Interpretation and Analysis of Target Scattering From Fully-Polarized ISAR Images Using Pauli Decomposition Scheme for Target Recognition

An assessment of polarimetric inverse synthetic aperture radar (Pol-ISAR) imaging is accomplished for realistic target models with the use of our recently developed high-frequency radar cross-section simulator tool called PREDICS. X-band, narrow-angle and full-polarimetric ISAR data for the CAD models of the well-known test object SLICY and a ground vehicle, namely a backhoe loader are analyzed to infer their structural characteristics. Experimental data obtained from a tower-turntable ISAR measurements of a T-72 tank target have also been utilized to assess the validity of the simulator. First, the intensity images in linear and circular polarization bases are directly utilized to evaluate the data quality and to characterize target features for classification. Then, the Pauli image decomposition scheme is applied to separate the basic scattering mechanisms occurring at target pixels. The identifiable canonical target forms are successfully extracted as single, double and multi-bounce scattering mechanisms that are pinpointed at their true locations. The results indicate that PREDICS is able to generate high-fidelity synthetic Pol-ISAR signatures of complex targets whereby successful interpretation of innumerous target scattering mechanisms and features can be achieved through Pauli decomposition scheme for classification purposes.