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High range resolution (HRR) radar produces high resolution target signatures of moving ground targets that can be separated from ground clutter using Doppler processing. As a result, HRR sensors are a leading candidate to provide all weather, day/night, long-standoff identification of moving ground targets. Previous automatic target recognition (ATR) studies have demonstrated the usefulness of HRR ATR with traditional statistical techniques such as mean-squared error template-based classifiers. This paper presents the results on an initial investigation of the use of artificial neural network (ANN) classifiers for HRR ATR in a continuous tracking (CT) scenario.