Method for determining three acoustic sensors for registering the ballistic wave of an artillery shot

Keywords:

Artillery shot, acoustic sensors, ballistic wave, shot verification, random disturbances, trajectory approximation

Synopsis

The chapter addresses the problem of improving the accuracy of determining the coordinates of the point where an artillery projectile impacts the surface under conditions of random disturbances by means of a rational selection of acoustic sensors for registering the ballistic wave. The factors influencing the effectiveness of acoustic measurements are analyzed, including registration errors, the probability of the sensors being in an operational state, and their spatial arrangement relative to the firing direction line. An approach is proposed for determining three most suitable acoustic measuring devices from the available set, taking into account the combined effect of the specified factors. The obtained results create prerequisites for the practical implementation of the artillery shot verification method and for estimating the coordinates of the projectile impact point in a mode close to real time.

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

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. 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., 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

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., 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

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

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

Hrinov, B. V., Kyrychenko, I. K. (2008). Analitichna heometriya. Kharkiv: Himnaziya, 340 p.

Kadilnikov, T. M., Kochetkova, I. B., Sushko, L. F., Bilova, O. V. (2012). Analitichna heometriya u prostori. Dnipropetrovsk: NMETAU, 48.

Bondarenko, N. V., Otrashevska, V. V. (2022). Analitichna heometriya. Kyiv: KNUBA, 84.

Kartashov, M. V. (2008). Imovirnist, protsesy, statystyka. Kyiv: Vydavnychopolihrafichnyi tsentr “Kyivskyi universytet”, 494.

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

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.

Hampel, R., Wagenknecht, M., Chaker, N. (2000). Fuzzy control: Theory and practice. New York: Physika-Verlag, Heidelberg, 410. https://doi.org/10.1007/978-3-7908-1841-3

Zadeh, L. A., Abbasov, A. M., Yager, R. R., Shahbazova, S. N., Reformat, M. Z. (Eds.) (2014). Recent Developments and New Directions in Soft Computing. Studies in Fuzziness and Soft Computing. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-06323-2

Jamshidi, M., Kreinovich, V., Kacprzyk, J. (Eds.) (2013). Advance trends in soft computing. Cham: Springer-Verlag, 468. https://doi.org/10.1007/978-3-319-03674-8

Kosko, B. (1994). Fuzzy systems as universal approximators. IEEE Transactions on Computers, 43 (11), 1329–1333. https://doi.org/10.1109/12.324566

Mamdani, E. H., Assilian, S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, 7 (1), 1–13. https://doi.org/10.1016/s0020-7373(75)80002-2

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June 19, 2026

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How to Cite

Demydenko, V., Dobrynin, Y., Maksymov, M., & Riaboshapka, R. (2026). Method for determining three acoustic sensors for registering the ballistic wave of an artillery shot. In M. Maksymov, P. Gultsov, O. Toshev, O. Sidelnykov, R. Riaboshapka, O. Brunetkin, V. Davydov, V. Demydenko, M. Maksymov, O. Maksymova, Y. Dobrynin, O. Maksymov, & V. Boltenkov, Simulation modeling of artillery systems for improving game simulators. From theory to practice (pp. 218-244). Scientific Route OÜ®. https://doi.org/10.21303/978-9908-8450-1-2.ch9