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基于二阶统计量盲源分离算法的无源雷达同频干扰抑制研究

吕晓德 孙正豪 刘忠胜 张汉良 刘平羽

吕晓德, 孙正豪, 刘忠胜, 张汉良, 刘平羽. 基于二阶统计量盲源分离算法的无源雷达同频干扰抑制研究[J]. 电子与信息学报, 2020, 42(5): 1288-1296. doi: 10.11999/JEIT190178
引用本文: 吕晓德, 孙正豪, 刘忠胜, 张汉良, 刘平羽. 基于二阶统计量盲源分离算法的无源雷达同频干扰抑制研究[J]. 电子与信息学报, 2020, 42(5): 1288-1296. doi: 10.11999/JEIT190178
Xiaode LÜ, Zhenghao SUN, Zhongsheng LIU, Hanliang ZHANG, Pingyu LIU. Research on Suppressing Co-channel Interference of Passive Radar Based on Blind Source Separation Using Second Order Statistics[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1288-1296. doi: 10.11999/JEIT190178
Citation: Xiaode LÜ, Zhenghao SUN, Zhongsheng LIU, Hanliang ZHANG, Pingyu LIU. Research on Suppressing Co-channel Interference of Passive Radar Based on Blind Source Separation Using Second Order Statistics[J]. Journal of Electronics & Information Technology, 2020, 42(5): 1288-1296. doi: 10.11999/JEIT190178

基于二阶统计量盲源分离算法的无源雷达同频干扰抑制研究

doi: 10.11999/JEIT190178
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

    孙正豪:男,1995年生,硕士生,研究方向为无源雷达信号处理

    刘忠胜:男,1977年生,副研究员,研究方向为干涉SAR信号处理

    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

    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:

    孙正豪 sunzhenghao17@mails.ucas.ac.cn

  • 中图分类号: TN958.97

Research on Suppressing Co-channel Interference of Passive Radar Based on Blind Source Separation Using Second Order Statistics

  • 摘要:

    针对基于长期演进(LTE)信号的无源雷达存在同频基站干扰的问题,该文提出一种基于2阶统计量的盲源分离算法,该算法是在卷积混合模型下,通过多通道最小均方(LMS)算法实现分离信号之间的相关性最小。由于各发射基站信号之间统计不相关,当分离信号之间的相关性达到最小时,完成观测信号的分离。在此基础上,改进了传统无源雷达信号处理的流程,增加了分离同频干扰基站直达波和多径杂波的步骤,实现了对同频干扰基站杂波的抑制。通过仿真分析,验证了算法的有效性,为基于LTE信号的无源雷达数据处理提供了参考。

  • 图  1  盲源分离模型结构图

    图  2  信号卷积混合滤波器模型

    图  3  信号后向分离滤波器模型

    图  4  i个通道的分离系统示意图

    图  5  无源雷达信号处理流程图

    图  6  传统无源雷达杂波对消能量对比图

    图  7  观测信号与源信号的散点图

    图  8  传统处理流程后的互模糊距离剖面图

    图  9  分离信号与源信号散点图

    图  10  对消能量比较图

    图  11  改进的处理流程后的互模糊距离剖面图

    图  12  噪声对杂波对消比的影响

    表  1  多通道LMS算法总结

     参数:$N$= 源数目,$M$= 观测信号数目
        一般假设$N = M$
        ${K_i}$= 分离滤波器阶数,$i = 1,2, ··· ,N$
        ${\mu _{ij}}$= 步长,$i,j = 1,2, ··· ,N$,且$i \ne j$
     输入:${x_i}\left( t \right) = $观测信号,$i = 1,2, ··· ,N$
     初始化:${ {{W} }_{ {{ij} } } }\left( 0 \right) = { {{{\textit{0}}} }_{ {{Kj} } } }$, $i,j = 1,2, ··· ,N$,且$i \ne j$
         ${ {{Y} }_i}\left( t \right) = { {{{\textit{0}}} }_{Ki} }$, $i = 1,2, ··· ,N$
         ${K_i}$选取$K \ge \max \left\{ {{K_i},i = 1,2, ··· ,N} \right\}$
         ${\mu _{ij}}$根据输入数据进行调整
     计算:对$t = 1,2, ··· $,迭代计算:
        ${y_i}\left( t \right) = {x_i}\left( t \right) - \displaystyle\sum\nolimits_{j \ne i,j = 1}^N { {{W} }_{ij}^{\rm{T} }\left( {t - 1} \right){ {{Y} }_j}\left( t \right)} $
        ${{{W}}_{ij}}\left( t \right) = {{{W}}_{ij}}\left( {t - 1} \right) + {\mu _{ij}}{y_i}\left( t \right){{{Y}}_j}\left( t \right)$
        ${{{Y}}_i}\left( t \right) = {\left[ {{y_i}\left( {t - 1} \right),{y_i}\left( {t - 2} \right), ··· ,{y_i}\left( {t - {K_i}} \right)} \right]^{\rm{T}}}$
        $i,j = 1,2, ··· ,N,i \ne j$
     终止条件:前后两次分离信号之间相关性系数的变化量小于所设
          的误差门限
     输出:${y_i}\left( t \right) = $分离信号,$i = 1,2, ··· ,N$
    下载: 导出CSV

    表  2  回波通道1仿真参数

    主基站信号同频干扰基站信号
    时延(μs)衰减(dB)时延(μs)衰减(dB)
    直达波000.07–1
    多径10.13–80.20–9
    多径20.29–110.36–12
    多径30.42–150.59–15
    弱多径0.16~1.95–20~>–300.16~1.95–20~>–30
    目标111.39–30
    目标217.15–37
    下载: 导出CSV

    表  3  回波通道2仿真参数

    主基站信号同频干扰基站信号
    时延(μs)衰减(dB)时延(μs)衰减(dB)
    直达波0.03–20–1
    多径10.19–80.16–9
    多径20.35–140.36–13
    多径30.46–190.49–14
    弱多径0.16~1.95–20~–300.16~1.95–20~–30
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-03-25
  • 修回日期:  2019-11-25
  • 网络出版日期:  2019-12-14
  • 刊出日期:  2020-06-04

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