基于主辅通道联合处理的无源雷达同频干扰抑制方法研究

刘平羽 吕晓德 刘忠胜 张汉良

刘平羽, 吕晓德, 刘忠胜, 等. 基于主辅通道联合处理的无源雷达同频干扰抑制方法研究[J]. 雷达学报, 2020, 9(6): 974–986. doi: 10.12000/JR19047
引用本文: 刘平羽, 吕晓德, 刘忠胜, 等. 基于主辅通道联合处理的无源雷达同频干扰抑制方法研究[J]. 雷达学报, 2020, 9(6): 974–986. doi: 10.12000/JR19047
LIU Pingyu, LYU Xiaode, LIU Zhongsheng, et al. Research on co-channel interference suppression method for passive radar based on the jiont processing of primary and reference channels[J]. Journal of Radars, 2020, 9(6): 974–986. doi: 10.12000/JR19047
Citation: LIU Pingyu, LYU Xiaode, LIU Zhongsheng, et al. Research on co-channel interference suppression method for passive radar based on the jiont processing of primary and reference channels[J]. Journal of Radars, 2020, 9(6): 974–986. doi: 10.12000/JR19047

基于主辅通道联合处理的无源雷达同频干扰抑制方法研究

doi: 10.12000/JR19047
基金项目: 国家自然科学基金(61771453),国家部委基金
详细信息
    作者简介:

    刘平羽(1994–),男,江苏人,西安电子科技大学学士,中国科学院空天信息创新研究院硕士研究生,主要研究方向为基于民用通信信号的无源雷达信号处理。E-mail: liupingyu17@mails.ucas.ac.cn

    吕晓德(1969–),男,中国科学院空天信息创新研究院研究员,研究方向为阵列天线及其信号处理、先进雷达探测技术和天线新技术及其应用。长期从事雷达信号处理技术的研究,曾获国家科技进步一等奖、省部级科技进步二等奖各一项。E-mail: louee@mail.ie.ac.cn

    张汉良(1993–),男,内蒙古人,吉林大学学士,中国科学院空天信息创新研究院硕士研究生,研究方向为无源雷达信号处理。E-mail: zhanghanliang16@mails.ucas.ac.cn

    通讯作者:

    吕晓德 louee@mail.ie.ac.cn

  • 责任主编:万显荣 Corresponding Editor: WAN Xianrong
  • 中图分类号: TN958.97

Research on Co-channel Interference Suppression Method for Passive Radar Based on the Jiont Processing of Primary and Reference Channels

Funds: The National Natural Science Foundation of China (61771453), The National Ministries Foundation
More Information
  • 摘要: 基于民用通信信号的无源雷达由于其辐射源分布密集,主通道与参考通道容易同时受同频辐射源干扰,严重影响检测效果。针对上述问题,该文提出了一种加入同频干扰抑制的信号处理流程。改进流程首先对所有通道接收信号联合处理,使用多通道盲反卷积算法估计各个辐射源直达波,再利用各通道主辐射源信号能量占比差异识别主辐射源直达波作为参考信号,然后对主通道中各辐射源杂波信号进行对消,最后用主辐射源直达波与对消剩余信号进行互模糊运算,完成目标检测。改进流程可以在不改变现有系统硬件条件的情况下有效抑制同频干扰,提升对消比,降低互模糊函数底噪,减少漏警。仿真分析与实测数据验证说明了该方法的正确性和有效性。

     

  • 图  1  无源雷达信号处理流程

    Figure  1.  Signal processing flows of passive radar

    图  2  多通道盲反卷积算法示意图

    Figure  2.  Schematic diagram of multi-channel blind deconvolution algorithm

    图  4  处理结果(互模糊函数距离-多普勒平面)

    Figure  4.  Processing results (range-Doppler plane of the cross-ambiguity function)

    图  5  处理结果(互模糊函数距离剖面)

    Figure  5.  Processing result (range profile of the cross-ambiguity function)

    图  6  实验场景

    Figure  6.  Experiment scenes

    图  7  处理结果(互模糊函数三维图)

    Figure  7.  Processing result (3-D graph of the cross-ambiguity function)

    图  8  处理结果(互模糊函数距离剖面图)

    Figure  8.  Processing result (range profile of the cross-ambiguity function)

    表  1  多通道盲反卷积算法步骤

    Table  1.   Algorithm procedure of multi-channel blind deconvolution

     参数:${\text{κ}},{\rm{batchsize}},L,\alpha ,\beta ,b,h,r$
     输入:${\text{x}}\left( n \right)$
     初始化:${{\text{W}}_{\rm{0}}} = {\text{I}},{{\text{W}}_k} = {\text{0}}\left( {k = 1,2, ·\!·\!· ,L - 1} \right),{\text{y}}\left( n \right) = {\text{x}}\left( n \right),{{\text{υ}}_k} = {\text{0}}$
     循环:
     (1) 随机选取${{\text{q}}_1},{{\text{q}}_2}, ·\!·\!· ,{{\text{q}}_{{\rm{batchsize}}}} \in {\text{κ}} $;
     (2) 对每个${{\text{h}}_i} \in \left\{ {{{\text{q}}_1},{{\text{q}}_2}, ·\!·\!· ,{{\text{q}}_{{\rm{batchsize}}}}} \right\}$,估计${\text{K}}_{{{\text{y}}^{\left( {{{\text{h}}_i}} \right)}}}^{\left( { - {{\text{h}}_i}} \right)}\left( n \right)$;
     (3) 对$k = 0{\rm{ ,1,}} ·\!·\!· {\rm{,}}L - 1$,更新${{\text{υ}}_k}$,${{\text{W}}_k}$:
       ${{\text{υ}}_k} \leftarrow \beta {{\text{υ}}_k} + \left( {1 - \beta } \right){\rm{E}}\left\{ {\left[ {\sum\nolimits_{{{\text{h}}_i} \in \left\{ {{{\text{q}}_1},{{\text{q}}_2}, ··· ,{{\text{q}}_{{\rm{batchsize}}}}} \right\}} {{\text{K}}_{{{\text{y}}^{\left( {{{\text{h}}_i}} \right)}}}^{\left( { - {{\text{h}}_i}} \right)}\left( n \right) + 2\left( {{\text{y}}\left( n \right) - {\text{x}}\left( n \right)} \right) + {\text{Φ}}\left( n \right)} } \right]{\text{x}}{{\left( {n - k} \right)}^{\rm{T}}}} \right\}$
       ${{\text{W}}_k} \leftarrow {{\text{W}}_k} - \alpha {{\text{υ}}_k}$;
     (4) 更新${\text{y}}\left( n \right)$:${\text{y}}\left( n \right) \leftarrow \sum\limits_{k = {\rm{0}}}^{L - 1} {{{\text{W}}_k}{\text{x}}\left( {n - k} \right)} $;
     (5) 判断:收敛或达到最大迭代次数后结束循环。
    下载: 导出CSV

    表  2  主通道1接收信号成分

    Table  2.   Signal component of primary channel 1

    信号源信号成分
    参数直达波多径1多径2多径3强目标1弱目标2
    主辐射源时延(μs)0.10.31.62.146.159.1
    幅度(dB)–0.41–19.53–28.29–35.09–33.15–43.10
    干扰辐射源1时延(μs)00.71.22.419.9
    幅度(dB)–3.10–19.27–20.57–29.79–33.98
    干扰辐射源2时延(μs)00.51.72.6
    幅度(dB)–2.55–18.63–21.75–33.31
    下载: 导出CSV

    表  3  主通道2接收信号成分

    Table  3.   Signal component of primary channel 2

    信号源信号成分
    参数直达波多径1多径2多径3强目标1弱目标2
    主辐射源时延(μs)0.10.81.62.246.159.1
    幅度(dB)–0.16–20.17–28.62–32.52–30.74–40.56
    干扰辐射源1时延(μs)00.31.52.4
    幅度(dB)–3.28–19.99–23.13–36.34
    干扰辐射源2时延(μs)00.51.82.3
    幅度(dB)–2.56–19.58–25.93–30.22
    下载: 导出CSV

    表  4  参考通道接收信号成分

    Table  4.   Signal component of reference channel

    信号源信号成分
    参数直达波多径1多径2多径3
    主辐射源时延(μs)01.11.72.9
    幅度(dB)0–22.05–28.64–34.42
    干扰辐射源1时延(μs)0.20.71.32.8
    幅度(dB)–10.17–22.82–23.99–33.00
    干扰辐射源2时延(μs)0.10.51.52.3
    幅度(dB)–9.37–24.40–26.03–35.21
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-04-05
  • 修回日期:  2019-06-03
  • 网络出版日期:  2019-08-05
  • 刊出日期:  2020-12-28

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