MICROWAVE TOMOGRAPHY EMPLOYING AN ADJOINT NETWORK BASED SENSITIVITY MATRIX

A reconstruction algorithm for two- and three-dimensional microwave imaging is proposed. The present efiort is focused on the reconstruction of conductivity (æ) and permittivity ("r) distributions aiming at a technique serving medical imaging, while permeability imaging can be easily incorporated to serve geophysical geophysical prospecting as well. This work constitutes the most recent one within the efiort of extending our Modifled Perturbation Method (MPM) from static to high and now microwave frequencies. MPM is an approximate method based on an exact Sensitivity or Jacobian matrix for an iterative update of an initial (æ;"r) guess until convergence. This method is proved almost immune of the problem inherent ill- posedness, but its robustness is actually gained by paying a penalty of compromised accuracy in the flnal achieved image. However, this image can be flne tuned by formulating and solving an exact inverse problem. Regarding the involved Jacobian matrix, this is evaluated through closed form expressions obtained through an Adjoint Network Theorem in conjuction with the electromagnetics reciprocity theorem. The fleld distributions required for its evaluation are readily available from the always required forward problem solutions on the assumed (æ;"r) distributions. Herein, the flnite element method along with absorbing boundary conditions are employed for the forward problem electromagnetic simulation.