欠采样数据形状重建的组合方法

A. Dell’Aversano, G. Leone, R. Solimene
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引用次数: 0

摘要

采用了一种结合Migration-MUSIC的方法,从欠采样背散射场数据中重构由基本形状组成并嵌入在电大调查域中的强散射体的形状。散射体部署在金属平面上,模拟地面层,就像在SAR场景中一样。为了减轻混叠现象,采用干涉法对不相交可用频带获得的偏移图像进行组合。其次,由于每个基本形状都具有少量的参数特征,因此采用MUSIC算法分别对其进行重构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A combined approach for shape reconstruction from under-sampled data
A combined Migration-MUSIC approach is adopted to deal with the inverse problem of reconstructing the shape of strong scatterers composed of elementary shapes and embedded within an electrically large investigation domain from under-sampled backscattered field data. The scatterers are deployed over a metallic plane, which mimics the ground floor, as in SAR scenarios. In order to mitigate aliasing, migration images obtained by using disjoint available frequency bands are combined in an interferometric way. Next as each elementary shape is characterized by a small amount of parameters, a MUSIC algorithm is employed to reconstruct them separately.
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