In North America, artillery and bombing training sites are littered with unexploded ordnance (UXO) buried just below the surface. UXO from decades-old military campaigns is also widespread in Europe and Southeast Asia. To ensure the safety of civilian populations, governments worldwide are stepping up efforts to find and remove UXO.
Conventional metal detectors are typically unable to distinguish UXO from harmless shrapnel and other metallic debris. A large number of excavations—sometimes numbering in the thousands—is required to unearth all metal identified with these detectors.
To reduce excavation costs, researchers at Black Tusk Geophysics use MATLAB® to accurately classify buried UXO by processing data acquired from advanced electromagnetic induction sensors.
“At the core of our software are MATLAB algorithms that enable us to fit models to observed sensor data and compare the results with a library of known UXO,” says Laurens Beran, research geophysicist at Black Tusk Geophysics. “The user interface we developed in MATLAB enables us to visualize all the information we need to make accurate classifications and, in some cases, almost halve excavation costs.”