Presenter Information

James H. Rose, Iowa State University

Location

La Jolla, CA

Start Date

1-1-1987 12:00 AM

Description

Inverse scattering theory concerns itself with determining the properties of a scatterer (e.g., the spatial variation of the scatterer’s dielectric constant and conductivity) from measured scattering data. Two general approaches to this problem exist. The first approach is a direct variational method. One starts by computing the scattering amplitude for some assumed properties of the scatterer. The resulting theoretical scattering amplitude is compared with the measured scattering data. If these results differ, then one varies the properties of the assumed scatterer and recomputes the scattered field for the new properties. This process is truncated when the measured and computed fields agree to a specified accuracy. The properties of the assumed scatterer are then supposed to coincide to within some accuracy with the unknown scatterer which generated the measured data.

Book Title

Review of Progress in Quantitative Nondestructive Evaluation

Volume

6A

Chapter

Chapter 2: Imaging, Microscopy, Inversion and Reconstruction

Section

Inversion and Reconstruction

Pages

595-599

DOI

10.1007/978-1-4613-1893-4_67

Language

en

File Format

application/pdf

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Jan 1st, 12:00 AM

Reconstruction of the Electromagnetic Wavefield from Scattering Data

La Jolla, CA

Inverse scattering theory concerns itself with determining the properties of a scatterer (e.g., the spatial variation of the scatterer’s dielectric constant and conductivity) from measured scattering data. Two general approaches to this problem exist. The first approach is a direct variational method. One starts by computing the scattering amplitude for some assumed properties of the scatterer. The resulting theoretical scattering amplitude is compared with the measured scattering data. If these results differ, then one varies the properties of the assumed scatterer and recomputes the scattered field for the new properties. This process is truncated when the measured and computed fields agree to a specified accuracy. The properties of the assumed scatterer are then supposed to coincide to within some accuracy with the unknown scatterer which generated the measured data.