ISSN: 2949-401X

Pravidlo M. N., Biryukov P. A., Kiselev A. P.

Annotation: An algorithm for generating the trajectory of an aerial target based on flight data recorder information is described. The algorithm allows generating reliable trajectory data of aerial target motion if the flight data of the aerial target motion is incomplete. One of the problems associated with simulating the trajectories of objects in 3D space during computer simulation is considered using the example of modeling guidance algorithms for aviation weapons in various tactical conditions. Simulating the motion of an aerial target in the atmosphere is one of the significant problems in using computer models. To evaluate the functioning of aerial target guidance systems, it is necessary to simulate the motion of a real target as realistically as possible, including instantaneous changes in trajectory coordinates and all random variables accompanying motion in the real atmosphere, such as trajectory instabilities, fluctuations in angular orientation parameters, etc. The difficulty of solving this problem lies in the lack of sufficient information about the statistical motion parameters, flight characteristics, and tactical maneuvers of real targets. Modern combat aircraft are equipped with flight data recording systems that allow recording the parameters determining the functioning of the targeting and navigation complex, including the motion parameters of observed aerial targets. Based on this, an approach to simulating the motion of a real target in a computer model is proposed, which consists in generating the trajectory of an aerial target based on data from a flight data recording system capable of registering the motion parameters of the observed target. An analysis of records from modern recording systems indicates the presence of severe noise and distortion in the recorded data. To eliminate them, well-known data recovery methods described in the literature are used. However, traditional data recovery methods prove inapplicable in the presence of anomalous jumps and gaps in the data. The proposed algorithm for recovering the acquired data uses well-known filtering methods and an original algorithm for eliminating anomalous distortions in the recorded data, which together makes it possible to obtain a dataset describing the trajectory and motion parameters of the target, serving as the basis for reproducing motion in a computer model of a maneuvering target. Since the proposed data recovery method does not impose high requirements on processing system performance, its use makes it possible to automate the high-quality processing of large volumes of data for the subsequent analysis of aviation weapons employment conditions in real tactical situations.

Keywords: flight data recording system, aviation guided weapon, aerial target, simulation modeling, computer model, experimental data, approximation

For citation: Pravidlo M. N., Biryukov P. A., Kiselev A. P. Trajectory generation for an aerial target based on flight data recorder data for computer simulation. Aerospace Engineering and Technology. 2026. Vol. 4, no. 1, pp. 92–104. (In Russ.) https://doi.org/10.52467/2949-401X-2026-4-1-92-104; https://elibrary.ru/CNFSDI

References
1. Pashkovsky I. M., Leonov V. A., Poplavsky B. K. Letnye ispytaniya samoletov i obrabotka rezul’tatov ispytanij [Flight tests of aircraft and processing of test results]. Moscow, Mashinostroenie, 1985. 416 p. (In Russ.)
2. Korsun O. N., Stulovsky A. V., Medvedkov A. V., Korolev A. N. Estimation of flight range using a population optimization algorithm. Sbornik dokladov Yubilejnoj Vserossijskoj nauchno-tekhnicheskoj konferencii “Aviacionnye sistemy v XXI veke” [Collection of reports of the Anniversary All-Russian Scientific and Technical Conference “Aviation Systems in the 21st Century” (Moscow, April 21–22, 2022)]. Moscow, 2022. P. 115. (In Russ.) https://elibrary.ru/KCCMIQ
3. Korsun A. Yu., Medvedkov A. V., Pravidlo M. N., Korolev A. N. Statistical modeling methodology. // Sbornik dokladov Yubilejnoj Vserossijskoj nauchno-tekhnicheskoj konferencii «Aviacionnye sistemy v XXI veke» [Collection of reports of the Anniversary All-Russian Scientific and Technical Conference “Aviation Systems in the 21st Century” (Moscow, April 21–22, 2022)]. Moscow, 2022. Pp. 116–117. (In Russ.) https://elibrary.ru/WPTAFU
4. Pravidlo M. N., Kharkov V. P., Korsun O. N., Moung Htang Om. Nonlinear stochastic estimation of altitude and vertical flight speed in real time. IOP Conference Series: Materials Science and Engineering. Workshop on Materials and Engineering in Aeronautics (MEA 2020) 16th–17th October 2020, Moscow, Russia. IOP Publishing, 2021. Vol. 1027. 012009. https://doi.org/10.1088/1757-899X/1027/1/012009
5. Zhdanyuk B. F. Osnovy statisticheskoj obrabotki traektornyh izmerenij [Basics of statistical processing of trajectory measurements]. Moscow: Sovetskoe Radio, 1978. 384 p. (In Russ)
6. Korsun O. N., Stulovsky A. V., Pravidlo M. N. Algorithms for Selection and Combination of Sliding intervals for identification Based on Large Volumes of Flight Data. E3S Web of Conferences: Proceedings of The 2nd international Conference on High-Speed Transport Development (HSTD 2023). Moscow, 29 aug–03 sept. 2023. Vol. 446. P. 06001. https://doi.org/10.1051/e3sconf/202344606001
7. Korsun O. N., Korolev A. YU., Stulovskiy A. V. Aircraft overloads restoration by measuring its velocity and orientation angles based on the nonlinear programming method. Herald of the Bauman Moscow State Technical University. Series Instrument Engineering. 2025. Vol. 152, no. 3, pp. 105–120. (In Russ.) https://elibrary.ru/NSQNYJ
8. Korsun O. N., Stulovskii A. V. Methodology of identification of dynamic systems based on data from field experiments (Using examples of identification of parameters of aircraft models according to flight data). Sbornik statej I mezhdunarodnoj nauchnoj konferencii “Teoriya i realizaciya informacionnyh sistem” [Collection of articles of the I international scientific conference “Theory and implementation of information systems”, Moscow, May 15, 2025]. Moscow, 2025. Pp.13–21. (In Russ.) https://elibrary.ru/VFMJXZ
9. Korsun O. N., Korolev A. Yu., Stulovsky A. V. The use of spline approximation in the task of restoring a noisy signal. Navigaciya, navedenie i upravlenie letatel’nymi apparatami: tezisy dokladov V Vserossijskoj nauchno-tekhnicheskoj konferencii «Modelirovanie aviacionnyh sistem» [Navigation, guidance and control of aircraft: abstracts of the V All-Russian Scientific and Technical Conference “Modeling of Aviation Systems” (Moscow, November 27–28, 2024)]. Moscow, 2024. Pp. 114–115. https://elibrary.ru/WUDWIF
10. Bulgakov V. V., Korsun O. N., Kulabukhov V. S., Stulovsky A. V., Timofeev D. S. Algorithms of increasing the calculation accuracy for an aircraft operation angle. Journal of computer and System Sciences International. 2016. Vol. 55, no. 1, pp. 150–161. https://doi.org/10.1134/S1064230715050032
11. Korsun O. N., Stulovsky A. V. Recovery of aircraft motion parameters using the optimal control algorithms. Journal of computer and System Sciences International. 2023. Vol. 62, no. 1, pp. 61–72. https://doi.org/10.1134/S1064230723010057
12.Korsun O. N., Stulovsky A. V. Estimation of the angular position of an aerial vehicle based on measurements of the parameters of its linear motion. Journal of Computer and Systems Sciences International. https://doi.org/10.1134/s1064230723030085
13.Burenok V. M., Naydenov V. G., Polyakov V. I. Matematicheskie metody i modeli v teorii informacionno-izmeritel’nyh sistem: uch. Posobie [Mathematical methods and models in the theory of information and measuring systems: study. Manual]. Moscow: Mashinostroenie, 2011. 336 p. (In Russ.) https://elibrary.ru/RYRXFN
14.Korsun O. N., Nikolaev S. V., Pushkov S. G. An algorithm for estimating systematic measurement errors for air velocity, angle of attack, and sliding angle in flight testing. Journal of Computer and Systems Sciences International. 2016. Vol. 55, no. 3, pp. 446–457. https://doi.org/10.1134/S1064230716030114
15. Nader Alhaf M. Algorithmic Support of Estimation and Identification of Descending Vehicle Performance in Flight Testing. Herald of the Bauman Moscow State Technical University. Series Mechanical Engineering. 2004. No. 4. Pp. 27–42. (In Russ.)
16. Budaev V. D., Vorobyov V. V., Zasukhin A. S., Sizikov D. O. A method for improving the accuracy of FV trajectory motion by increasing the accuracy of FV motion parameters determination using optimal filtering techniques. International Research Journal. 2024. Vol. 145, no. 7. (In Russ.) https://doi.org/10.60797/IRJ.2024.145.7

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