基于卷积神经网络的空间导航信号抗干扰处理技术  

Anti-jamming Processing Technology of Space Navigation Signal Based on Convolutional Neural Network

作　　者：王春霞 刘新芳 WANG Chunxia;LIU Xinfang(School of Optoelectronic Information,Minnan Science and Technology University,Quanzhou 362332,China)

机构地区：[1]闽南科技学院光电信息学院,福建泉州362332

出　　处：《无线电工程》2023年第11期2659-2663,共5页Radio Engineering

基　　金：泉州市高校中青年学科(专业)带头人培养对象计划(泉教高[2018]1号)。

摘　　要：为了提高空间导航信号抗干扰能力,提出基于卷积神经网络(Convolutional Neural Network,CNN)的空间导航信号抗干扰技术。构建空间导航信号的卫星传感采样模型,通过等间隔均衡调度的方法进行空间导航信号的输出均衡控制,对采集的空间导航信号进行波束聚焦和信号增强处理,提取空间导航信号的时频相关性特征量,采集空间导航信号的空间频谱特征量,根据信号的频谱特征收敛性进行信号补偿和滤波抑制。采用CNN滤波器进行空间导航信号的信号滤波处理,对导航信号的抗干扰能力进行优化,实现空间导航信号增强和抗干扰滤波的技术处理。仿真结果表明,采用该方法进行空间导航信号滤波处理的抗干扰性较好,输出信噪比较高,提高了空间导航信号的高精度采样和信号均衡传输能力。In order to improve the anti-jamming capability of space navigation signal,the anti-jamming technology of space navigation signal based on Convolutional Neural Network(CNN)is proposed.Construct a satellite sensing sampling model for space navigation signals,control the output balance of space navigation signals through equal interval equalization scheduling,carry out beam focusing and signal enhancement processing on the collected space navigation signals,extract the time-frequency correlation characteristics of the space navigation signals,collect the spatial spectral characteristics of the space navigation signals,and perform signal compensation and filtering suppression based on the convergence of the signal’s spectral characteristics.The CNN filter is used to filter the space navigation signal,optimize the anti-jamming ability of navigation signal,and realize the technical processing of space navigation signal enhancement and anti-jamming filtering.The simulation results show that using the proposed method for filtering spatial navigation signals has good anti-jamming performance and high output signal-to-noise ratio,and improves the high-precision sampling and signal equalization transmission capabilities of space navigation signals.

关 键 词：卷积神经网络 卫星导航 抗干扰技术 滤波处理 

分 类 号：TN919[电子电信—通信与信息系统]