UWB SAR for Subsurface-Target Identification

摘要

This project has involved both numerical simulation of electromagnetic scattering for ultra-widenband synthetic aperture radar (SAR) for foliage and ground penetrating radar (FOPEN and GPEN, respectively). We have developed a fast multipole method (FMM) model for electromagnetic scattering from electrically large conducting targets in the presence of a half space, with application to scattering from surface/subsurface unexploded ordnance (UXO), as well as for scattering from surface vehicles, such as tanks. The FMM simulator is significantly faster than conventional method-of-moments (MoM) solvers. allowing solution of problems that were heretofore intractable. The code has been delivered to the Army Research Laboratory (ARL), and successfully compared with data measured by ARL. In addition to this modeling, we have developed hidden Markov model (HMM) automatic target recognition algorithms, applicable to the SAR detection and discrimination of concealed targets. Within the context of the HMM, we have employed a physics based matching pursuits feature parser. This signal processing paradigm has been successfully applied to ARL-measured FOPEN and GPEN data.