Sensing Dielectric Scatterers by Means of The Born Iterative Method in the Contrast-Field Bayesian Compressive Sensing Framework

M. Salucci, G. Oliveri, A. Massa
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Abstract

A novel method based on the contrast field formulation for imaging sparse scatterers is proposed in this paper. The inversion of the scattering data is achieved by means of a Bayesian Compressive Sensing $(BCS)$-based methodology developed within an iterative procedure where the non-linear problem is recast as a sequence of linear problems solved through a Relevance Vector Machine (RVM). Selected numerical examples are illustrated in order to evaluate the effectiveness of the presented approach, also in a comparative fashion with a state-of-the-art $(SoA)BCS$-based method based on the first order Born approximation,
基于对比场贝叶斯压缩感知框架的Born迭代法检测介质散射体
提出了一种基于对比度场公式的稀疏散射体成像新方法。散射数据的反演是通过基于贝叶斯压缩感知$(BCS)$的方法实现的,该方法是在迭代过程中开发的,其中非线性问题被重新映射为通过相关向量机(RVM)解决的线性问题序列。为了评估所提出方法的有效性,还以一种基于一阶玻恩近似的最先进的基于SoA的BCS方法的比较方式说明了选定的数值示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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