Multifrequency microwave tomography in Lebesgue spaces with nonconstant exponents

This article proposes an inversionmethod for microwave tomography that combines a multifrequency data processing with a nonlinear regularization procedure formulated in Lebesgue spaces with nonconstant exponents. In order to fully take advantage of frequency diversity, scattered-field data measured at different frequencies are jointly processed inside the inversion algorithm. The performance of the proposed method versus the range of the Lebesgue-space exponent function is assessed from an experimental viewpoint by considering both homogeneous and inhomogeneous targets from the well-known Fresnel data sets.