非平坦介質表面之微波成像

本論文探討非平坦介質表面進行重建的問題，吾人利用掩埋物體法進行重建，即將非平坦部分之介質視為一連串之物體，埋藏於平坦之半空間中，計算出這些掩埋物體之介電常數，就可以重建出非平坦介質表面之形狀，吾人利用積分方程式及量到的散射場，將逆散射問題轉化成最佳化問題，搭配自我適應之動態差異型演化法來處理大量未知數的電磁成像問題。本論文將會以非平坦介質表面為主軸，探討在此環境下，給予不同的初始條件，使用自我適應之動態差異型演化法(SADDE)重建，測試其對非平坦介質表面的搜尋速度及強建性。將非平坦介質表面視為一連串之物體掩埋於平坦之半空間中，一組為凸起之物體，另一組為凹陷之物體，並分別對兩組物體進行重建，首先推導其數學式，利用等效電流導出兩組物體的積分方程式，並使用動差法將其轉為矩陣，交由電腦計算散射場，並進行數值模擬。最後利用自我適應之動態差異性演化法重建出非平坦介質之表面，不論初始的猜測值如何，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，我們仍可求得準確的數值解，成功的重建出表面區域的介電常數。另外模擬結果亦顯示無論在低於5%雜訊的情況下，吾人都可重建出近似的結果

關鍵字

微波成像；子空間演算法；非平坦介質表面；自我適應之差異型演化法；整數型自我適應之差異型演化法

並列摘要

This thesis presents the reconstruction of rough surface ,we use the buried object approach to reconstruct the shape and dielectric constant of the rough surface. The rough surface is regarded as a series of objects buried in the flat half space which located alternately on both sides of a plan on interface between two half space .By calculating the dielectric constant of these buried objects, we can reconstruct the shape of rough surface use through the application of the integral equations and the measured scattered field, the inverse scattering problem is transformed into an optimization problem and solved by self-adaptive dynamic differential evolution(SADDE) which can process a lot of unknowns for the electromagnetic imaging problems. The thesis tests the search speed for SADDE by different initial guesses for the rough surface. The rough surface is regarded as a series of objects buried on the both sides of the flat half space. A group of convex objects, and a group of concave objects are to be reconstructed. The mathematical formula for the equivalent current is derived by applying two integral equations, then the moment method is employed to solve these equations by computer. By using the SADDE to reconstruct the rough surface, numerical results show that the SADDE converges to the overall extreme value (global extreme) regardless of the initial guess. Even if the initial guess is far away from the actual value, SADDE can get the correct shape and the dielectric constant of the rough surface. Simulation results also show that when the noise in less than 5%, we can also reconstruct the similar result.

並列關鍵字

Microwave Imaging ； Subspace-based Algorithm ； Rough Surface ； Integer type ； Self-Adaptive Dynamic Differential Evolution (SADDE)

參考文獻

[1] E. Wolf, “Three-dimensional structure determination of semi-transparentobjects from holographic data,” Opt. Commun., Vol. 1, pp.153–164, Sep.-Oct. 1969.

[2] O. Mudanyalı, S. Yıldız, O. Semerci, A. Yapar and I. Akduman, “A Microwave Tomographic Approach for Nondestructive Testing of Dielectric Coated Metallic Surfaces”, IEEE Geoscience and Remote Sensing Letters, Vol. 5, No. 2, pp. 180 - 184, Apr. 2008.

[3] S. Genovesi, E. Salerno, A. Monorchio and G. Manara, “Permittivity range profile reconstruction of multilayered structures from microwave backscattering data by using particle swarm optimization,” Microwave and Optical Technology Letters, Vol. 51, No. 10, pp. 2390 - 2394, Oct. 2009.

[4] T. Rubæk, O. S. Kim, P. Meincke, “Computational Validation of a 3-D Microwave Imaging System for Breast-Cancer Screening,” IEEE Transactions on Antennas and Propagation, vol. 57, No. 7, Jul. 2009.

[5] M. Klemm, J. A. Leendertz, D. Gibbins, I. J. Craddock, A. Preece, R. Benjamin, “Microwave Radar-Based Breast Cancer Detection: Imaging in Inhomogeneous Breast Phantoms” IEEE Antennas and Wireless Propagation Letters, Vol. 8, 2009.

國際替代計量

非平坦介質表面之微波成像

全文下載

主題瀏覽