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基于LTE信号的外辐射源雷达同频基站干扰抑制方法研究

吕晓德 张汉良 刘忠胜 孙正豪 刘平羽

吕晓德, 张汉良, 刘忠胜, 孙正豪, 刘平羽. 基于LTE信号的外辐射源雷达同频基站干扰抑制方法研究[J]. 电子与信息学报, 2019, 41(9): 2123-2130. doi: 10.11999/JEIT180904
引用本文: 吕晓德, 张汉良, 刘忠胜, 孙正豪, 刘平羽. 基于LTE信号的外辐射源雷达同频基站干扰抑制方法研究[J]. 电子与信息学报, 2019, 41(9): 2123-2130. doi: 10.11999/JEIT180904
Xiaode LÜ, Hanliang ZHANG, Zhongsheng LIU, Zhenghao SUN, Pingyu LIU. Research on Co-channel Base Station Interference Suppression Method of Passive Radar Based on LTE Signal[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2123-2130. doi: 10.11999/JEIT180904
Citation: Xiaode LÜ, Hanliang ZHANG, Zhongsheng LIU, Zhenghao SUN, Pingyu LIU. Research on Co-channel Base Station Interference Suppression Method of Passive Radar Based on LTE Signal[J]. Journal of Electronics & Information Technology, 2019, 41(9): 2123-2130. doi: 10.11999/JEIT180904

基于LTE信号的外辐射源雷达同频基站干扰抑制方法研究

doi: 10.11999/JEIT180904
详细信息
    作者简介:

    吕晓德:男,1969年生,研究员,研究方向为基于阵列技术的的新体制雷达系统及其应用

    张汉良:男,1993年生,硕士生,研究方向为基于LTE信号的无源雷达信号处理

    孙正豪:男,1994年生,硕士生,研究方向为无源雷达信号处理

    刘平羽:男,1994年生,硕士生,研究方向为无源雷达信号处理

    通讯作者:

    张汉良 zhanghanliang16@mails.ucas.ac.cn

  • 中图分类号: TN958.97

Research on Co-channel Base Station Interference Suppression Method of Passive Radar Based on LTE Signal

  • 摘要: 针对基于LTE信号的外辐射源雷达接收信号包含多个同频发射基站的直达波和多径杂波干扰的问题,该文对传统的外辐射源雷达信号处理流程进行了改进,增加了对同频基站干扰的处理步骤,提出了一种基于卷积混合模型的盲源分离算法来抑制同频基站的杂波干扰。假设混合矩阵是一个矢量线性时不变滤波器矩阵,以互信息为代价函数,通过求取互信息的梯度,用最速下降法进行迭代,分离准则是使分离后的信号之间互信息最小化。仿真表明,该文算法能够有效地抑制LTE信号同频发射基站的杂波干扰,为后续的主基站杂波对消处理提供了基础。
  • 图  1  基于LTE信号的外辐射源雷达系统接收模型

    图  2  外辐射源雷达信号处理流程

    图  3  传统外辐射源雷达信号处理流程中杂波对消结果

    图  4  基于卷积混合模型的盲源分离模型结构框图

    图  5  天线接收信号与原始基站信号散点图

    图  6  未进行对消时互模糊函数距离剖面

    图  7  盲源分离后信号与原始基站信号散点图

    图  8  对消同频基站杂波后的互模糊函数距离剖面

    图  9  对消同频基站及主基站杂波后互模糊函数距离剖面

    表  2  仿真参数

    主基站同频干扰基站
    强干扰弱干扰目标强干扰弱干扰
    直达波多径1多径2多径3多径4目标1目标2直达波多径1多径2
    时延(μs)00.230.260.290.03~3.2215.9222.7512.9935.2213.02~16.24
    衰减(dB)0–12–20–21–46–34–23–6–7.5–46
    下载: 导出CSV

    表  1  基于卷积混合模型的盲源分离算法

     初始化:Y(n)=X(n);
     循环迭代:
     (1)从{–M,–M+1,···,+M}中选择一个随机值m
     (2)计算(Y1(n),Y2(n-m))之间的互信息梯度${{\text{β}}_{{{\text{Y}}^{\left( m \right)}}}}$;
     (3)更新输出:Y(m)Y(m)-${\rm{\mu }}{{\text{β}}_{{{\text{Y}}^{\left( m \right)}}}}$(Y(m));
       归一化:移除DC分量,并令Yi=Yi/${{\rm{\sigma }}_{\rm{i}}}$,${{\rm{\sigma }}_{\rm{i}}}$为Yi的标准偏差;
     (4)由式(8)计算分离矩阵Bk, k=0,1,···,p
     (5)令Y(n)=[B(z)Y(n)];
     收敛或达到最大迭代次数后停止循环。
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-09-20
  • 修回日期:  2019-02-25
  • 网络出版日期:  2019-03-14
  • 刊出日期:  2019-09-10

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