摘要
为改善在舰载相控阵雷达的光束控制中指向精度的参数指标,同时增强光束控制器性能与舰载相控阵雷达检测的准确性,本文通过相关影响因素分析,选取合理的器件参数,期望达到最佳效果。然后研究基于分数阶耦合复值神经网络的光束指向控制策略,通过对分数阶复值神经网络的投影同步的研究证明,系统的投影同步可以控制光束的指向。采用哈里斯鹰算法(HHO)对液晶相控阵进行光束指向精度优化,仿真实验结果表明,本文设计的全局与局部并行优化策略的哈里斯鹰算法,归一化精度误差由100数量级优化为10-4数量级,有效提高了舰载相控阵雷达的检测精度。
To improve the parameter index of pointing accuracy in the beam control of shipboard phased array radar,while enhancing the beam controller performance and the accuracy of shipboard phased array radar detection.This paper selects reasonable device parameters through the analysis of relevant influencing factors,expecting to achieve the best results.Then the beam pointing control strategy based on fractional-order coupled complex-valued neural network is studied.By applying a fractional-order complex-valued neural network to the projection synchronisation technique,it is shown that the method can achieve more accurate beam control pointing.The Harris Hawk algorithm(HHO)is used to optimize the beam pointing accuracy for liquid crystal phased arrays.The simulation experimental results show that the Harris Hawk algorithm with global and local parallel optimization strategies designed in this paper optimizes the normalized accuracy error from 100 orders of magnitude to 10-4 orders of magnitude and greatly reduces the fluctuation amplitude of the normalized accuracy error.This study effectively improves the detection accuracy of shipboard phased array radar.
作者
胡奇
王哲
田嘉政
耿辉
韦宇宁
HU Qil;WANG Zhe;TIAN Jia-zheng;GENG Hui;WEI Yu-ning(School of Artificial Intelligence,Changchun University of Science and Technology,Changchun 130022,China;School of Electronic Information Engineering,Changchun University of Science and Technology,Changchun 130022,China)
出处
《舰船科学技术》
北大核心
2023年第10期135-138,共4页
Ship Science and Technology
基金
吉林省教育厅科技专项(JJKH20210835KJ)。
关键词
液晶相控阵
光束偏转
指向精度优化
分数阶复值神经网络
哈里斯鹰优化算法
liquid crystal phased array
beam deflection
pointing accuracy optimization
fractional-order complexvalued neural networks
Harris Hawks optimization algorithm
