.png){kind=icon}
返回
SUBSPACE-BASED OPTIMIZATION METHOD FOR RECONSTRUCTING PERFECTLY ELECTRIC CONDUCTORS
.png){kind=icon}
PRE
AI
DOI：10.2528/PIER09111606.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Reconstruction of perfectly electric conductors (PEC) with transverse magnetic (TM) illumination by a subspace-based optimization method (SOM) is presented. Apart from the information that the unknown object is PEC, no other prior information such as the number of the objects, the approximate locations or the centers is needed. The whole domain is discretized into segments of current lines. Scatterers of arbitrary number and arbitrary shapes are represented by a binary vector, and the descent method is used to solve the discrete optimization problem. Several numerical simulations are chosen to validate the proposed method. In particular, a combination of a line type object and a rectangular shape object is successfully reconstructed. The subspace-based optimization method for PEC scatterers is found to be more complex than its counterpart for dielectric scatterers.
Keyword:
GENETIC ALGORITHM
IMAGE-RECONSTRUCTION
INVERSE SCATTERING
OBJECTS
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
P
IF:
9.3
论文数:
2.9K
被引数:
2.7K
机构
引用论文
.png){kind=icon}
RECONSTRUCTION OF 2-DIMENSIONAL PERMITTIVITY DISTRIBUTION USING THE DISTORTED BORN ITERATIVE METHOD
PREAI
分享收藏 没有更多内容
没有更多内容