Match hypothesis evaluation for synthetic aperture radar targets

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. Processing begins with a structural analysis using parametric modeling of radar scattering centers. The energy, location, dispersion and shape of all measured target scattering centers are parameterized. The resulting structural description is used to represent each target and is used to evaluate the hypotheses of the targets in the candidate set as indicated by an initial index inputs. The hypothesis evaluation process keys on the largest, most similar scatterers, with registration and proximity constraints. A probability estimate is computed for each hypothesis based on relative cross-section differences, target scattering center non-correspondences and model scattering center non-correspondences. The entire modeling and computation process is accomplished within Mathematica