Design and analysis of an Euler transformation algorithm applied to full-polarimetric ISAR imagery

Use of an Inverse Synthetic Aperture Radar (ISAR) enables the construction of spatial images of an object's electromagnetic backscattering properties. A set of fully polarimetric ISAR images contains sufficient information to construct the coherent scattering matrix for each resolution cell in the image. A diagonalization of the scattering matrix is equivalent to a transformation to a common basis, which allows the extraction of phenomenological parameters. These phenomenological scattering parameters, referred to as Euler parameters, better quantify the physical scattering properties of the object than the original polarization parameters. The accuracy and meaning of the Euler parameters are shown to be degraded by transform ambiguities as well as by azimuthal nonpersistence. The transform ambiguities are shown to be removed by a case-wise characterization and redefinition of the Euler parameters. The azimuthal nonpersistence is shown to be a result of multiple scattering centers occupying the same cell.; An optimized Euler transformation algorithm is presented that removes transform ambiguities and minimizes the impact of cells containing multiple scattering centers. The accuracy of the algorithm is analyzed by testing its effectiveness in Automatic Target Recognition (ATR) using polarimetric scattering signatures obtained at the University of Massachusetts Lowell Submillimeter-Wave Technology Laboratory and the U.S. Army National Ground Intelligence Center. Finally, a complete ATR algorithm is presented and analyzed which uses the optimized Euler transformation without any previous knowledge and without human intervention. The algorithm is shown to enable successful automatic target recognition.