Coherence Factor-Based Polarimetric Diffraction Tomography for 3-D Inverse Scattering With a Sparse Planar Array

A sparse planar array often suffers from the strong grating-lobes that deteriorate inversion performance due to spatial undersampling. In this article, a diffraction tomography (DT) algorithm is proposed to solve 3-D electromagnetic inverse scattering problems (EISPs) with a sparse planar array and polarization diversity. The method deals with multifrequency multipolarization data as follows: first, doing a polarization fusion; next, using the exact coordinate transformation; then decoupling and modifying the aliased multifrequency spatial spectrum of the permittivity and the conductivity; finally, applying the range-normalization 2-D coherence factor (2-D CF) weighting. The weak scatterers’ geometries and dielectric properties can be well reconstructed under low-contrast conditions, and the non-weak scatterers can also be detected. The proposed method outperforms the conventional DT approach regarding grating-lobes and noise suppression without compromising quantitative inversion performance, as demonstrated by the inverted results obtained from synthetic and experimental data.