Application of the Global Optimization Approaches to Planar Near-Field Antenna Phaseless Measurements

Abstract

This paper deals with a method of the radiation pattern determination of the directional antennas. The method combining both the functional minimization method and the Fourier iterative algorithm is based on the phaseless near-field measurement on two plane surfaces. The method is used for a reconstruction of the phase distribution on the aperture of the measured antenna, and for the determination of the antenna radiation pattern, consequently. The binary genetic algorithm (BGA), the realvalued genetic algorithm (RVGA), the particle swarm optimization (PSO), and differential evolutionary algorithm (DEA) were chosen for the global functional minimization. The paper is aimed to analyze the performance of the global optimizations (GOs) when solving the described problem, and to compare the GOs. GOs were examined through data achieved by measurement of a horn antenna and a parabola.

Keywords

• Radiation pattern
• planar near-field scanning
• particle swarm optimization (PSO)
• binary genetic algorithms (BGA)
• real-valued genetic algorithm (RVGA)
• differential evolutionary algorithm (DEA)
• Fourier iterative algorithm