# Influence of the Probability of Object Recognition by a Thermal Imager on the Maximum Observation Range

## DOI:

https://doi.org/10.20535/RADAP.2022.88.77-85## Keywords:

thermal imager, maximum recognition range, probability of object recognition.## Abstract

The main function of thermal imaging systems is to detect and recognize objects (targets) with a given probability. One of the main characteristics of such thermal imagers is the maximum range of observation at a given probability of recognition. Many monographs and articles have been devoted to the development and research of goal recognition processes, in which methods of calculating the maximum recognition range (MRR) are proposed, based on Johnson's criterion for a probability of recognition of 50%. For the practical application of thermal imaging surveillance systems (TISS) it is necessary to know the MRR for a given probability of recognition.

The purpose of this article is to develop a method for calculating of the maximum recognition range in real conditions using TISS at a given probability of recognition.

A method for calculating MRR targets in real conditions with a given probability of recognition, which is based on the proposed model of image formation in the thermal imaging monocular, has been developed. It is proposed to consider TISS, the maximum range of which is limited by the contrast of the image or the system's own noise. The model of thermal imaging monocular is considered, which takes into account the parameters of the object of observation, atmosphere, lens, radiation detector, display, eyepiece and visual analyzer of the operator. The proposed model allowed to develop methods for calculating MRR for given recognition probabilities. The equations obtained for the calculation of the MRR for TISS, which are limited by the contrast of the image or the intrinsic noise of the system. An example of calculating the MRR of a thermal imaging monocular is considered.

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*Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia*, (88), pp. 77-85. doi: 10.20535/RADAP.2022.88.77-85.

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