The Army Research Laboratory (ARL), as part of its mission- funded exploratory development program, has been evaluating the use of a low-frequency, ultra-wideband imaging radar to detect tactical vehicles concealed by foliage. An instrumentation-grade measurement system has been designed and implemented by ARL. Extensive testing of this radar over the preceding 18 months has led to the establishment of a significant and unique data base of radar imagery. We are currently using these data to develop target detection algorithms which can aid an operator in separating vehicles of interest from background. This paper provides early findings from the algorithm development effort. To date, our efforts have concentrated on identifying computationally simple strategies for canvassing large areas for likely target occurrences--i.e., prescreening of the imagery. Phenomenologically-sound features are being evaluated for discrimination capability. Performance assessments, in terms of receiver operating characteristics, detail detection capabilities at various false alarm rates.