Full-Wave Three-Dimensional Microwave Imaging With a Regularized Gauss-Newton Method-- Theory and Experiment
Résumé
A reconstruction algorithm is detailed for three-dimensional full-vectorial microwave imaging based on Newton-type optimization. The goal is to reconstruct the three-dimensional complex permittivity of a scatterer in a homogeneous background from a number of time-harmonic scattered field measurements. The algorithm combines a modified Gauss-Newton optimization method with a computationally efficient forward solver, based on the fast Fourier transform method and the marching-on-in-source-position extrapolation procedure. A regularized cost function is proposed by applying a multiplicative-additive regularization to the least squares datafit. This approach mitigates the effect of measurement noise on the reconstruction and effectively deals with the non-linearity of the optimization problem. It is furthermore shown that the modified Gauss-Newton method converges much faster than the Broyden-Fletcher-Gold-farb-Shanno quasi-Newton method. Promising quantitative reconstructions from both simulated and experimental data are presented. The latter data are bi-static polarimetric free-space measurements provided by Institut Fresnel, Marseille, France.
Mots clés
Wireless telecommunication
Electromagnetic wave propagation
Inverse problem
Wave scattering
Free space propagation
Polarimetry
Quasi Newton method
Convergence rate
Non linear phenomenon
Non linear effect
Least squares method
Cost function
Fast Fourier transformation
Harmonic
Electromagnetic wave scattering
Complex permittivity
Optimization
Algorithm
Gauss Newton method
Microwave imaging
Three dimensional model