The work described in this paper focuses on recent progress in radar signal processing and target recognition techniques developed in support of WL/AARA target recognition programs. The goal of the program is to develop evaluation methodologies of hypotheses in a model-based framework. In this paper, we describe an hypothesis evaluation strategy that is predicated on a generalized likelihood function framework, and allows for incomplete or inaccurate descriptions of the observed unknown target. The target hypothesis evaluation procedure we have developed begins with a structural analysis by means of parametric modeling of the several radar scattering centers. The energy, location, dispersion, and shape of all measured target scattering centers are parametrized. The resulting structural description is used to represent each target and, subsequently, to evaluate the hypotheses of each of the targets in the candidate set.
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