A quasi-Newton reconstruction algorithm for a complex microwave imaging scanner environment

An iterative complex permittivity reconstruction technique for two-dimensional near-field imaging is presented. A particular feature of the algorithm is that it takes into account the complicated environment of a circular 434 MHz microwave imaging scanner, which was developed to conduct biomedical imaging experiments. This is accomplished in a computationally efficient way by means of an embedding technique. The reconstruction technique is further based on a quasi-Newton optimization scheme with approximate line search, in which the Hessian matrix is iteratively updated with the Broyden–Fletcher–Goldfarb–Shanno (BFGS) formula. This way, second derivative information is exploited to a large extent. The technique is illustrated with complex permittivity reconstructions of homogeneous and inhomogeneous lossy dielectric cylinders of moderate and high contrast from simulated data