Testing of discrimination technology has been primarily limited to test sites, with little application at live sites. For discrimination technologies to be validated they must be demonstrated at real sites with unexploded ordnance (UXO) and real world conditions. ESTCP has invested in munitions response demonstration and validation efforts to understand the applicability and limitations of these pilot technologies at live sites under the Live Site Program. ESTCP has also assembled an Advisory Group to address the regulatory, programmatic, and stakeholder acceptance issues associated with the implementation of discrimination in the munitions response process. The continued involvement of regulators within the demonstration process aids technology development and relevance for decision makers.

The two primary demonstration objectives of this study were to (1) determine the discrimination capabilities of the Berkely UXO Discriminator (BUD) at San Luis Obispo (SLO), California, and (2) investigate, in cooperation with regulators and program managers, how discrimination technologies can be implemented in cleanup operations.

Technology Description

BUD not only detects an object but also quantitatively determines its size, shape, and orientation. BUD performs target characterization from a single position of the sensor platform above a target. BUD was designed to detect UXO in the 20 mm to 155 mm size range for depths between 0 and 1.5 m, and to characterize them in a depth range from 0 to 1.1 m. The system incorporates three orthogonal transmitters and eight pairs of differenced receivers. The transmitter-receiver assembly together with the acquisition box, as well as the battery power and global positioning system (GPS) receiver, is mounted on a small cart to assure system mobility. System positioning is provided by the state-of-the-art Real Time Kinematic (RTK) GPS receiver. The survey data acquired by BUD are processed by software developed by LBNL, which is efficient and simple, and can be operated by relatively untrained personnel. Data acquisition was performed on a single board, with transmitter coils powered separately from the data acquisition board. The detection performance of the system is governed by an object’s size-depth relationship. It is assumed that BUD’s lower receiver plan is 0.2 m above the ground, which infers that the system can detect and discriminate objects from 0.9 m to 1.3 m with a depth uncertainty of 10%. And objects buried at more than 0.9 m will have a low probability of discrimination, and any objects below 1.3 m will have a low probability of detection.

Demonstration Results

The BUD cued discrimination survey at SLO took place over 13 working days between June 22, 2009, and July 9, 2009. The ground truth data at SLO contained 50 targets of interest (TOI) and 412 pieces of scrap.  It was found that the use of one-dipole or two-dipole polarizability inversion results on a target-by-target basis greatly determined the ability for BUD to discriminate a TOI; 95% of all TOI were correctly identified with only two false positives. The template match approach showed that more than 50% of the total number of digs could be avoided while correctly identifying all TOI.

Implementation Issues

BUD not only detects but also discriminates UXO from non-UXO/scrap and gives its characteristics (location, size, polarizability, aspect ratio) from a single position of the sensor platform above the object. BUD was designed to detect and discriminate UXO in the 20 mm to 155 mm size range buried anywhere from 0 to 1.5 m depth and from 0 to1.1 m, respectively. Any objects buried at a depth more than 1.5 m will have a low probability of detection, and any objects buried at a depth more than 1.1 m will have a low probability of discrimination. With the existing algorithms in the system computer at the time, it was not possible to recover the principal polarizabilities of large objects close to the system. Detection of large shallow objects was assured, but at that time discrimination was not. Post processing of the field data was required for shape discrimination of large shallow targets.