Development and implementation of efficient segmentation algorithm for the design of antennas and arrays

Abstract

The method of moments (MoM) is a common numerical technique for solving integral equations. However, the method generates dense matrix which is computationally expensive to solve, and this limits the complexity of problems which can be analyzed. To reduce the computational cost of the method of moments, iterative solvers are employed to solve the dense matrix. However, iterative solvers may lead to convergence difficulties in dealing with large scale objects. In order to overcome the convergence issue, segmentation techniques, which can significantly reduce the number of unknowns, are used to analyze large structures. The focus of this thesis is to develop improved segmentation method for effective simulation of large scale problems. This is achieved by a new grouping concept of near-far neighbour evaluation which combines macro-basis function with progressive method coupled with adaptive integral method (MBF-PM-AIM). To further improve the accuracy of the solution, a new iterative refinement process, which utilizes the concept of the macro-basis function, is introduced. After developing the segmentation technique, MBF-PM-AIM is applied to the design of broadband probe-fed antennas and arrays. Due to the growing demand of modern wireless communication systems, there is a need to enhance the impedance bandwidth of the antennas. In this thesis, various wideband semi-circle probe-fed antennas and arrays are developed for wireless local area network.