基于稀疏约束的电磁场反问题散射成像方法研究

Siying Wu, Huilin Zhou
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引用次数: 0

摘要

由于被测散射场的维数通常远小于未知参数的维数,这使得电磁场积分方程是病态的,可以使用稀疏约束正则化方法得到方程的解。为此,本文引入了一种稀疏域下的非线性电磁场逆散射成像算法,即:稀疏约束子空间优化法(SP-SOM)算法,该算法用于重建多媒体目标电性能参数的空间分布信息。采用不精确牛顿法,可以采用SP-SOM算法对散射场方程进行重构。仿真结果表明,SP-SOM算法可以有效地重构电性能参数的空间分布信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Scatter Imaging Method for Electromagnetic Field Inverse Problem Based on Sparse Constraints
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 introduced a nonlinear electromagnetic field inverse scattering imaging algorithm under sparse domain, namely: sparse constraints subspace optimization method (SP-SOM) algorithm, the algorithm is used to reconstruct the spatial distribution information of electrical performance parameters of multi-media targets. To use the inexact Newton method, it can be handled that the scattered field equations is reconstructed using the SP-SOM algorithm. The simulation results show that SP-SOM algorithm can effectively reconstruct the spatial distribution information of electrical performance parameters.
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