Algorithm for Determining the Probability of Target Detection and Recognition by an Aviation Thermal Vision System in Noise Conditions

Abstract

Thermal imaging equipment is widely used in modern military operations due to its ability to observe targets even in adverse weather conditions continuously. Thermal imaging surveillance systems (TISS) are primarily designed to detect, recognize, and identify targets. Despite the progress, existing methods do not allow quickly calculating the probability of detecting, recogniz- ing, or identifying a target at user-defined distances from the TISS to the target. The article aims to develop a more advanced method and algorithm for calculating the probability of detection, recognition, and identification of a target by a noise-limited thermal imaging surveillance system. A more advanced (convenient) algorithm and method for calculating the probability of detection, recognition, and identi- fication of an object (target) by a thermal imaging surveillance system at a given range have been developed. This is based on the minimum resolution temperature difference, Johnson’s criterion, as well as the TTPF and TRTPF functions. The proposed algorithm makes it relatively easy to calculate the probability of detecting, recognizing, and identifying a target by a thermal imaging system, which is limited by system noise.