The Automatic Target Recognition (ATIR) problem generally involves the acquisition, digitization and processing of video/IR signals from a given scene, in which the "targets" of interest are to be identified. There has been, up to date, no single effective procedure to handle a wide class of targets acquired by different sensors under different conditions. There has been, however, increasing success in decision making under uncertainty, using a rule based approach. In this paper, the need to appropriately model the types of uncertainties inherent in the decision process, and the need to compensate for disparate evidence sources is emphasized. Along with this, a systematic approach towards uncertainty management within the ATR problem domain is presented.