GPR UXO Classification Results for the Blossom Point Site: Demo #2
Abstract
An ultra-wide bandwidth, full-polarimetric ground penetrating radar (GPR) system operating from 10 MHz to 810 MHz has been applied to the classification of unexploded ordnance (UXO). Late-time radar signatures such as natural resonance and polarization were utilized to separate false alarm objects from UXO-like items with elongated bodies with length-to-diameter ratios greater than three. Additional features such as length, depth and orientation were also extracted from the data. Good classification performance was obtained from the previous Tyndall Test [1] for UXO-like items with inclination angles less than 45 degrees [2], where inclination is measured relative to the approximately horizontal ground surface. That particular test utilized only features extracted from a single radar position, approximately directly above the target. It was later found that this single-position approach contributed to many false alarms and the incapability of classifying UXO s with large inclination angles, such as vertical UXO s. Subsequently, new measurement approaches and additional radar features were developed to reduce the false alarm rate and missed-UXO s. A second field test ( Demo #2), conducted at the Blossom Point UXO Site [3,4], is the subject of this report. An improved system configuration and measurement approach was used to collect GPR data at multiple positions by moving the antenna along a straight line centered at the target spot. Other than 14 known targets, there were 78 blind target positions marked, where either UXO s or clutter items had been emplaced without the test team knowing the target identities. Multiple passes were performed along different orientations through each target position. The new approach provides spatial distributions of scattering response, including both early-time behavior as well as late-time UXO signatures.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2005
- Accession Number
- ADA606890
Entities
People
- Chi-chih Chen
- Kevin O’neill
- Matthew B. Higgins
Organizations
- Cold Regions Research and Engineering Laboratory