Sensitivity-Based Reconstruction in Microwave Imaging Using Near-Field Calibration Measurements

The sensitivity-based microwave imaging method requires the incident field distributions in the background medium, which insofar have been derived from analytical or simulation models. However, such models often prove inadequate in near-field imaging due to the complexity of the background and the acquisition setup. Here, we propose a calibration technique to efficiently acquire the necessary field information via measurements of a known calibration object containing a sufficiently small "point" scatterer. Only measurement data is needed to generate the images, i.e., the simulation or analytical incident-field model is replaced by a measurement-based model. The approach is validated through experiments with a planar raster scanning system. Two different tissue mimicking phantoms are imaged: i) dielectric cylinders embedded in a 5-cm thick layer of high-loss dielectric material and ii) tissue phantom containing porcine and bovine meat samples as well as grape inclusions.