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The automatic detection of targets in cluttered infrared imagery is considered. The environment for the problem is that of a "fire-and-forget" weapon, and the mission philosophy for such a weapon dictates that the weapon has to find one and only one target in the automatic detection phase. A detection system that meets this requirement is presented. The system uses techniques of image processing and pattern recognition, with the extension that ranking methods are used instead of thresholds to accommodate the requirement of finding one and only one target. A probability model of the system is developed to determine the system performance as a function of throughput and expressions derived for the probability that the object chosen by the system as the target is actually a target. In order to validate the theoretical results, the actual performance of the detection system on a database of 68 infrared images is determined and compared with the predicted performance of the system. It is shown that there is good correspondence between the empirical results and the theoretical performance.