An Efficient Antenna Optimization Method Based on Kriging Model and Multidimensional Uniform Sampling

During the process of antenna design and optimization, classical optimization methods often require hundreds or even thousands trials of different parameter combinations, which leads to a low efficiency in solving multi-parameter and large scale optimization problems. In this paper, a quick and approximate computation of the EM response can be realized though a Kriging model, which is created by fitting the simulation results to their structural parameters. The number of EM simulation needed can be reduced by Latin Hypercube Sampling for MultiDimensional Uniformity (LHS-MDU) at the initial stage and a candidate-selecting method in the following optimization loops. In order to optimize the resonant frequency and impedance bandwidth, the feed position of a rectangular patch antenna and the dipole lengths of a dual-band monopole antenna are adjusted by the proposed method and compared with the genetic optimization, the numbers of EM simulation are reduced by 75% and 84% respectively.