Method of parabolic approximation for determining the impact point coordinates of an artillery projectile
Keywords:
Artillery shot, firing verification, ballistic wave, acoustic reconnaissance, trajectory approximation, random disturbancesSynopsis
This section considers a method for verifying an artillery shot under conditions of random disturbances, which is based on the registration of acoustic fields formed by ballistic and muzzle waves. The position of the proposed approach among modern technologies for ensuring the accuracy of artillery fire is demonstrated, and the feasibility of using the ballistic wave as a source of useful information for estimating projectile flight parameters is substantiated.
A general description of the method, the layout of the measuring equipment, and the sequence of measurement data processing are presented. The method is based on recording the moments when the projectile passes over spatially separated observation points, followed by approximation of the flight trajectory using a system of parabolas. The proposed algorithm takes into account possible changes in the relative positions of the measurement points with respect to the ascending and descending branches of the trajectory, which makes it possible to partially compensate for random disturbances caused by instability of the initial velocity and other firing-related factors.
The effectiveness of the method is investigated by means of simulation modeling for a large-caliber artillery projectile, taking into account random disturbances of temporal parameters. It is shown that the use of a system of approximating parabolas provides estimation of the projectile impact point coordinates with an error on the order of fractions of a percent of the firing range. A comparative analysis with the traditional method of compensating random disturbances by successive corrective shots is carried out, and the results of a field experiment involving the registration of ballistic wave signals are presented. The obtained results confirm the fundamental possibility of verifying an artillery shot using a single firing with acceptable accuracy.
References
Dobrynin, Y., Volkov, V., Maksymov, M., Boltenkov, V. (2020). Development of physical models for the formation of acoustic waves at artillery shots and study of the possibility of separate registration of waves of various types. Eastern-European Journal of Enterprise Technologies, 4 (5 (106)), 6–15. https://doi.org/10.15587/1729-4061.2020.209847
Boltenkov, V., Brunetkin, O., Dobrynin, Y., Maksymova, O., Kuzmenko, V., Gultsov, P. et al. (2021). Devising a method for improving the efficiency of artillery shooting based on the Markov model. Eastern-European Journal of Enterprise Technologies, 6 (3 (114)), 6–17. https://doi.org/10.15587/1729-4061.2021.245854
Brunetkin, O., Beglov, K., Brunetkin, V., Maksymov, О., Maksymova, O., Havaliukh, O., Demydenko, V. (2020). Construction of a method for representing an approximation model of an object as a set of linear differential models. Eastern-European Journal of Enterprise Technologies, 6 (2 (108)), 66–73. https://doi.org/10.15587/1729-4061.2020.220326
Dobrynin, Y., Brunetkin, O., Maksymov, M., Maksymov, О. (2020). Constructing a method for solving the riccati equations to describe objects parameters in an analytical form. Eastern-European Journal of Enterprise Technologies, 3 (4 (105)), 20–26. https://doi.org/10.15587/1729-4061.2020.205107
Maksymov, M. V., Brunetkin, O. I., Beglov, K. V., Alyokhina, S. V., Butenko, O. V. (2022). Automatic Control for the Slow Pyrolysis of Organic Materials with Variable Composition. Advanced Control Systemss: Theory and Applications. Series in Automation, Control and Robotics. River Publishers, 397–434. https://doi.org/10.1201/9781003337010-16
Brunetkin, O., Maksymov, M., Dobrynin, Y., Demydenko, V., Sidelnykov, O. (2024). Development of a process model for determining the composition and energy characteristics of a pyrotechnic mixture using the library method. EUREKA: Physics and Engineering, 5, 99–112. https://doi.org/10.21303/2461-4262.2024.003453
Brunetkin, O., Dobrynin, Y., Maksymenko, A., Maksymova, O., Alyokhina, S. (2020). Inverse problem of the composition determination of combustion products for gaseous hydrocarbon fuel. Computational Thermal Sciences: An International Journal, 12 (6), 477–489. https://doi.org/10.1615/computthermalscien.2020034878
Brunetkin, O. I., Beglov, K. V., Maksymov, M. M., Ulytska, O. O. (2021). Model and method of controlled pyrolysis of organic sub-stances of variable composition. Problems of Control and Informatics, 66 (1), 134–146. https://doi.org/10.34229/1028-0979-2021-1-12
Brunetkin, O., Sidelnykov, O., Maksymov, M., Dobrynin, Y. (2025). Improving the model for determining the composition of gunpowder gases during thermal destruction of gunpowder in a limited volume space. Eastern-European Journal of Enterprise Technologies, 3 (6 (135)), 35–45. https://doi.org/10.15587/1729-4061.2025.330654
Brunetkin, O., Maksymov, M., Brunetkin, V., Maksymov, О., Dobrynin, Y., Kuzmenko, V., Gultsov, P. (2021). Development of the model and the method for determining the influence of the temperature of gunpowder gases in the gun barrel for explaining visualize of free carbon at shot. Eastern-European Journal of Enterprise Technologies, 4 (1 (112)), 41–53. https://doi.org/10.15587/1729-4061.2021.239150
Damarla, T. (2015). Battlefield Acoustics. Springer International Publishing, Switzerland, 262. https://doi.org/10.1007/978-3-319-16036-8
Tarakhtii, O. S., Gultsov, P. S., Maksymov, O. M. (2023). Pat. No. 127193. Sposib vyznachennia koordynaty zustrichi artyleriiskoho snariada z poverkhneiu. declareted: 28.04.2021; published: 31.05.2023, Bul. No. 22.
Bolton, J. Q. (2023). The More Things Change … Russia’s War in Ukraine Mirrors the Past as Much as It Shows the Future. Military Review, 1–14. Available at: https://www.armyupress.army.mil/Journals/Military-Review/Online-Exclusive/2023-OLE/The-More-Things-Change/
Shevtsov, R. (2023). An improved mathematical model of fire damage to enemy artillery units by missile forces and artillery in operations. Social Development and Security, 13 (1), 13–22. https://doi.org/10.33445/sds.2023.13.1.2
Sviderok, S. M., Shabatura, U. V., Prokopenko, A. O. (2016). Technique of the fire correction of artillery systems according to modern requiremernts to the data preparation for shooting. Military Technical Collection, 14, 99–103. https://doi.org/10.33577/2312-4458.14.2016.99-103
Krzyzanowski, S. (2018). How to assess the accuracy of artillery fire. Scientific Journal of the Military University of Land Forces, 187 (1), 25–39. https://doi.org/10.5604/01.3001.0011.7355
Šilinger, K., Brabcová, K., Potužák, L. (2019). Assessment of possibility to conduct fire for effect without adjust fire according to observational distance of a target in artillery automated fire control systems. International Journal of Electrical Engineering and Computer Science, 1, 103–108.
Bartulović, V., Trzun, Z., Hoić, M. (2023). Use of unmanned aerial vehicles in support of artillery operations. Strategos, 7 (1), 71–92. Available at: https://www.researchgate.net/publication/372657457_Use_of_Unmanned_Aerial_Vehicles_in_Support_of_Artillery_Operations
Khudov, H., Yuzova, I., Lisohorskyi, B., Solomonenko, Y., Mykus, S., Irkha, A. et al. (2021). Development of methods for determining the coordinates of firing positions of roving mortars by a network of counter-battery radars. EUREKA: Physics and Engineering, 3, 140–150. https://doi.org/10.21303/2461-4262.2021.001821
Kochan, R., Kochan, O., Trembach, B., Kohut, U., Zawislak, S., Falat, P., Warwas, K. (2019). Theoretical Error of Bearing Method in Artillery Sound Ranging. 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 615–619. https://doi.org/10.1109/idaacs.2019.8924450
Zhuravlev, А., Orlov, S., Shuliakov, S. (2020). Mathematical model of the flight path of a projectile of a long-range artillery system. Systems of Arms and Military Equipment, 3 (63), 62–68. https://doi.org/10.30748/soivt.2020.63.09
Wessam, M. E., Chen, Z. H. (2015). Firing Precision Evaluation For Unguided Artillery Projectile. Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering, 123. https://doi.org/10.2991/aiie-15.2015.156
STANAG 4355 (2022). The Modified Point Mass and five degrees of freedom trajectory models – AOP-4355 EDITION A. Washington: United States Department of Defense. Available at: https://www.scribd.com/document/492052990/STANAG-4355-The-modified-point-mass-and-five-degrees-of-freedom-trajectory-models-Edition-3
Aldoegre, M. (2019). Comparison between trajectory models for firing table application. North-West University. Available at: https://repository.nwu.ac.za/items/cad7cd66-e45d-4da8-aa79-1723e382a549
Le Bot, O., Gervaise, C., Mars, J. I. (2016). Time-difference-of-arrival estimation based on cross recurrence plots, with application to underwater acoustic signals. Recurrence Plots and Their Quantifications: Expanding Horizons. Springer, 265–288. https://hal.science/hal-01343668/document
Dobrynin, Y. V., Boltenkov, V. O., Kuzmenko, V. V., Maksymov, O. M. (2022). Development of a universal binary classifier of the state of artillery barrels by the physical fields of shots. Applied Aspects of Information Technology, 5 (4), 289–302. https://doi.org/10.15276/aait.05.2022.19
Maksymov, M. V., Boltenkov, V. O., Gultsov, P. S., Maksymov, O. M. (2023). Verification of artillery fire under the influence of random disturbances for the computer game ARMA 3. Applied Aspects of Information Technology, 6 (4), 362–375. https://doi.org/10.15276/aait.06.2023.24


