Multiresolution Subspace-Based Optimization Method for the Retrieval of 2-D Perfect Electric Conductors

Xiuzhu Ye; Francesco Zardi; Marco Salucci; Andrea Massa

doi:10.1109/TMTT.2022.3220252

Multiresolution Subspace-Based Optimization Method for the Retrieval of 2-D Perfect Electric Conductors

Xiuzhu Ye, Francesco Zardi, Marco Salucci, Andrea Massa^*

^*Corresponding author for this work

School of Information and Electronics

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

Perfect electric conductors (PECs) are reconstructed integrating the subspace-based optimization method (SOM) within the iterative multiscaling approach (IMSA). Without a priori information on the number or/and the locations of the scatterers and modeling their electromagnetic (EM) scattering interactions with a (known) probing source in terms of surface electric field integral equations, a segment-based representation of PECs is retrieved from the scattered field samples. The proposed IMSA-SOM inversion method is validated against both synthetic and experimental data by assessing the reconstruction accuracy, the robustness to the noise, and the computational efficiency with some comparisons, as well.

Original language	English
Pages (from-to)	1732-1744
Number of pages	13
Journal	IEEE Transactions on Microwave Theory and Techniques
Volume	71
Issue number	4
DOIs	https://doi.org/10.1109/TMTT.2022.3220252
Publication status	Published - 1 Apr 2023

Keywords

Inverse problems
inverse scattering
iterative multiscaling approach (IMSA)
metallic scatterers
microwave imaging
multiresolution
perfect electric conductor (PEC)
subspace-based optimization method (SOM)

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10.1109/TMTT.2022.3220252

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title = "Multiresolution Subspace-Based Optimization Method for the Retrieval of 2-D Perfect Electric Conductors",

abstract = "Perfect electric conductors (PECs) are reconstructed integrating the subspace-based optimization method (SOM) within the iterative multiscaling approach (IMSA). Without a priori information on the number or/and the locations of the scatterers and modeling their electromagnetic (EM) scattering interactions with a (known) probing source in terms of surface electric field integral equations, a segment-based representation of PECs is retrieved from the scattered field samples. The proposed IMSA-SOM inversion method is validated against both synthetic and experimental data by assessing the reconstruction accuracy, the robustness to the noise, and the computational efficiency with some comparisons, as well.",

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AU - Ye, Xiuzhu

AU - Zardi, Francesco

AU - Salucci, Marco

AU - Massa, Andrea

PY - 2023/4/1

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AB - Perfect electric conductors (PECs) are reconstructed integrating the subspace-based optimization method (SOM) within the iterative multiscaling approach (IMSA). Without a priori information on the number or/and the locations of the scatterers and modeling their electromagnetic (EM) scattering interactions with a (known) probing source in terms of surface electric field integral equations, a segment-based representation of PECs is retrieved from the scattered field samples. The proposed IMSA-SOM inversion method is validated against both synthetic and experimental data by assessing the reconstruction accuracy, the robustness to the noise, and the computational efficiency with some comparisons, as well.

KW - Inverse problems

KW - inverse scattering

KW - iterative multiscaling approach (IMSA)

KW - metallic scatterers

KW - microwave imaging

KW - multiresolution

KW - perfect electric conductor (PEC)

KW - subspace-based optimization method (SOM)

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Multiresolution Subspace-Based Optimization Method for the Retrieval of 2-D Perfect Electric Conductors

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Keywords

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