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.

The chapters in this volume were presented at the July–August 2008 NATO Advanced Study Institute on Unexploded Ordnance Detection and Mitigation. The conference was held at the beautiful Il Ciocco resort near Lucca, in the glorious Tuscany region of northern Italy. For the ninth time we gathered at this idyllic spot to explore and extend the reciprocity between mathematics and engineering. The dynamic interaction between world-renowned scientists from the usually disparate communities of pure mathematicians and applied scientists which occurred at our eight previous ASI’s continued at this meeting. The detection and neutralization of unexploded ordnance (UXO) has been of major concern for very many decades; at least since the First World war. UXO continues to be the subject of intensive research in many ?elds of science, incl- ing mathematics, signal processing (mainly radar and sonar) and chemistry. While today’s headlines emphasize the mayhem resulting from the placement of imp- vised explosive devices (IEDs), humanitarian landmine clearing continues to draw signi?cant global attention as well. In many countries of the world, landmines threaten the population and hinder reconstruction and fast, ef?cient utilization of large areas of the mined land in the aftermath of military con?icts.

Wars may officially end and treaties may be signed, but their lethal legacy lives on in the form of unexploded ordinance and minefields that continue to harm civilian populations. Aerial reconnaissance reduces the need for risky, costly and time-consuming ground operations, and the rapid development of unmanned aerial vehicles offers crucial innovations for addressing the aftermath of conflicts worldwide. Aleksandar Smiljanic, an international recognized subject matter expert in next generation defence technologies, examines current developments in technology, electronics, and unmanned autonomous systems that are increasingly allowing military experts to address the challenges of mine clearance and left-over munitions, thereby helping to neutralize the dangers posed by former battlefields. Focusing on the role that unmanned vehicle reconnaissance can play in future identification and clearance operations, the author's timely and critical account - richly illustrated and with a host of supporting scientific and mathematical evidence throughout - offers a fertile and thought-provoking array of solutions to a scourge that has affected civilian populations and civic infrastructure throughout the world for decades. This is a must-read for political and military policymakers and a vital contribution to global efforts at humanitarian relief when it comes to rebuilding the social, political, economic, and cultural landscape of affected populations, with effects not just on their own countries but consequences for us all.

Over the past 2 years, several accounts of the casualties caused by antipersonnel landmines have brought to light the threat such munitions pose years after hostilities cease. The deaths and injuries attributed to these mines each year have been estimated to total about 30,000. Many of the victims are civilians, including children. While the contamination of land caused by landmines and other forms of unexploded ordnance (UXO) may appear to be primarily a Third World issue, closer examination suggests that the problem is shared by developed nations as well. As you requested, we assessed the extent to which ongoing or foreseeable technology efforts offer solutions to worldwide landmine and other UXO problems.

Unexploded ordnance (UXO) pose a persistent and expensive problem throughout the world; over 11 million acres are potentially contaminated in the U.S. alone. However, detection requires a very high degree of reliability, the false alarm rate is typically enormous, and cleanup costs are very high. This Tutorial Text addresses the unique challenges of UXO detection and the following topics: fundamental physics and phenomenology; new, successful modeling and analysis methods; the design, development, and testing of new instruments that provide expanded and superior data; innovative processing techniques; and highly successful discrimination performance in blind field tests at standardized sites. The book is written for lay scientists and engineers, as well as specialists in the field, requiring only some familiarity with basic vector calculus and matrix methods, common statistical concepts, and elementary physics.

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.