利用边界条件约束增强导电目标线性采样成像

Matthew J. Burfeindt, H. Alqadah
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引用次数: 3

摘要

我们提出了一种新的线性采样方法(LSM),用于从空间稀疏数据采集中成像传导目标。该技术通过在未知目标边界上引入与电场边界条件相关的先验信息来缓解空间通道的缺乏。我们将所提出的技术应用于模拟数据,并证明了相对于标准LSM的图像保真度有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancement of Linear Sampling Method imaging of conducting targets using a boundary condition constraint
We present a new formulation of the Linear Sampling Method (LSM) for imaging conducting targets from spatially sparse data acquisitions. The technique mitigates the lack of spatial channels by introducing a priori information into the problem formulation related to the electric field boundary conditions on the unknown target boundary. We apply the proposed technique to simulated data and demonstrate improved image fidelity relative to the standard LSM.
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