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首页> 外文期刊>Inverse Problems: An International Journal of Inverse Problems, Inverse Methods and Computerised Inversion of Data >Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium
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Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium

机译:基于子空间的非均匀背景介质逆散射问题的优化方法

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摘要

This paper proposes a version of the subspace-based optimization method to solve the inverse scattering problem with an inhomogeneous background medium where the known inhomogeneities are bounded in a finite domain. Although the background Green's function at each discrete point in the computational domain is not directly available in an inhomogeneous background scenario, the paper uses the finite element method to simultaneously obtain the Green's function at all discrete points. The essence of the subspace-based optimization method is that part of the contrast source is determined from the spectrum analysis without using any optimization, whereas the orthogonally complementary part is determined by solving a lower dimension optimization problem. This feature significantly speeds up the convergence of the algorithm and at the same time makes it robust against noise. Numerical simulations illustrate the efficacy of the proposed algorithm. The algorithm presented in this paper finds wide applications in nondestructive evaluation, such as through-wall imaging.
机译:本文提出了一种基于子空间的优化方法,用于解决背景不均匀的逆散射问题,其中已知的不均匀性以有限域为界。尽管在非均匀背景情况下无法直接使用计算域中每个离散点的背景格林函数,但本文还是使用有限元方法来同时获得所有离散点的格林函数。基于子空间的优化方法的本质是,对比度源的一部分是通过频谱分析确定的,而没有使用任何优化,而正交互补的部分则是通过解决低维优化问题来确定的。此功能显着加快了算法的收敛速度,同时使其对噪声具有鲁棒性。数值仿真表明了该算法的有效性。本文提出的算法在无损评估中具有广泛的应用,例如穿墙成像。

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