用于宽带频率不变光束图案合成的有效卷积神经网络

IF 3.7 2区 计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Xiao Yan Ju;Yong Qiang Hei;Wen Tao Li
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引用次数: 0

摘要

在这篇文章中,提出了一个基于卷积神经网络(CNN)的框架来实现高效的宽带频率不变(FI)波束图合成。利用CNN获取一组优化后的有限脉冲响应(FIR)滤波器系数,对应于期望的宽带FI图。在本文提出的CNN框架中,将由期望模式的上界得到的一组初始化的滤波器系数作为未标记的输入样本,两个输入通道分别表示滤波器系数的实部和虚部。通过精心设计损耗函数,实现了低旁瓣电平和频率不变波束方向图。然后,通过最小化训练过程中的损失函数,获得所需模式对应的滤波器系数。给出了宽带FI铅笔波束图、异形波束图和可扫描波束图的数值算例,验证了该方法的灵活性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective Convolutional Neural Network for Wideband Frequency Invariant Beam Pattern Synthesis
In this letter, a convolutional neural network (CNN) based framework is proposed to achieve efficient wideband frequency invariant (FI) beampattern synthesis. The CNN is employed to acquire a set of optimized finite-impulse-response (FIR) filter coefficients corresponding to the desired wideband FI pattern. In the proposed CNN framework, a set of initialized filter coefficients obtained by the upper bound of the desired pattern is taken as the unlabeled input sample, with two input channels representing the real and the imaginary parts of the filter coefficients, respectively. By carefully designing loss function, low sidelobe level (SLL) and frequency invariant beam pattern are well achieved. Then, by minimizing the loss function during the training process, the filter coefficients corresponding to the desired pattern are acquired. Numerical examples involving wideband FI pencil-beam pattern, shaped beam pattern, and scannable beam pattern are provided to validate the flexibility and effectiveness of the proposed method.
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来源期刊
CiteScore
8.00
自引率
9.50%
发文量
529
审稿时长
1.0 months
期刊介绍: IEEE Antennas and Wireless Propagation Letters (AWP Letters) is devoted to the rapid electronic publication of short manuscripts in the technical areas of Antennas and Wireless Propagation. These are areas of competence for the IEEE Antennas and Propagation Society (AP-S). AWPL aims to be one of the "fastest" journals among IEEE publications. This means that for papers that are eventually accepted, it is intended that an author may expect his or her paper to appear in IEEE Xplore, on average, around two months after submission.
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