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An Imaging Method Based on Sparse Constrained Nonlinear Electromagnetic Field Inverse Scattering

机译:基于稀疏约束非线性电磁场逆散射的成像方法

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This paper proposes a nonlinear electromagnetic field inverse scattering imaging method under sparse domain, and applies this method to the spatial distribution information of electrical performance parameters for reconstructing multi-media targets. Since the dimension of the measured scattering field is usually much smaller than the dimension of the unknown parameter, this makes the electromagnetic field integral equation ill-conditioned, and the solution of the equation can be obtained using sparse constraint regularization. For this reason, this paper proposes a nonlinear algorithm in sparse domain, which is named as SP-CS algorithm (Sparse Constraints-Contrast Source). The solution of the scattered field equations of the algorithm can be computed by an inexact Newton method.
机译:提出了一种稀疏域下的非线性电磁场逆散射成像方法,并将其应用于电气性能参数的空间分布信息,以重构多媒体目标。由于测量的散射场的维数通常比未知参数的维数小得多,因此这会使电磁场积分方程变得不适,并且可以使用稀疏约束正则化来获得方程的解。为此,本文提出了一种稀疏域中的非线性算法,称为SP-CS算法(稀疏约束-对比度源)。该算法的散射场方程的解可以通过不精确的牛顿法来计算。

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