General Framework for the Efficient Optimization of Reflectarray Antennas for Contoured Beam Space Applications

Abstract

This paper describes a general framework for the optimization of very large reflectarrays for space applications. It employs the generalized intersection approach as optimizing algorithm, integrating a number of techniques that substantially improve the baseline algorithm by accelerating computations while preserving the accuracy of the electromagnetic analysis. In particular, a learning algorithm based on support vector machines is used to obtain a surrogate model of the reflectarray unit cell accelerating the analysis more than three orders of magnitude. For the optimization, the gradient computation is accelerated by employing the technique of differential contributions on the radiated field, which avoids the use of the fast Fourier transform in the computation of the far field. Finally, to improve the cross-polarization performance, instead of optimizing the crosspolar pattern, the crosspolar discrimination or crosspolar isolation is optimized, improving both the antenna and algorithm performances. Relevant numerical examples are provided to show the capabilities of the proposed framework for a Direct Broadcast Satellite mission, showing how to design a contoured beam reflectarray with a European footprint with two different coverage zones. In addition, a complete study of computing time is carried out to analyze the impact of each technique in the optimization process.

Keywords

• Very large reflectarray
• radiation pattern synthesis
• contoured beam
• crosspolar optimization
• machine learning technique
• support vector machines