doi: 10.17586/2226-1494-2024-24-3-513-519


Management of space surveillance radar temporal resource on fuzzy set theory

Y. Babkin, G. Zverev, A. V. Timoshenko, A. Y. Perlov, M. F. Bulatov


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Babkin Yu.V., Zverev G.P., Timoshenko A.V., Perlov A.Yu., Bulatov M.F. Management of space surveillance radar temporal resource on fuzzy set theory. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2024, vol. 24, no. 3, pp. 513–519 (in Russian). doi: 10.17586/2226-1494-2024-24-3-513-519


Abstract
This paper addresses the problem of optimizing the use of temporal resources of a radar station (RS) under limited time resources. Special attention is given to the necessity of considering a multitude of compensatory optimality criteria when allocating the RS operating time. The proposed approach is based on the use of fuzzy set theory which represents an innovative solution in the context of this task. The task of managing the RS temporal resources is formulated as the search for an optimal work schedule among all potentially possible options. This schedule should minimize the values of all partial optimality criteria. Fuzzy set theory is applied to solve this problem, allowing for the consideration of uncertainty and variability in task execution conditions. An algorithm for managing the RS temporal resources was presented. The review results confirm the probable increase in efficiency, especially in conditions of acute shortage of temporal resources, ensuring their optimal distribution among current tasks. Furthermore, the algorithm enables decisions to be made about the possibility of performing special or additional tasks without compromising the main monitoring functions. The review of the proposed algorithm provides a basis for hypothesizing its advantages over traditional methods of managing the RS temporal resources. In particular, the use of fuzzy set theory allows for more flexible responses to changes in task execution conditions and enhances the overall adaptability of the system. In the future, this approach could be adapted and applied in other areas where there is a need for resource optimization under conditions of limitation and uncertainty of external factors.

Keywords: RLS, temporal resource, space monitoring, fuzzy sets

Acknowledgements. This work was done with the support of MSU Program of Development, Project No. 24-S01-04.

References
  1. Observation Methods and Models of Space Debris. Ed. by G.G. Raikunov. Moscow, Fizmatlit Publ., 2014, 248 p. (in Russian)
  2. Levkina P.A. Physical and orbital characteristics of space debris objects based on optical observation data. Dissertation for the degree of candidate of physical and mathematical sciences. Institute of Astronomy of the Russian Academy of Sciences, 2016. Available at: http://www.gaoran.ru/russian/diss/LevkinaPA.pdf (accessed: 03.09.2023). (in Russian)
  3. Veniaminov S.S., Chervonov A.M. Space Debris is a Threat to Common Humanity. Moscow, Space Research Institute Publ., 2012, 192 p. (in Russian)
  4. Savrasov Iu.S. Algorithms and Programs in Radio Detecting and Ranging. Moscow, Radio i Svjaz' Pub., 1985, 216 p. (in Russian)
  5. Biacino L., Gerla G. Fuzzy Logic, Continuity and Effectiveness. Archive for Mathematical Logic, 2002, vol. 41, no. 7, pp. 643–667. https://doi.org/10.1007/s001530100128
  6. Laborie P., Rogerie J., Shaw P., Vilím P. IBM ILOG CP optimizer for scheduling. Constraints, 2018, vol. 23, no. 2, pp. 210–250. https://doi.org/10.1007/s10601-018-9281-x
  7. Vedyakov A.A., Milovanovich E.V., Slita O.V., Tertychny-Dauri V.Yu. Variational problem of adaptive optimal control. Theoretical and applied computer analysis. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2023, vol. 23, no. 2, pp. 252–262. (in Russian). https://doi.org/10.17586/2226-1494-2023-23-2-252-262
  8. Bessmertniy I. A Set-theoretic approach to the logical inference in knowledge bases. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2010, no. 2(66), pp. 43–48. (in Russian)
  9. Tatarnikova T.M., Arkhiptsev E.D. Fuzzy logic controller algorithm for placing files in a data storage system. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2023, vol. 23, no. 6, pp. 1171–1177. (in Russian). https://doi.org/10.17586/2226-1494-2023-23-6-1171-1177
  10. Lazarev A.A., Gafarov E.R. Scheduling Theory. Problems and Algorithms. Moscow, Lomonosov Moscow State University, 2011, 222 p. (in Russian)
  11. Dogadina E.P., Kropotov Yu.A. Determination steamed ensemble to realization of the work on example of the using the genetic algorithm. Systems of Control, Communication and Security, 2015, no. 4, pp. 142–149. (in Russian)
  12. Bezginov A.N., Tregubov S.Yu. Exploring the existing approaches for evaluating the quality of university course timetables and description of the novel multi-criteria approach based on fuzzy logic. Control Sciences, 2011, no. 2, pp. 52–59. (in Russian)
  13. Bogatyrev V.A., Bogatyrev S.V., Bogatyrev A.V. Assessment of the readiness of a computer system for timely servicing of requests when combined with information recovery of memory after failures. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2023, vol. 23, no. 3, pp. 608–617. (in Russian). https://doi.org/10.17586/2226-1494-2023-23-3-608-617
  14. Bogatyrev V.A., Bogatyrev S.V., Bogatyrev A.V. Reliability and timeliness of servicing requests in infocommunication systems, taking into account the physical and information recovery of redundant storage devices. Proc. of the 2022 International Conference on Information, Control, and Communication Technologies (ICCT), 2022, pp. 1–4. https://doi.org/10.1109/icct56057.2022.9976800


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