矩形微带贴片天线叠加载荷效应快速估计的神经网络建模

S. Chakraborty, S. Mandal, B. Gupta
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引用次数: 2

摘要

提出了一种用于研究介电层覆盖矩形微带天线谐振频率漂移的神经网络模型。这种载荷的主要作用是改变天线的谐振频率。变化的绝对值随工作频率、相对介电常数和介电层厚度的增加而增大。如果在设计中不考虑负载的影响,这种变化可能会由于微带天线固有的窄带宽而导致性能下降。本文提出的神经网络模型可用于设计可能受到结冰或其他大气沉积或涂有保护层的微带天线。所建立的模型与矩量法的电磁仿真结果吻合较好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural network modeling for the fast estimation of superstrate loading effect on rectangular microstrip patch antennas
A neural network model for the shift in resonant frequency of a rectangular microstrip antenna covered with a dielectric layer is presented. The primary effect of such loading is to change the resonant frequency of the antenna. The absolute value of change increases with operating frequency, relative permittivity and the thickness of the dielectric layer. This change may cause degradation in performance due to the inherently narrow bandwidth of microstrip antennas, if the effect of loading is not considered in the design. The neural network model presented here may be used to design microstrip antennas that may be subjected to icing or other atmospheric deposition or coated with protective layers. The model developed is found to be in good agreement with electromagnetic simulation using method of moments.
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