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Distorted Born iterative method with back-propagation improves permittivity reconstruction

Published online by Cambridge University Press:  28 April 2022

Amit Magdum Open the ORCID record for Amit Magdum [Opens in a new window]  and
Mallikarjun Erramshetty
Amit Magdum*
Affiliation:
Department of Electronics and Communication Engineering, National Institute of Technology Goa, Ponda, India
Mallikarjun Erramshetty
Affiliation:
Department of Electronics and Communication Engineering, National Institute of Technology Goa, Ponda, India
*
Author for correspondence: Amit Magdum, E-mail: amitmagdum7671@gmail.com
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Abstract

The distorted Born iterative method (DBIM) is a widely used quantitative reconstruction algorithm to solve the inverse scattering problems of microwave imaging. The major mathematical challenges in solving such problems are non-uniqueness, non-linearity, and ill-posedness. Due to these issues, the optimization algorithm converges to a local minimum. This drawback can be overcome by selecting the correct initial guess solution, which helps to escape local minima and thus guides the inversion algorithm to a satisfactory result. This study uses a back-propagation algorithm to calculate the initial estimate, which significantly accelerates the rate of convergence and improves the accuracy of the standard DBIM approach. The results of this method are compared with zero initialization and Born-approximated initialization. For comparison, weak as well as strong scattering profiles of synthetic and experimental dataset are considered. The results suggest that the proposed method provides a significant improvement in terms of computing cost and efficiency. Furthermore, the proposed technique has the potential to successfully push the limits of reconstructible contrast.

Keywords

Back-propagationBorn approximationdistorted Born iterative methodinitial guess solutionmicrowave imaging
Type
EM Field Theory
Information
International Journal of Microwave and Wireless Technologies , Volume 15 , Issue 2 , March 2023 , pp. 331 - 337
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press in association with the European Microwave Association

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