A Multisurrogate-Assisted Optimization Framework for SSPP-Based mmWave Array Antenna

Abstract

Spoof surface plasmon polariton (SSPP) transmission lines are frequently used to excite millimeter-wave (mmWave) antenna arrays due to high field confinement and easy integration with planar structures. However, the design of the SSPP-based array antennas requires significant efforts because of multiple specifications, the high cost of electromagnetic (EM) evaluations, and a large number of design parameters. This article proposes a multisurrogate-assisted optimization framework for the efficient design of SSPP-based mmWave array antennas. The framework has three stages. In each stage, a surrogate is proposed to solve a specific task. The first stage is to find the initial values of four key design parameters using artificial neural network (ANN)-based surrogate model optimization. The second stage focuses on the optimization of sidelobe level based on another ANN surrogate model. The third stage is a beamforming-focused optimization procedure using the space mapping technique with an improved array factor formula as a surrogate. An mmWave SSPP-based array antenna with 16 circular patches at a central frequency of 28 GHz is successfully designed using the proposed framework. The antenna is also redesigned for five sets of main lobe directions and null locations at 24 GHz. All antennas are verified using full-wave EM simulations.