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A Study on Reconfigurable Antenna Array Feed Networks Using Distributed Switched-Line Phase Shifters for mm-Wave Operation

使用分布式开关线移相器进行毫米波操作的可重构天线阵列馈电网络的研究

基本信息

批准号：
2496930
负责人：
金额：
--
依托单位：
Queen Mary University of London
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2496930
关键词：
Study Reconfigurable Antenna Array Feed

项目摘要

The primary aim of the research is to design a passive high-gain planar mm-wave antenna which can be electronically scanned in two dimensions by reconfiguring the array feed network. In addition to this, the research aims to implement a design which could be realised using phase-change materials to minimise the insertion loss and size of a switch-line phase shifter, which is suitable for use in an antenna array feed network (this is fundamental to increasing the operating frequency well into the mm-wave bands). Finally, the research also aims to reduce the complexity of configuring the antenna array by developing a machine learning algorithm to assist with the array design incorporating the switched-line phase shifters. The research aims to answer the following questions: 1) What benefits can be offered by distributing phase shifters throughout the array feed network rather than at each individual element? 2) Can phase-change materials facilitate sufficiently low-loss RF switches at mm-wave frequencies suitable for a reconfigurable antenna feed network? 3) Can a machine learning algorithm enable a reduction in the complexity of a large dual-scan array configuration by reducing the number of redundant phase states? To be updated in January 2024 (at Year 3 Progression)

该研究的主要目的是设计一种无源高增益平面毫米波天线，该天线可以通过重新配置阵列馈电网络进行二维电子扫描。除此之外，该研究的目的是实现一种可以使用相变材料实现的设计，以最大限度地减少开关线移相器的插入损耗和尺寸，该设计适合在天线阵列馈电网络中使用（这是将工作频率提高到毫米波段的基础）。最后，该研究还旨在通过开发机器学习算法来协助结合开关线移相器的阵列设计，从而降低配置天线阵列的复杂性。该研究旨在回答以下问题：1）通过在整个阵列馈电网络而不是在每个单独的元件上分布移相器可以带来什么好处？ 2) 相变材料能否在适合可重构天线馈电网络的毫米波频率下实现足够低损耗的射频开关？ 3）机器学习算法能否通过减少冗余相位状态的数量来降低大型双扫描阵列配置的复杂性？将于 2024 年 1 月更新（第 3 年进展）