Integration of features and attributes into target tracking

An obvious use for feature and attribute data is for target typing (discrimination, classification, identification, or recognition) and in combat identification. Another use is in the dark (or track) association process. The data association function is often decomposed into two steps. The first step is a preliminary threshold process to eliminate unlikely measurement-track pairs. This is followed by the second step, the process of selecting measurement-track pairs or assigning weights to measurement-track pairs so that the tracks can be updated by a filter. The primary concern of this paper is the use of feature and attribute data in the data association process for tracking small targets with data from one or more sensors.