Array antenna pattern synthesis method based on intelligent algorithm

Zhang He, Z. Hua, L. Hongmei, Liu Beijia, Wu Qun
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引用次数: 3

Abstract

The paper introduced the basic theories of intelligent algorithms, equally spaced linear antenna array and antenna pattern synthesis principle, also introduced the related omni-directional antenna. The procedure, parameter settings, characteristics of genetic algorithm and the neural network algorithms were demonstrated that used in the pattern synthesis, then the simulation programs were given. In the experimental stage, three groups of three different DOA of interference signal were applied to the antenna array model, respectively. The genetic algorithm and neural network algorithm were applied to the array pattern that simulated, then the simulation results were statisticed to compare their accuracy and robustness. At the same time, the linear antenna array model was established by the FEKO simulation software, whose antenna element is omni-directional COCO antenna whose center frequency is 1.8GHz. The weight coefficient produced by genetic algorithm and neural network algorithm were applied to the excitation voltage of every array elements, whose amplitude and phase is controlled by the weight coefficient. Then the results were analyzed which came from the two intelligent algorithms with different interference signals.
基于智能算法的阵列天线方向图合成方法
本文介绍了智能算法的基本理论、等间距线性天线阵列和天线方向图合成原理,并介绍了相关的全向天线。介绍了遗传算法和神经网络算法在模式综合中的应用过程、参数设置、特点,并给出了仿真程序。在实验阶段,对天线阵模型分别施加三组三种不同DOA的干扰信号。将遗传算法和神经网络算法应用于模拟的阵列方向图,并对仿真结果进行统计,比较其精度和鲁棒性。同时,利用FEKO仿真软件建立线性天线阵模型,天线单元为中心频率为1.8GHz的全向COCO天线。将遗传算法和神经网络算法产生的权系数应用于阵列各单元的激励电压,通过权系数控制各单元的幅值和相位。然后对两种智能算法在不同干扰信号下的结果进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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