High speed imaging of antipersonnel land mines by the convexification algorithm for a simplified mathematical model in two dimensions
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Abstract
We address the efficiency issue for the globally convergent convexification algorithm for coefficient inverse problems. By properly choosing the upper limit for pseudo-frequency and with quadratic polynomial approximations of the quantities which depend on the pseudo-frequency, we show that the algorithm can be made dramatically faster relative to the previous “tail-free” implementation. Numerical results from imaging and the mathematical modeling of antipersonnel land mines demonstrate that the algorithm can detect the location(s) of the inclusion(s) from the background medium, as well as correctly identify the material property of the inclusion(s) and the background. This indicates that the convexification algorithm may be applied in real-time to detect and image mine-like targets in the field.
© de Gruyter 2009
Articles in the same Issue
- Estimation in time-delay modeling of insecticide-induced mortality
- Inverse scattering problem for the wave equation with locally perturbed centrifugal potential
- Two regularization methods for an axisymmetric inverse heat conduction problem
- A second order Newton method for sound soft inverse obstacle scattering
- High speed imaging of antipersonnel land mines by the convexification algorithm for a simplified mathematical model in two dimensions
Articles in the same Issue
- Estimation in time-delay modeling of insecticide-induced mortality
- Inverse scattering problem for the wave equation with locally perturbed centrifugal potential
- Two regularization methods for an axisymmetric inverse heat conduction problem
- A second order Newton method for sound soft inverse obstacle scattering
- High speed imaging of antipersonnel land mines by the convexification algorithm for a simplified mathematical model in two dimensions
