Controlled mine detonation in Cambodia in 1995. Courtesy of the International Committee of the Red Cross and Paul Grabhorn.

El-Shenawee developed the three-dimensional model of dirt using a unique technique called the steepest descent fast multilevel multipole method, or SDFMM, an algorithm that analyzes how electromagnetic waves scatter as they bounce off rough surfaces. SDFMM is essentially a combination of mathematical equations that calculate the electric and magnetic currents on the surface of an object. Originally developed by Vikram Jandhyala, Eric Michielssen, and Weng Cho Chew at U of I's Center for Computational Electromagnetics, SDFMM was first used by El-Shenawee to study radar scattering on the ocean's surface.

Output of the landmine simulations. The left image shows the column of dirt without a buried mine. The center image shows the similar signature of a column of dirt that does contain a mine. And the final image shows the mine exposed after the data from the first image has been subtracted from the data in the second.

"When I came to Northeastern, we thought, 'This is perfect. Why don't we apply this technique to mine detection?'" she says. Working with Rappaport and signal processing specialist Eric Miller, El-Shenawee repurposed SDFMM to look beneath the soil's surface.

"All the previous working models were two-dimensional," she says. "There are three-dimensional models, but they're not fast enough. It would take days and days to get an answer." Using SDFMM, a simulation takes only hours. SDFMM runs a linear system of equations and considers a host of inputs important in creating the model all at once. These data include statistics that represent the behavior of electromagnetic scattered waves, receiver positions and angles, the boundary conditions of electric and magnetic fields, and interactions between the rough ground and smooth mine. Altering these inputs slightly and looking at the different outcomes will ultimately allow researchers to design the best system for detecting a mine.