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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Preprocessing the Reciprocity Gap Sampling Method in Buried-Object Imaging Experiments
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Preprocessing the Reciprocity Gap Sampling Method in Buried-Object Imaging Experiments

机译：掩埋物成像实验中的互惠差距采样方法的预处理

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摘要

A reciprocity gap linear sampling method (RG-LSM) coupled with an analytic continuation method is proposed to localize and retrieve the shape of objects buried under a rough surface from multistatic data at a fixed frequency. The obtained procedure makes feasible the application of the RG-LSM algorithm to imaging experiments where the data are collected in the upper domain. It does not require the computation of the Green's function of the background layered medium and also does not require any a priori knowledge on the number or the physical properties of the buried scatterers. The efficiency and robustness of the method are validated through various numerical experiments for single and multiconnected objects.
机译：提出了一种倒数差距线性采样方法（RG-LSM）结合解析连续方法，以固定频率从多静态数据中定位和获取埋在粗糙表面下的物体的形状。所获得的过程使得RG-LSM算法在成像实验中的应用成为可能，在成像实验中在较高域中收集数据。它不需要计算背景分层介质的格林函数，也不需要有关掩埋散射体的数量或物理特性的任何先验知识。通过对单个和多个连接对象的各种数值实验，验证了该方法的效率和鲁棒性。

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