Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors

• Main Author: Binajjaj, Saeed Ali Saeed
• Format: Thesis
• Language: English
• Published: 2010
• Subjects: TK1-9971 Electrical engineering. Electronics. Nuclear engineering
• Online Access: http://eprints.usm.my/43063/1/Saeed_Ali_Saeed_Binajjaj24.pdf; http://eprints.usm.my/43063/
• Institution: Universiti Sains Malaysia

This study investigates the time-domain inverse scattering of ultra wide band (UWB) tomography used in reconstructing the dielectric properties of the unknown targets in two dimensions. The image reconstruction algorithm was based on the gradient minimization of an augmented cost function defined as the difference between measured and calculated fields. Computation of the sensitivity function required two successive steps: (i) the forward (direct) propagation of the UWB wave-field, and (ii) the reverse (adjoint) propagation of the residual waves. The direct and adjoint fields were calculated using the finite-difference time-domain (FDTD) method, implementing the Mur‘s and the perfectly matched layer (PML) absorbing boundary conditions. The imaging algorithm was based on a non-linear optimization technique from which the single-step and iterative inversion schemes were realized. First, the algorithms‘ performances were evaluated using numerical simulation employing two different scanning geometries: limited and full view scanning geometries, where the applicability of these algorithms was accessed by comparing the reconstructed images with actual model. Second, the stability problem and the computational requirements were investigated using four experimental data collected by two different data acquisition systems. In experiments, organic objects with various properties were used to simulate cancerous-like dielectric profile, while the plastic pipe was employed for further performance and testing purposes. Finally, the algorithms‘ robustness against the noisy data was evaluated using two simulated experiments with signal-to-noise ratios of 6 and 8 dB respectively.