Analytical Approach to UAV Cargo Delivery Processes Under Malicious Interference Conditions

The instability of the geopolitical situation due to the high terrorist danger leads to the need to take into account at the planning stage the capabilities of intruders to perform UAV flight missions. A general method for analyzing the process of cargo delivery by UAVs (Unmanned Aerial Vehicles) to hard-to-reach areas during emergencies has been proposed. This method allows for the evaluation of UAV effectiveness based on the probability of successful cargo delivery within a specified time limit. The method is based on applying topological transformation techniques to stochastic networks. The cargo delivery process is modeled as a stochastic network, followed by the determination of its equivalent function and the use of Heaviside decomposition to calculate the distribution function and the expected delivery time. This presentation of the studied process for the first time made it possible to take into account the impact on the flight mission of the UAV of the destructive impact from the attacker. This approach allows the destructive effects on the UAV from malicious interference to be considered. The input data used for the analysis are parameters that characterize the properties of individual processes within the stochastic network, represented as branches, which are computed using methodologies published in earlier studies. It has been demonstrated that the resulting distribution function of the mission completion time can be accurately approximated by a gamma distribution with a level of precision suitable for practical applications. In this case, the gamma distribution parameters are determined using the equivalent function of the stochastic network. The proposed method can be used by flight planners when scheduling UAV operations in emergency zones, especially in scenarios where there is a risk of malicious interference.

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Publication Details

Journal
Mathematics
Published
2025-06-18
DOI
https://doi.org/10.3390/math13122008
Citations
2
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
9.99

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article

Analytical Approach to UAV Cargo Delivery Processes Under Malicious Interference Conditions

Fazliddin Makhmudov, Young Im Cho, Gamzatdin Bekbaev, Alpamis Kutlimuratov et al.
2 citations
Mathematics
UAV Applications and Optimization
9.99
article

Analytical Approach to UAV Cargo Delivery Processes Under Malicious Interference Conditions

Fazliddin Makhmudov, Young Im Cho, Gamzatdin Bekbaev, Alpamis Kutlimuratov, Sergey Egorenkov, Andrey Privalov, Andrey Pryadkin
article en
2 citations

Abstract

The instability of the geopolitical situation due to the high terrorist danger leads to the need to take into account at the planning stage the capabilities of intruders to perform UAV flight missions. A general method for analyzing the process of cargo delivery by UAVs (Unmanned Aerial Vehicles) to hard-to-reach areas during emergencies has been proposed. This method allows for the evaluation of UAV effectiveness based on the probability of successful cargo delivery within a specified time limit. The method is based on applying topological transformation techniques to stochastic networks. The cargo delivery process is modeled as a stochastic network, followed by the determination of its equivalent function and the use of Heaviside decomposition to calculate the distribution function and the expected delivery time. This presentation of the studied process for the first time made it possible to take into account the impact on the flight mission of the UAV of the destructive impact from the attacker. This approach allows the destructive effects on the UAV from malicious interference to be considered. The input data used for the analysis are parameters that characterize the properties of individual processes within the stochastic network, represented as branches, which are computed using methodologies published in earlier studies. It has been demonstrated that the resulting distribution function of the mission completion time can be accurately approximated by a gamma distribution with a level of precision suitable for practical applications. In this case, the gamma distribution parameters are determined using the equivalent function of the stochastic network. The proposed method can be used by flight planners when scheduling UAV operations in emergency zones, especially in scenarios where there is a risk of malicious interference.

MathematicsVol. 13(12)
Gachon University (KR), Perm Military Institute (RU), Military Academy of Communications named after Marshal of the Soviet Union SM Budennogo (RU), Tashkent State University of Economics (UZ), Westminster International University in Tashkent (UZ)
Gachon University
Openalex Percentile: Top 3%
UAV Applications and Optimization
9.99
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