本論文是研究在水面上導電目標物之電磁成像。其目的是在空氣上半空間中搜集散射電場來重建水面上目標物之形狀。基於水面的散射效應必須在散射電場積分時考慮半空間的格林函數。本研究所有的散射電場都是藉由動差法來做數值計算。在電磁成像中，目標物的形狀是以傅立葉級數表示，故藉由計算傅立葉級數之係數，即可得到目標物之形狀。在上半空間中以不同入射方向的平面波照射目標物，對於每一入射方向，以等角、等距的位置來搜集散射電場，這些位置真正的散射電場可以通過實際測量或理論計算來得到。初始猜測目標物形狀的傅立葉級數之係數，接著由人工蜂群演算法來更新係數，即逼近目標物之形狀函數。對於每一次迭代所得到的傅立葉級數之係數，即暫時猜測的目標物之形狀函數，且其在相同的量測位置計算散射電場，並將計算出的散射電場與真正的散射電場進行比較，直到散射電場的相對誤差低於預設值，此時，目標物的形狀函數確定，換句話說，目標物的形狀被成功重建，即實現電磁成像技術。數值模擬結果顯示出，該電磁成像技術可以成功重建於淡水和海水表面上的目標物之形狀。人工蜂群演算法本質上是一種進化的優化演算法，它不需要任何梯度運算，使得它可以實現複雜的優化系統甚至是黑盒子系統。該研究可應用於船艦探測水面上目標物。

In this thesis, the electromagnetic imaging of a conducting target on water surface is given. The goal is to reconstruct the shape of a conducting target on water surface by collecting scattered electric fields in the upper half space of air. The scattering effect due to water is considered by using the half-space Green’s function in integrals of scattered electric fields. All scattered electric fields of this study are numerically calculated by the Moment Method. In electromagnetic imaging, the target’s shape is represented by a Fourier series and the goal becomes to determine the Fourier series coefficients. The target is illuminated by plane waves from different incident directions in the upper half space. For each incident direction, the scattered electric fields are collected in several equiangular and equidistant locations in the upper half space. The true scattered electric fields at these locations can be obtained by practical measurement or theoretical calculation. Values for Fourier series coefficients of the target’s shape are initially guessed, and are then updated by the Artificial Bee Colony algorithm. For each set of temporary values for Fourier series coefficients, i.e., temporarily guessed shape for the target, scatted electric fields at the same measurement locations are calculated. These calculated electric fields are then compared with the true scattered electric fields. Update for values of Fourier series coefficients will continue until the relative error of scattered fields is below a threshold. Thus the Fourier series of the target’s shape function is determined. In other words, the target’s shape is successfully reconstructed and the electromagnetic imaging is achieved. Numerical simulation results show that the proposed electromagnetic imaging algorithm can successfully reconstruct the shape of a target on both fresh and sea water surface. The Artificial Bee Colony algorithm is inherently an evolutionary optimization algorithm. It does not require any gradient operation so that it can achieve optimization of complicated or even black-box systems. This study can be applied to naval target detection on water surface.

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