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The problem of interfering scatters in high range resolution (HRR) radar data is addressed in this paper. We derive, using a scattering center representation of a target, classifiers that can handle the unknown phases of the centers. We also show how to incorporate uncertainties in the magnitudes and positions of the scattering centers. The automatic target recognition (ATR) problem is discussed in a Bayesian setting, and we show how the uncertainties can be handled by such scattering center classifiers. Monte Carlo simulations are used to evaluate the performance and robustness of the classifiers for simple test cases, and data from electromagnetic prediction codes are used to illustrate the behavior on real targets.