Regional estimation of the dielectric properties of inhomogeneous objects using near-field reflection data

Abstract

We present a new inversion strategy that integrates radar-based methods with microwave tomography (MT) to efficiently provide low resolution information about an object's structure and average dielectric properties. For this preliminary investigation, we assume that the object may be characterized as having three regions: a thin outer layer and an interior with two inhomogeneous regions having dissimilar average dielectric properties. Our aim is not to reconstruct a detailed image of an object, but rather to provide information about its basic structure, including the geometric and mean dielectric properties of regions predominantly composed of a given material. The inversion technique is carried out in two steps. First, a reconstruction model indicating the locations and spatial features of the three regions of interest is constructed efficiently and quickly using ultrawideband (UWB) reflection data. The reconstruction model formed using radar-based techniques is then incorporated into the second step of the procedure which estimates the mean dielectric properties over each region using MT methods. Identifying the three homogeneous regions with radar-based techniques provides a priori information about an object's internal geometry and significantly simplifies the parameter space structure so that the inverse scattering problem solved with MT is not as ill-posed as those typically encountered. The performance of the proposed technique is first evaluated with both reflection and transmission data generated by progressively more complex 2D numerical models. Microwave breast imaging approaches would benefit from the internal structural information extracted by the algorithm, so a practical application is explored using 2D breast models formed from the magnetic resonance (MR) scans of a patient study. The algorithm's ability to infer the breast's basic internal structure is demonstrated with these examples.