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Image Reconstruction of Buried Multiple Conductors by Genetic Algorithms

机译:基于遗传算法的埋藏多导体图像重建

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This paper presents an inverse scattering problem for recovering the shapes of multiple conducting cylinders with the immersed targets in a half-space by genetic algorithm. Two separate perfectly conducting cylinders of unknown shapes are buried in one half-space and illuminated by transverse magnetic (TM) plane wave from the other half-space. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations are derived, and the electromagnetic imaging problem is reformulated into an optimization problem. The improved steady state genetic algorithm is used to find out the global extreme solution. Numerical results are given to demonstrate the performance of the inverse algorithm. Good reconstruction can be obtained even when the initial guesses are far different from the exact shapes, and then the multiple scattered fields between two conductors are serious. In addition, the effect of Gaussian noise on the reconstruction is investigated. We can find that the effect of noise is negligible for the normalized standard deviations below 0.01.
机译:本文提出了一种逆散射问题,通过遗传算法可以将目标浸没在半空间中的多个导电圆柱体的形状恢复。将两个未知形状的独立导电圆柱体埋在一个半空间中,并用来自另一半空间的横向(TM)平面波照明。根据边界条件和测得的散射场,导出一组非线性积分方程,并将电磁成像问题重新表述为优化问题。改进的稳态遗传算法用于求解全局极限解。数值结果表明了逆算法的性能。即使最初的猜测与实际形状相差甚远,然后两个导体之间的多个散射场也很严重,也可以获得良好的重构。另外,研究了高斯噪声对重建的影响。我们发现,对于低于0.01的归一化标准偏差,噪声的影响可以忽略不计。

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