An Automatic Target Classifier using Model Based Image Processing

Abstract

A primary mission of air assets is to detect and destroy enemy ground targets. In order to accomplish this mission, it is essential to detect, track, and classify contacts to determine which are valid targets. Traditional combat identification has been performed using all-weather sensors and processing algorithms designed specifically for such sensor data. Electro- optical (EO) sensors produce a very different type of data that does not lend itself to traditional combat identification algorithms. This paper will detail how we analyzed the visual and physical characteristics of a large number of potential targets. The results of this analysis were used to drive the requirements of a demonstration system. We will detail the test data we collected from the military and CAD models for likely targets, as well as overall requirements for system performance.