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Reflection phase analysis based on multilayer perceptron network model for unit element design of a dual-layered microstrip reflectarray

机译:基于多层感知器网络模型的反射相位分析用于双层微带反射阵列单元设计

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摘要

In this paper, the most common neural network architecture called as the multilayer perceptron (MLP) Model is presented as convenient interface for obtaining and optimizing the phase characterization of the dual-layered Minkowski unit element. The high priority objective of Reflectarray antenna design is to get the reflection phase characteristic that has small gradient and wider phase range. For this purpose, firstly the Reflectarray unit element was placed at the end of a standard X-band H-wall waveguide simulator and its reflection phase characteristics were obtained by the 3D Computer Simulation Technology Microwave Studio (CST MWS) simulations. Thereafter MLP Network Model is constructed to approximate this nonlinear relationship between the geometrical properties of antenna parameters and the reflection phase characteristics. In comparison with the target data network output data, it is understood that the MLP network structure can be used as a very effective method to estimate the reflection phase characteristics of Reflectarray unit element.
机译:在本文中,提出了最常见的称为多层感知器(MLP)模型的神经网络体系结构,作为获取和优化双层Minkowski单元元素的相表征的便捷接口。 Reflectarray天线设计的最高优先目标是获得具有小梯度和宽相位范围的反射相位特性。为此,首先将Reflectarray单元元素放置在标准X波段H壁波导模拟器的末端,并通过3D计算机仿真技术微波工作室(CST MWS)仿真获得其反射相位特性。此后,构建MLP网络模型以近似估计天线参数的几何特性与反射相位特性之间的非线性关系。与目标数据网络输出数据相比,可以理解,MLP网络结构可以用作估计Reflectarray单元元素的反射相位特性的非常有效的方法。

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