Methodology for calculating the integral coefficient of intelligence protection of armored vehicles of the Security and Defense Forces of Ukraine

Abstract

The article presents a novel methodology for determining the integral coefficient of reconnaissance protection of armored vehicles used by the Security and Defense Forces of Ukraine. The rapid evolution of optical, infrared, radar, acoustic, seismic, and radio-technical reconnaissance systems has dramatically increased the probability of detection and subsequent destruction of armored vehicles on the modern battlefield. This highlights the urgent need for a formalized quantitative model capable of assessing the real level of multispectral detectability of armored platforms, taking into account both passive and active factors, including the operation of electronic warfare systems and counter-radio-controlled munition protection complexes.
The study substantiates reconnaissance protection as an integral property of an armored vehicle that reflects its ability to remain low-observable to the enemy across multiple detection channels. The proposed approach introduces a weighted aggregation model that combines partial coefficients of acoustic, thermal, optical, infrared, radar, seismic (vibration), and radio-technical visibility. Each coefficient is normalized based on field measurements, empirical data, or expert evaluation. The influence of active emitters ‒ electronic warfare systems, communication equipment, and counter-UAV jamming modules ‒ is incorporated through an additional radio-technical visibility factor, which significantly affects the overall detectability of a vehicle.
A ten-step methodology is developed, covering identification of combat conditions, detection spectra, monitoring of signature sources, normalization of visibility indicators, determination of weighting coefficients, and calculation of the integral index. The method enables scenario-based assessment of detectability during movement, firing, operation of EW/RCIED-countermeasures, deployment, or static concealment. The obtained integral coefficient allows classification of reconnaissance protection levels and supports operational planning decisions regarding routes, deployment positions, masking measures, and optimization of equipment settings.
The proposed model establishes a direct link between multispectral signature formation and the probability of detection, tracking, and targeting of armored vehicles. The results create scientific grounds for improving survivability, modernizing armored platforms, enhancing counter-reconnaissance capabilities, and integrating signature-management measures into a broader system of ensuring national security. Future research will focus on evaluating the effectiveness of counter-radio-controlled munition systems, forecasting UAV reconnaissance activity, and developing technologies for active degradation of enemy intelligence channels.