系統識別號 | U0002-1009202014483200 |
---|---|
DOI | 10.6846/TKU.2020.00258 |
論文名稱(中文) | 近場量測於非平坦表面之成像 |
論文名稱(英文) | Imaging of Rough Surfaces By Near Field Measurement |
第三語言論文名稱 | |
校院名稱 | 淡江大學 |
系所名稱(中文) | 電機工程學系碩士班 |
系所名稱(英文) | Department of Electrical and Computer Engineering |
外國學位學校名稱 | |
外國學位學院名稱 | |
外國學位研究所名稱 | |
學年度 | 108 |
學期 | 2 |
出版年 | 109 |
研究生(中文) | 詹舜傑 |
研究生(英文) | Shun-Jie Chan |
學號 | 607440202 |
學位類別 | 碩士 |
語言別 | 繁體中文 |
第二語言別 | |
口試日期 | 2020-07-16 |
論文頁數 | 49頁 |
口試委員 |
指導教授
-
丘建青(chiu@ee.tku.edu.tw)
委員 - 林丁丙(dblin@mail.ntust.edu.tw) 委員 - 方文賢(whf@mail.ntust.edu.tw) |
關鍵字(中) |
微波成像 近場量測 非平坦表面 自我適應之差異型演化法 |
關鍵字(英) |
Microwave Imaging Near Field Measurement Rough Surfaces Self-Adaptive Dynamic Differential Evolution (SADDE) |
第三語言關鍵字 | |
學科別分類 | |
中文摘要 |
微波成像是一種以微波作為訊號傳遞的成像方法,屬於電磁逆散射問題。其原理是用微波照射被測物體,然後通過物體外部散射場的測量值進行數學式的計算來獲得最終的目標-介電系數的分布。介電係數可以用來重建物體的形狀、材質等等。由於介電系數與生物組織的含水量密切相關,所以微波成像常用來作生物組織的成像。 本論文將對週期性非平坦表面的近場量測進行研究,比較近場與遠場的誤差,結果顯示近場的重建效果較遠場來的好。吾人利用已知邊界條件及量測到的散射場值,可以推導出一組積分方程式,再由散射場積分方程式算出電場,將逆散射問題轉換成最佳化問題,接著使用自我適應之動態差異型演化法(SADDE)重建出物體位置及介電系數分佈,並比較其對非均勻物體重建之蒐尋速度及穩定性。 利用自我適應之動態差異性演化法重建出週期性非平坦表面,不論一開始的猜測值如何,自我適應之動態差異性演化法總會收歛到整體的極值(global extreme),因此在數值模擬顯示中,即使最初的猜測值遠大於實際值,吾人還是可以求得準確的數值解,成功的重建出表面形狀函數、週期長度和相對介電常數,模擬結果顯示在近場量測的誤差要比遠場量測來的小 |
英文摘要 |
Microwave imaging is an imaging method that uses microwaves as a signal transfer, and belongs to the problem of electromagnetic backscattering. The principle is to irradiate the measured object with microwave, and then use the measurement value of the external scattering field to calculate the mathematical formula to obtain the final target-dielectric coefficient distribution. The dielectric coefficient can be used to reconstruct the shape, material, etc. of the object. Because the dielectric constant is closely related to the water content of biological tissues, microwave imaging is often used to image biological tissues. In this paper, we will study the near-field measurement of periodic non-flat surfaces and compare the error between the near and far fields. The results show that the reconstruction effect of the near field is better than that of the far field. Using known boundary conditions and measured scattering field values, we can derive a set of integral equations, and then calculate the electric field from the scattering field integral equations, convert the inverse scattering problem into an optimization problem, and then use the dynamic difference of self-adaptation Model evolution method (SADDE) reconstructs the object position and dielectric coefficient distribution, and compares the search speed and stability of the reconstruction of non-uniform objects. Using the self-adaptive dynamic differential evolution method to reconstruct a periodic non-flat surface, regardless of the initial guess value, the self-adaptive dynamic differential evolution method will always converge to the global extreme (global extreme), so in the numerical simulation In the display, even if the initial guess value is much larger than the actual value, we can still find an accurate numerical solution and successfully reconstruct the surface shape function, period length and relative dielectric constant. The simulation results show that the error in the near field measurement Smaller than measured in the far field. |
第三語言摘要 | |
論文目次 |
目錄 誌謝 I 中文摘要 II Abstract IV 目錄 VI 圖目錄 VIII 第一章 簡介 1 1.1 研究動機與相關文獻 1 1.2 本研究之貢獻 7 1.3 各章內容簡述 8 第二章 週期性非平坦表面之逆散射理論 10 2.1 正散射的理論公式推導 10 2.2 動差法求正散射公式 13 第三章 自我適應之動態差異性演化法 (Self-Adaptive Dynamic Differential Evolution)..........................16 第四章 數值分析及模擬結果 24 4.1 模擬環境介紹 25 4.2 模擬結果 27 第五章 結論 43 參考文獻 45 圖目錄 圖2.1 週期性非平坦表面示意圖 11 圖3.1 自我適應之動態差異型演化法流程圖 18 圖3.2 自我適應之動態差異型進化法中突變方法一的示意圖 20 圖3.3 自我適應之動態差異型進化法中突變方法二的示意圖 21 圖4.1 模擬環境示意圖 25 圖4.2 DF、DP在d=0.06之近場與遠場比較圖(a)遠場(y=2m) (b)近場 (y=0.05m)..............................................28 圖4.3 DF、DEPS在d=0.06之近場與遠場比較圖(a)遠場(y=2m) (b)(y=0.05m)..............................................29 圖4.4 d=0.06m加入不同雜訊比之DF、DP和DEPS比較圖(a)遠場(y=2m) (b)近場(y=0.05m) .......................................................30 圖4.5 10%雜訊表面之重建結果(a)遠場(y=2m) (b)近場(y=0.05m)….31 圖4.6 DF、DP在雜訊10%之近場與遠場比較圖(a)遠場(y=2m) (b)近場(y=0.05m).............................................34 圖4.7 DF、DEPS在雜訊10%之近場與遠場比較圖(a)遠場(y=2m) (b)近場(y=0.05m).............................................35 圖4.8 10%雜訊表面之重建結果(a)遠場(y=2m) (b)近場(y=0.05m).............................................36 圖4.9加入不同雜訊比之DF、DP和DEPS比較圖(a)遠場(y=2m) (b)近 場(y=0.05m)..............................................37 圖4.10 DF、DP在雜訊10%之近場與遠場比較圖(a)遠場(y=2m) (b)近場(y=0.05m)..............................................39 圖4.11 DF、DEPS在雜訊10%之近場與遠場比較圖(a)遠場(y=2m) (b)近場(y=0.05m)..............................................40 圖4.12 10%雜訊表面之重建結果。(a)遠場(y=2m)(b)近場=0.05m)............................................41 圖4.13加入不同雜訊比之DF、DP和DEPS比較圖(a)遠場(y=2m)(b)近場(y=0.05m)..............................................42 |
參考文獻 |
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