摘要
为了删除网络内的离群点,提升辐射干扰信号检测性能,设计了面向大数据网络的舰船辐射干扰信号检测方法。选取软硬结合的划分策略分割舰船网络中的信号集,通过并行处理方式检测信号集内各元素的离群度并删除离群点;采用Hilbert变换方法与小波包方法结合,通过包络解调方式提取完成预处理的舰船辐射干扰信号特征;将所提取的舰船辐射干扰信号特征,利用自组织特征映射神经网络检测舰船辐射干扰信号。实验结果表明,该方法可以有效检测面向网络的不同类型舰船辐射干扰信号,具有较高的可行性。
Research on the detection method of ship radiated interference signal for big data network,delete outliers in the big data network,and improve the performance of radiated interference signal detection.Select a combination of software and hardware to divide the signal set in the ship’s big data network,and use parallel processing to detect and delete outliers based on the outliers of each element in the signal set.The Hilbert transform method and wavelet packet method are combined,and the pre-processed ship radiated interference signal characteristics are extracted through envelope demodulation;the extracted ship radiated interference signal characteristics are used by self-organization.Feature mapping neural network detects interference signals radiated by ships.Experimental results show that this method can effectively detect the interference signals radiated by different types of ships facing big data networks,and it has high feasibility.
作者
周雪芳
高长全
刘阳
ZHOU Xue-fang;GAO Chang-quan;LIU Yang(Qingdao Huanghai College,Qingdao 266500,China;The 41 Research Institute of China Electronics Technology Group Corporation,Qingdao 266500,China;Qingdao Beihai Shipbuilding Industry Co.,Ltd.,Qingdao 266520,China)
出处
《舰船科学技术》
北大核心
2022年第3期147-150,共4页
Ship Science and Technology
基金
青岛市源头创新计划应用基础研究项目(18-2-2-41-jch)。
关键词
大数据网络
舰船
辐射干扰信号
检测方法
离群度
空域相关滤波
big data network
ship
radiated interference signal
detection method
outlier
airspace correlation filtering
作者简介
周雪芳(1985-),女,硕士,副教授,研究方向为大数据技术应用及过程挖掘。
