基于卷积神经网络的共形天线阵广义辐射方向图综合方法

Shiyuan Zhang, Chen Wang, Da Huang, Haobo Han, M. Bai
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引用次数: 1

摘要

随着天线阵布局的日益复杂,有效地合成共形天线阵辐射方向图的方法已成为一个挑战。本文提出了一种基于卷积神经网络的广义共形天线阵辐射方向图综合方法。在此基础上,采用基于泰勒孔径投影法生成训练样本,并将训练标签设计为双通道数据矩阵。设计了共形天线阵的仿真实验,成功地合成了训练集和测试集的辐射方向图。结果表明,训练后的网络对共形天线阵辐射方向图的合成具有较高的效率和良好的泛化效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Generalizing Radiation Pattern Synthesis Method for Conformal Antenna Array Based on Convolutional Neural Network
With the increasing complexity of antenna array layouts, the efficient methods for synthesizing the radiation patterns of conformal antenna arrays have been the challenge. In this paper, a generalized method based on convolution neural network is proposed to synthesize the radiation patterns of conformal antenna arrays. Furthermore, the Taylor-based aperture projection method is used to generate the training samples and training labels are designed as some two-channel data matrices. Simulation experiments have been designed with a conformal antenna array, of which the radiation patterns of training set and test set are successfully synthesized. The results show that the trained network has high efficiency and good generalization effect for synthesizing the radiation patterns of conformal antenna array.
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