We develop a theoretical bound on the receiver operating characteristics (ROC) associated with a target detector that bases its decision on the spatial distribution of extracted peak locations in synthetic-aperture (SAR) imagery. There are three basic steps to our analysis. In the first step, we formulate statistical models for both target and clutter regions of interest that have passed through a pre-screening stage. From these models, we then infer a corresponding detection procedure, which takes the form of a generalized likelihood ration test (GLRT). Finally, in the third step, we again use our statistical models to determine the ROC performance of the GLRT. This third step is where we believe our primary technical innovation lies. In the presence of uncertainty regarding target type and pose, it is generally difficult to obtain analytical performance expressions. We circumvent this problem by treating statistically the database of target exemplars. This approach has tow benefits. First, it suppresses the details of the database of exemplars, alleviating the need to specify the spatial configuration of points for every database entry. second, it leads to analytical performance expressions, which can be calculated with considerably less effort than is possible with Monte Carlo simulation.