Probability of Target Discrimination by the Contrast-Limited Thermal Vision System of a Uav

Abstract

Equipping modern unmanned aerial vehicles (UAVs) with thermal imaging cameras expands their potential utilization in various environmental conditions, enabling efficient aerial reconnaissance and execution of combat-related tasks. The primary objec- tives for target discrimination encompass detection, recognition, and identification. However, existing methods and algorithms for determining the probability of distinguishing targets do not offer an efficient and swift means of calculating these probabili- ties based on the target’s distance. This article aims to develop a novel method for calculating the probability of detecting, recognizing, and identifying an object (target) using a thermal imaging surveillance system. The proposed approach involves an improved algorithm that utilizes the Johnson criterion, as per the NATO standard 4347, the Schultz approximation of the threshold contrast for the operator’s perception of the image on the display screen, and incorporates the objective function of probability transfer along with probability transfer functions based on the target’s distance. An example illustrating the calculation of the target discrimination probability is included to provide clarity. With the suggested algorithm, the probability of detecting, recognizing, and identifying the target through the contrast-limited thermal imaging system of the drone can be rapidly calculated.