Accession Number:

ADA379084

Title:

UWB SAR for Subsurface-Target Identification

Descriptive Note:

Final progress rept. 17 Aug 1998-16 Nov 1999

Corporate Author:

DUKE UNIV DURHAM NC

Personal Author(s):

• Carin, Lawrence

Report Date:

1999-12-23

Pagination or Media Count:

4.0

Abstract:

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 surfacesubsurface 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.

Descriptors:

• *TARGET RECOGNITION
• *SYNTHETIC APERTURE RADAR
• MATHEMATICAL MODELS
• ALGORITHMS
• SIGNAL PROCESSING
• SCATTERING
• ARMY RESEARCH
• DETECTION
• NUMERICAL ANALYSIS
• ELECTROMAGNETIC SCATTERING
• PROBLEM SOLVING
• SURFACES
• GROUND VEHICLES
• RADAR TARGETS
• DISCRIMINATION
• AUTOMATIC
• SUBSURFACE
• MARKOV PROCESSES
• FOLIAGE
• MULTIPOLARITY
• CONCEALMENT
• UNEXPLODED AMMUNITION
• GROUND PENETRATING RADAR

Subject Categories:

• Active and Passive Radar Detection and Equipment

Distribution Statement:

APPROVED FOR PUBLIC RELEASE