Unexploded ordnance (UXO) cleanup is the number one priority Army installation remediation restoration requirement. The problem is enormous in scope, with millions of acres and hundreds of sites potentially contaminated. Before the UXO can be recovered and destroyed, it must be located. UXO location requires surface geopbysical surveys. The geophysical anomalies caused by the UXO must be detected, discriminated from geophysical anomalies caused by other sources, and ideally identified or classified. Recent UXO technology demonstrations, live site demonstrations, and practical UXO surveys for site cleanup confirm that most UXO anomalies can be detected (with probabilities of detection of 90 percent or better), however there is little evidence of discrimination capability (i.e., the false alarm rates are high), and there is no identification capability. Approaches to simultaneously increase probability of detection and decrease false alarm rate and ultimately to give identification/classification capability involve rational multisensor data integration for discrimination and advanced development of new and emerging technology for enhanced discrimination and identification. The goal of multisensor data integration is to achieve true joint inversion of data to a best-fitting model using realistic physics-based models that replicate UXO geometries and physical properties of the UXO and surrounding geologic materials. Data management, analysis, and display procedures for multisensor data are investigated. A magnetic modeling capability is developed, validated, and documented that uses a prolate spheroid model of UXO. The electromagnetic modeling of UXO signatures is more problematic, and an intermediate quasi-empirical modeling capability (a simple analytical model modified to reflect measured signature observations) is explored.

Unexploded ordnance (UXO) cleanup is the number one priority Army installation remediation/restoration requirement The problem is enormous in scope, with millions of acres and hundreds of sites potentially contaminated. Before the UXO can be recovered and destroyed, it must be located. UXO location requires surface geophysical surveys. The geophysical anomalies caused by the UXO must be detected, discriminated from geophysical anomalies caused by other sources, and ideally identified or classified. Recent UXO technology demonstrations, live site demonstrations, and practical UXO surveys for site cleanup confirm that most UXO anomalies can be detected (with probabilities of detection of 90 percent or better), however there is little evidence of discrimination capability (i.e., the false alarm rates are high), and there is no identification capability. Approaches to simultaneously increase probability of detection and decrease false alarm rate and ultimately to give identification/classification capability involve rational multisensor data integration for discrimination and advanced development of new and emerging technology for enhanced discrimination and identification. The goal of multisensor data integration is to achieve true joint inversion of data to a best-fitting model using realistic physics-based models that replicate UXO geometries and physical properties of the UXO and surrounding geologic materials. Data management, analysis, and display procedures for multisensor data are investigated. The role of empirical, quasi-empirical, and analytical modeling for UXO geophysical signature prediction are reviewed and contrasted with approaches that require large signature databases (e.g., expert systems, neural nets, signature database comparison) for training or best-fit comparison. A magnetic modeling capability is developed, validated, and documented that uses a prolate spheroid model of UXO.

US Defense Department estimates indicate that as many as 11 million acres of government land in the U.S. may contain unexploded ordnance (UXO), with the cost of identifying and disposing of this material estimated at nearly $500 billion. The size and character of the ordnance, types of interference, vegetation, geology, and topography vary from site to site. Because of size or composition, some ordnance is difficult to detect with any geophysical method, even under favorable soil and cultural interference conditions. For some sites, airborne methods may provide the most time and cost effective means for detection of UXO. Airborne methods offer lower risk to field crews from proximity to unstable ordnance, and less disturbance of sites that maybe environmentally sensitive. Data were acquired over a test site at Edwards AFB, CA using airborne magnetic, electromagnetic, multispectral and thermal sensors. Survey areas included sites where trenches might occur, and a test site in which we placed deactivated ordnance, ranging in size from small ''bomblets'' to large bombs. Magnetic data were then acquired with the Aerodat HM-3 system, which consists of three cesium magnetometers within booms extending to the front and sides of the helicopter, and mounted such that the helicopter can be flown within 3m of the surface. Electromagnetic data were acquired with an Aerodat 5 frequency coplanar induction system deployed as a sling load from a helicopter, with a sensor altitude of 15m. Surface data, acquired at selected sites, provide a comparison with airborne data. Multispectral and thermal data were acquired with a Daedelus AADS 1268 system. Preliminary analysis of the test data demonstrate the value of airborne systems for UXO detection and provide insight into improvements that might make the systems even more effective.

Most military and commercial detectors sense the presence of metal casings or components of buried mines or explosive ordnance; however, this traditional approach to mine and unexploded ordnance (UXO) detection is prone to high false alarm rates. Explosive components, common to all mines and ordnance devices, offer a unique discriminator among buried objects. Two approaches to detect buried explosive devices directly are investigated: chemical trace detection, which relies on detecting either the vapor emanating from buried devices or the small explosive particles [and/or their explosive-related compounds (ERCs)] concentrated in the top soil, and radiation techniques, which uses radiation to probe beneath the earth's surface to provide bulk detection of buried explosive devices. This report describes the technology approaches and the current performance of each approach and discusses some promising new explosive detection technologies. It suggests that the Joint Unexploded Ordnance Coordination Office (JUXOCO) take a leadership role in establishing standards and protocols for reporting the results of field measurements in which trace analyses are used for detection of buried mines and ordnance and in sponsoring the development and maintenance of an open-sourced code to predict the variability of explosive detection in different environments.