.
  14. Koval SA. Analysis of the possibilities of organizing communication in the field area using atmospheric optical communication lines [In Russian]. Proc 1th Int Symp Engineering Sciences: Tradition and Innovation, Chelyabinsk 2012: 17-20.
  15. Gui Y. Airborne vision-based navigation method for UAV accuracy landing using infrared lamps. J Intell Robot Syst 2013; 72: 197-218.
  16. Yakushenkov YuG. Theory and calculation of optoelectronic devices textbook for universities [In Russian]. Moscow: "Logos" Publisher; 2012.
  17. Abakumov AV, Kuz'menko IK, Livshic DYu, Sergushov IV, Slonov VN. Automatic landing system for unmanned aerial vehicles using laser emitters [In Russian]. Proc 29th Int Symp on Mathematical methods in engineering and technology, Saratov 2016: 130-132.

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