Multi-Resolution subspace-Based optimization method for solving three-Dimensional inverse scattering problems

Xiuzhu Ye, Lorenzo Poli, Giacomo Oliveri, Yu Zhong, Krishna Agarwal, Andrea Massa, Xudong Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

An innovative methodology is proposed to solve quantitative three-dimensional microwave imaging problems formulated within the contrast source framework. The introduced technique is based on the combination of an efficient iterative multiscaling strategy aimed at mitigating local minimum issue arising in inverse scattering problems, and a local search algorithm based on the subspace-based optimization method (SOM) devoted to effectively retrieving both the "deterministic" and the "ambiguous" parts of the unknown contrast currents. To achieve this goal, a nested iteration process is adopted in which the outer loop iteratively refines the region of interest (ROI) where the scatterers are detected, while the inner loop retrieves the dielectric properties of the scatterers within the ROIs. Selected numerical examples are also given to show the validity and robustness of the proposed algorithm in comparison with state-of-the-art techniques.

Original languageEnglish
Pages (from-to)2218-2226
Number of pages9
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume32
Issue number11
DOIs
Publication statusPublished - 1 Nov 2015
Externally publishedYes

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