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基于帕累托前沿遍历和设计外推法的电磁驱动宽带圆极化天线尺寸缩减与多准则优化

EM-driven size reduction and multi-criterial optimization of broadband circularly-polarized antennas using pareto front traversing and design extrapolation.

作者信息

Ullah Ubaid, Al-Hasan Muath, Koziel Slawomir, Mabrouk Ismail Ben

机构信息

Al Ain University, P.O. Box (112612), Abu Dhabi, United Arab Emirates.

Engineering Optimization and Modeling Center, Reykjavik University, 102, Reykjavik, Iceland.

出版信息

Sci Rep. 2022 Jun 14;12(1):9877. doi: 10.1038/s41598-022-13958-9.

Abstract

Maintaining small size has become an important consideration in the design of contemporary antenna structures. In the case of broadband circularly polarized (CP) antennas, miniaturization is a challenging process due to the necessity of simultaneous handling of electrical and field properties (reflection, axial ratio, gain), as well as ensuring sufficient frequency range of operation, especially at the lower edge of the antenna bandwidth. An additional difficulty is that-for the sake of reliability-the design process has to be based on full-wave electromagnetic simulation tools. This is a computationally expensive endeavor because rendering the minimum-size design under the assumed constraints concerning the operating frequencies requires rigorous numerical optimization, which entails massive evaluations of the structure at hand. This paper describes an algorithmic framework for efficient identification of broadband CP antenna designs that realize the best possible trade-offs (Pareto set) between the antenna size and its operating bandwidth. The designs are generated sequentially by solving local optimization tasks targeting explicit reduction of the antenna footprint with implicit constraints imposed on the reflection and axial ratio characteristics. The data accumulated during the previous iterations is employed to yield good initial points for further stages by means of inverse surrogates and extrapolation. Low cost of the process is ensured by sparse sensitivity updates within the trust-region gradient-based algorithm being the main optimization engine. The proposed methodology is demonstrated using three examples of wide-slot CP structures with the trade-off designs representing broad ranges of achievable antenna sizes and operating bandwidth. The framework can be used to assess the antenna suitability for particular application areas as well to conclusively compare alternative CP geometries from the point of view of achievable miniaturization rate and capability of fulfilling given performance requirements.

摘要

在当代天线结构设计中,保持小尺寸已成为一个重要考量因素。对于宽带圆极化(CP)天线而言,由于需要同时处理电气和场特性(反射、轴比、增益),以及确保足够的工作频率范围,特别是在天线带宽的下限,小型化是一个具有挑战性的过程。另一个困难在于,为了保证可靠性,设计过程必须基于全波电磁仿真工具。这是一项计算成本高昂的工作,因为要在关于工作频率的假定约束下实现最小尺寸设计,需要进行严格的数值优化,这就需要对现有结构进行大量评估。本文描述了一种算法框架,用于高效识别宽带CP天线设计,该设计能在天线尺寸与其工作带宽之间实现最佳权衡(帕累托集)。通过解决局部优化任务来依次生成设计,这些任务旨在明确减小天线尺寸,并对反射和轴比特性施加隐含约束。利用在前几次迭代中积累的数据,借助逆代理和外推法为后续阶段提供良好的初始点。通过作为主要优化引擎的基于信赖域梯度的算法中的稀疏灵敏度更新,确保了该过程的低成本。使用三个宽缝CP结构示例展示了所提出的方法,其权衡设计代表了可实现的天线尺寸和工作带宽的广泛范围。该框架可用于评估天线对特定应用领域的适用性,也可从可实现的小型化率和满足给定性能要求的能力角度,最终比较替代CP几何结构。

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