Single step microwave imaging in the time domain using FDTD-based gradient minimization

Abstract

This paper deals with single step microwave imaging for reconstructing the dielectical properties of the unknown targets in 2D. The image reconstruction algorithm is based on the gradient minimization of an augmented cost function defined as the different between measured and calculated fields. The algorithm requires two successive steps for convergent: the direct and the adjoint solutions. The forward-backward time stepping algorithm, implementing the finite-difference time-domain (FDTD) method with PML absorbing boundaries was used in the calculation. Image reconstruction was based on Born approximation in which the solution was obtained after the first iteration. Multiple view simulated data was used to validate the accuracy of this inversion method. Results indicate that this technique can accurately detect and locate unknown targets with different contrast ratios.