Electromagnetic Imaging for a Conducting Object Including Half-Space Effects of Water Surface

論文翻譯標題: 考慮水面半空間效應之金屬物體電磁成像之研究
  • 戴 翊軒

學生論文: Master's Thesis


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
獎項日期2016 八月 8
監督員Kun-Chou Lee (Supervisor)