An obvious use for feature and attribute data is for target classification (discrimination, type, identification, or recognition) and in combat identification. An additional use is in the data (or track) association process to reduce the misassociations. In target tracking, the data association function is often decomposed into two steps. The first step, the gating process, 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. Previous papers discussed for integrating features and attributes into target track processing. The primary concern of this paper is to further clarify the distinction between simple features and categorical features and the differences in the processing methods in the data association process for tracking small targets with data from one or multiple sensors.