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

被引:7
|
作者
Ye, Xiuzhu [1 ]
Zardi, Francesco [2 ,3 ]
Salucci, Marco [2 ,3 ]
Massa, Andrea [2 ,4 ,5 ]
机构
[1] Beijing Inst Technol, Sch Informat & Elect, Beijing, Peoples R China
[2] ELEDIA Res Ctr, Dept Civil Environm & Mech Engn DICAM, I-38123 Trento, Italy
[3] CNIT Univ Trento, ELEDIA Res Unit, I-38123 Trento, Italy
[4] Univ Elect Sci & Technol China, ELEDIA Res Ctr, Sch Elect Sci & Engn, Chengdu 611731, Peoples R China
[5] ELEDIA Res Ctr, Beijing 100084, Peoples R China
基金
美国国家科学基金会;
关键词
Inverse problems; inverse scattering; iterative multiscaling approach (IMSA); metallic scatterers; microwave imaging; multiresolution; perfect electric conductor (PEC); subspace-based optimization method (SOM); ELECTROMAGNETIC INVERSE SCATTERING; CONCEALED OBJECT DETECTION; CUBIC-SPLINE EXPANSION; IMAGE-RECONSTRUCTION; SENSOR; ALGORITHM; EVOLUTION; CYLINDER; TARGETS; LOCATION;
D O I
10.1109/TMTT.2022.3220252
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:1732 / 1744
页数:13
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