Improving methods and models for artillery combat control
Keywords:
Combat capability, artillery unit, stochastic modeling, firing effectiveness, Markov model, combat employment controlSynopsis
This chapter deals with methodological approaches to estimating the effectiveness of the combat employment of artillery units considering minimization of the loss of combat capability. The definition of combat capability is proposed, which is seen as the ability of a unit to perform assigned tasks under specified operating and external conditions. The influence of external factors and loads on the state of the unit and on the intensity of failure of its elements is analyzed. A stochastic model of the combat operation of an artillery battery is presented. The model is based on a discrete Markov chain structure which allows to estimate time and dynamic characteristics, including the recovery rate, the probability of destructing a target and the average firing time. Criteria for an effective shot are defined. The use of a combined criterion to estimate combat effectiveness is justified. The proposed approaches provide a scientific basis to predict combat capability, optimize control processes and decision-making in automated systems for estimating artillery fire effectiveness.
Simulation results demonstrate that the proposed approach allows maintaining the combat capability at a level of 0.78–0.81 for a 10-shot mission, while the ratio between optimal and worst mission structures reaches values from 4 to 10.
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143-169
Text Identifier of this Chapter
Chapter 6
Published
June 19, 2026
Copyright (c) 2026 Pavlo Gultsov, Oksana Maksymova, Yevhenii Dobrynin
How to Cite
Gultsov, P., Maksymova, O., & Dobrynin, Y. (2026). Improving methods and models for artillery combat control. 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. 143-169). Scientific Route OÜ®. https://doi.org/10.21303/978-9908-8450-1-2.ch6
