Design of Neural-Network-Based Mutual Coupling Compensators for Printed Planar Antenna Arrays

被引:1
作者
Alzahed, Abdelelah M. [1 ]
Antar, Yahia M. M. [1 ]
Mikki, Said [2 ]
机构
[1] Royal Mil Coll Canada, Dept Elect & Comp Engn, Kingston, ON, Canada
[2] Univ New Haven, Dept Elect & Comp Engn & Comp Sci, West Haven, CT USA
来源
2020 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION AND NORTH AMERICAN RADIO SCIENCE MEETING | 2020年
关键词
D O I
10.1109/IEEECONF35879.2020.9330214
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We propose a methodology to compensate the effect of mutual coupling in planar antenna array arrangements using a novel electromagnetic machine learning (ML) technique. The electromagnetic behavior of the array elements and their mutual coupling interactions are described via the antenna current Green's function (ACGF). A ML artificial neural network (ANN) procedure is then applied and combined with the ACGF to optimize array ports and mitigate for mutual coupling effects.
引用
收藏
页码:1035 / 1036
页数:2
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