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We describe an experimental, model-based automatic target recognition (ATR) system, called XTRS, for recognizing tactical vehicles in real or synthetic laser-radar (LADAR) range and intensity images corresponding to a forwardlooking, CO/sub 2/ laser radar (LADAR) that is carried either on a ground vehicle or on an airborne platform. Various aspects of the system's operation are illustrated through a variety of examples. Generic techniques are highlighted whenever possible. A first such technique is the use of feature-indicating interest images to focus attention on specific areas of the input imagery. A second is the use of an application-independent matching engine for matching features extracted from the imagery against an application-dependent appearance model hierarchy that represents the objects to be recognized. A third generic technique is the system's architectures and its control mechanism. Following the description of XTRS, we discuss XTRS's recognition performance on real data collected with the groundbased version of the ladar sensor. We then provide a detailed account of XTRS's performance on synthetic datasets created to rest the limits of system performance. Finally, we briefly discuss the use of XTRS in conjunction with the airborne version of the sensor. Overall, more than 1500 range and intensity image pairs were used throughout XTRS's development.