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Time domain microwave imaging for a metallic cylinder by using evolutionary algorithms

机译:基于进化算法的金属圆柱体时域微波成像

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This paper presents the studies of time domain inverse scattering for a metallic cylinder based on the finite difference time domain (FDTD) method and the evolutionary algorithms (EAs). For the forward scattering, the FDTD method is employed to calculate the scattered E fields. Base on the scattering fields, these inverse scattering problems are transformed into optimisation problem. The idea is to perform the image reconstruction by utilisation of some optimisation schemes to minimise the discrepancy between the measured and calculated scattered field data. They are the asynchronous particle swarm optimisation (APSO), dynamic differential evolution (DDE) and the non-uniform steady state genetic algorithm (NU-SSGA). The suitability and efficiency of applying the above methods for microwave imaging of a two-dimensional metallic cylinder arc examined. Numerical results show that good reconstruction can be obtained by all optimisation methods. However, the DDE outperform the NU-SSGA and APSO regarding the reconstruction accuracy and the convergent speed in terms of the number of the objective function calls. In addition, the effects of Gaussian noise on the reconstruction results are investigated.
机译:本文基于有限差分时域(FDTD)方法和进化算法(EAs),对金属圆柱体进行时域逆散射研究。对于前向散射,采用FDTD方法计算散射的E场。根据散射场,将这些反散射问题转化为优化问题。这个想法是通过利用一些优化方案来执行图像重建,以最小化测量和计算的散射场数据之间的差异。它们是异步粒子群优化(APSO),动态差分进化(DDE)和非均匀稳态遗传算法(NU-SSGA)。应用上述方法对二维金属圆柱弧进行微波成像的适用性和效率。数值结果表明,采用所有优化方法均能获得良好的重建效果。但是,就目标函数调用的数量而言,DDE在重构精度和收敛速度方面优于NU-SSGA和APSO。此外,研究了高斯噪声对重建结果的影响。

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