The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

A systematic approach to robust preconditioning for gradient based inverse scattering algorithms

Author

Summary, in English

This paper presents a systematic approach to robust preconditioning for gradient based non-linear inverse scattering algorithms. In particular, one- and two-dimensional inverse problems are considered where the permittivity and conductivity profiles are unknown and the input data consists of the scattered field over a certain bandwidth. A time-domain least-squares formulation is employed and the inversion algorithm is based on a conjugate gradient, or

quasi-Newton algorithm together with an FDTD-electromagnetic solver. A Fisher information analysis is used to estimate the Hessian of the error functional. A robust preconditioner is then obtained by incorporating a parameter scaling such that the scaled Fisher information has a unit diagonal. By improving the conditioning of the Hessian, the convergence rate of the conjugate gradient or quasi-Newton methods are improved. The preconditioner is robust

in the sense that the scaling, i.e., the diagonal Fisher information is virtually invariant to the numerical resolution and the discretization model that is employed. Numerical examples of image reconstruction are included to illustrate the efficiency of the proposed technique.

Publishing year

2008

Language

English

Publication/Series

Technical Report LUTEDX/(TEAT-7164)/1-23/(2008)

Document type

Report

Publisher

[Publisher information missing]

Topic

  • Electrical Engineering, Electronic Engineering, Information Engineering

Status

Published

Report number

TEAT-7164

Research group

  • Electromagnetic theory