2022, issue 2, p. 74-82

Received 29.08.2022; Revised 09.09.2022; Accepted 29.09.2022

Published 30.09.2022; First Online 05.10.2022


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UDC 623.7:004.056

To the Problems of the National State Recognition System Improving

Maxim Ogurtsov ORCID ID favicon Big,   Vyacheslav Korolyov ORCID ID favicon Big,   Oleksandr Khodzinskyi * ORCID ID favicon Big

V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine, Kyiv

* Correspondence: This email address is being protected from spambots. You need JavaScript enabled to view it.


Introduction. A rapid increase in the number of objects that simultaneously take part in combat operations in the air requires improvement of systems for recognizing military objects both in terms of qualitative and quantitative indicators. This requires the development of appropriate algorithms for identifying new-generation "friend-foe" objects. Such algorithms can be based on various methods of information security, in particular symmetric and asymmetric cryptographic algorithms and other methods of cryptography.

The purpose of the article is to survey modern systems of state recognition of objects (SSRO), identify their shortcomings and provide recommendations for their elimination.

Results. The requirements for SSRO as a system for processing, transmitting, securing information and identifying objects based on cryptography and computer security methods are defined. Common and distinctive features for civil and military identification systems are highlighted. The advantages and disadvantages of the existing SSRO are shown. Recommendations are formulated to address the shortcomings of the existing SSRO. An example of a stand and a hardware and software basis for studying SSRO algorithms with backup channels is given.

Conclusions. Eliminating the shortcomings of the SSRO and improving the level of its reliability will require the implementation of the following organizational and technical measures.

1. Replacing the current state recognition system with a more modern one, which will support more modern cryptographic algorithms and a larger number of recognition objects. Adding support for radio tag recognition (RF tags).

2. Support for recognition lines in various directions, including "ground – UAV", "plane – tank", "plane – UAV" and others. Adding support for the NATO standard – STANAG 4579, adopted in 2001, and others.

3. Using of broad-spectrum signals to reduce the probability of detection and interception, as well as a number of signal-code structures and a working frequency grid.


Keywords: Friend-or-Foe, object identification, cryptography, backup channels.


Cite as: Ogurtsov M., Korolyov V., Khodzinskyi O. To the Problems of the National State Recognition System Improving. Cybernetics and Computer Technologies. 2022. 2. P. 74–82. (in Ukrainian) https://doi.org/10.34229/2707-451X.22.2.8



           1.     The General Staff of the Armed Forces of Ukraine, the Ministry of Digital and UNITED24 are gathering the "Army of Drones", Ministry of Digital Transformation of Ukraine. (in Ukrainian) https://www.kmu.gov.ua/news/genshtab-zsu-mincifri-ta-united24-zbirayut-armiyu-droniv (accessed: 01.07.2022)

           2.     Rudinskas D., Goraj Z., Stankūnas J. Security Analysis Of UAV Radio Communication System. Aviation. 2009. 13 (4). P. 116-121. https://doi.org/10.3846/1648-7788.2009.13.116-121

           3.     Ogurtsov M.I. Development of a secure data exchange protocol for special networks. Matematychne ta komp’yuterne modelyuvannya. 2019. 19. P. 108113. (in Ukrainian) https://doi.org/10.32626/2308-5916.2019-19.108-113

           4.     Matt B. J. Lightweight and Survivable Key Management for Army Battlefield Networks. Internal Publication, Network Associates Laboratories. 2003. http://projects.mindtel.com/2005/SDSU.Geol600.Sensor_Networks/sensornets.refs/2003. ASC. Army Studies Conference/OA05 Lightweight and Survivable Key Management for Army Battlefield Networks.pdf (accessed: 25.07.2022)

           5.     Ermak S.N., Kasanin O.A., Khozhevets S.N. Design and operation of ground means of the state identification system. Minsk: BGUIR, 2017. 230 p. (in Russian)

           6.     Waterman D. L. Fratricide: Incorporating DESERT STORM Lessons Learned. https://citeseerx.ist.psu.edu/viewdoc/download?doi= (accessed 25.07.2022)

           7.     Zakrevskyi O. Friend or Foe. (in Russian) https://dou.ua/forums/topic/10097/ (accessed: 25.07.2022)

           8.     STANAG 4193. Technical Characteristics Of The IFF Mk XIIA System. NATO, 2016. p. 45. https://nhqc3s.hq.nato.int/Apps/Architecture/NISP/volume2/ch03s03.html (accessed 25.07.2022)

           9.     Kanashchenkov A.I., Merkulov V.I. Radar systems of multifunctional aircraft. M.: Radiotechnika, 2006. 656 p. (in Russian)

       10.     Kamaltinov G.G. Recognition of objects on the battlefield. Analysis of world experience. Armament and military equipment. 2016. 4. P. 22–26. (in Ukrainian) http://nbuv.gov.ua/UJRN/ovt_2016_4_5

       11.     Rohan P., Gangopadhyay A., Erbacher A. R., Busartet C. Camouflaged object detection system at the edge. Automatic Target Recognition XXXII. Vol. 12096. SPIE, 2022. https://doi.org/10.1117/12.2618869

       12.     Nolan P., Hamilton S. IFF using Beamforming in Telemetry Beacons. 2021 IEEE Western New York Image and Signal Processing Workshop (WNYISPW), IEEE, 2021. P. 1–5 https://doi.org/10.1109/WNYISPW53194.2021.9661287

       13.     Korolyov V.Yu., Ogurtsov M.I., Kochubinsky A.I. Identification of Technical Objects in the Special Networks According to the Principle of “Friend Or Foe” Control Systems and Computers. 2021. 4. P. 3–12 (in Ukrainian) https://doi.org/10.15407/csc.2021.04.003

       14.     Korolyov V. Yu., Ogurtsov M.I., Khodzinskyi O.M. Multilevel Identification Friend Or Foe of Objects and Analysis of the Applicability of Post-Quantum Cryptographic Algorithms for Information Security. Cybernetics and Computer Technologies. 2020. 3. P. 74–84. (in Ukrainian) https://doi.org/10.34229/2707-451X.20.3.7



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