1. 阜阳师范学院物理与电子工程学院,安徽,阜阳,236037
2. 阜阳师范学院数学与统计学院,安徽,阜阳,236037
3. 阜阳师范学院物理与电子工程学院,安徽,阜阳,236037
4. 阜阳师范学院数学与统计学院,安徽,阜阳,236037
纸质出版:2015
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刘广东, 葛新同. 多极德拜色散媒质的时域电磁逆散射改进技术[J]. 电子学报, 2015,43(12):2518-2524.
LIU Guang-dong, GE Xin-tong. An Improved Time-Domain Electromagnetic Inverse Scattering Technique for Multi-Pole Debye Dispersive Media[J]. Acta Electronica Sinica, 2015, 43(12): 2518-2524.
刘广东, 葛新同. 多极德拜色散媒质的时域电磁逆散射改进技术[J]. 电子学报, 2015,43(12):2518-2524. DOI: 10.3969/j.issn.0372-2112.2015.12.026.
LIU Guang-dong, GE Xin-tong. An Improved Time-Domain Electromagnetic Inverse Scattering Technique for Multi-Pole Debye Dispersive Media[J]. Acta Electronica Sinica, 2015, 43(12): 2518-2524. DOI: 10.3969/j.issn.0372-2112.2015.12.026.
在已有的经验模型中
多极德拜(Debye)模型最适合高精地描述生物组织、土壤、水等媒质的色散特性.为了同时反演这类媒质的电磁参数
本文提出了一种时域逆散射改进技术:分别应用迭代法和吉洪诺夫(Tikhonov)正则化技术克服逆问题的非线性和病态性困难;解析导出了目标泛函关于目标参数的梯度;迭代重建过程中
产生的正演、反演子问题分别选用时域有限差分(FDTD)法、共轭梯度(CG)法求解.噪声环境下
通过两个一维(1-D)的数值算例
初步证实了该技术的可行性和鲁棒性.
The Debye model with multiple relaxation times is most suitable for highly accurate description of the dispersion characteristics of many media
such as biological tissues
soil
and water
among the developed empirical models.In order to reconstruct the electromagnetic properties of these dispersive media simultaneously
a modified time-domain inverse scattering technique is presented.Firstly
in the proposed technology
the nonlinearity and ill-posedness of the inverse problem is circumvented by an iterative method and the Tikhonov's regularization
respectively.Secondly
a set of closed gradients (Frchet derivatives) of its cost functional with respect to objective parameters are derived for the aforementioned inverse problem.Then
the finite-difference time-domain (FDTD) method and any conjugate gradient (CG) method is applied
at its each iteration
to solve the resulting forward and backward sub-problem
respectively.Lastly
the feasibility and robustness for the inversion technique are preliminarily confirmed by two one-dimensional (1-D) numerical examples where a model of the additive white Gaussian noise (AWGN) is considered.
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