Uncertainty Analysis of Antenna Response Using Adaptive Surrogate Model

As the material property error of antenna impact the electromagnetic (EM) performance of the antenna system, a novel analytic approach for the research of the effect on antenna response with the material property error based on surrogate model and model-order reduction is proposed. The material property error of antenna is modeled as interval parameters. A Method based on the proper orthogonal decomposition (POD) is addressed to accurately and rapidly predict the EM performance of antenna. In this method, a reduced basis is constructed from a set of full-order snapshots by the POD, and the Kriging model is used to approximate the projection coefficients. Moreover, a multi-point parallel adaptive sampling algorithm is used to improve the accuracy of proposed model. Then the derived model can be used as efficient surrogate for statistical analysis of antennas EM performance. Some numerical results are presented to illustrate the accuracy and efficiency of the proposed method. The proposed approach has good prospect to be applied in uncertainty analysis.