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
- Microwave imaging
- Three dimensional model
- Gauss Newton method
- Algorithm
- Optimization
- Complex permittivity
- Electromagnetic wave scattering
- Harmonic
- Fast Fourier transformation
- Cost function
- Least squares method
- Non linear effect
- Non linear phenomenon
- Convergence rate
- Quasi Newton method
- Polarimetry
- Free space propagation
- Wave scattering
- Inverse problem
- Electromagnetic wave propagation
- Wireless telecommunication