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Buried object adaptive shape reconstruction and ground parameters estimation using differential evolution

机译:利用差分进化的掩埋物体自适应形状重构和地面参数估计

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摘要

In this study, the capability of the opposition-based differential evolution stochastic searching algorithm in shape reconstruction of a two-dimensional conducting target buried in a lossy dielectric half-space is investigated using simulated backscattered fields calculated above the ground by both method of moment with far-field approximation and geometrical optics approximation at different observation and frequency points. For an efficient reconstruction, the target boundary is approximated by a non-uniform cubic B-spline curve with variable number of curve control parameters (CP). Using the knot insertion Oslo algorithm and through the optimisation process, the DE algorithm finds the optimum number of CP, successfully reconstructs the ground parameters (i.e. permittivity and conductivity) together with target upper part shape and location for moderate values of the signal-to-noise power ratio.
机译:在这项研究中,使用基于矩的两种方法在地面上计算的模拟反向散射场,研究了基于对立的差分演化随机搜索算法在掩埋在有损介电半空间中的二维导电目标的形状重构中的能力。在不同观察点和频率点的远场近似和几何光学近似。为了进行有效的重建,目标边界由具有可变数量的曲线控制参数(CP)的不均匀三次B样条曲线近似。使用结插入奥斯陆(Oslo)算法并通过优化过程,DE算法找到了最佳CP数,成功地重建了地面参数(即介电常数和电导率)以及目标上部形状和位置,以得到适中的信噪比值。噪声功率比。

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