基于正交投影的子带信息几何雷达弱小目标检测方法

杨政 程永强 吴昊 黎湘 王宏强

杨政, 程永强, 吴昊, 等. 基于正交投影的子带信息几何雷达弱小目标检测方法[J]. 雷达学报, 2023, 12(4): 776–792. doi: 10.12000/JR23079
引用本文: 杨政, 程永强, 吴昊, 等. 基于正交投影的子带信息几何雷达弱小目标检测方法[J]. 雷达学报, 2023, 12(4): 776–792. doi: 10.12000/JR23079
YANG Zheng, CHENG Yongqiang, WU Hao, et al. Subband information geometry detection method based on orthogonal projection for weak radar targets[J]. Journal of Radars, 2023, 12(4): 776–792. doi: 10.12000/JR23079
Citation: YANG Zheng, CHENG Yongqiang, WU Hao, et al. Subband information geometry detection method based on orthogonal projection for weak radar targets[J]. Journal of Radars, 2023, 12(4): 776–792. doi: 10.12000/JR23079

基于正交投影的子带信息几何雷达弱小目标检测方法

doi: 10.12000/JR23079
基金项目: 国家自然科学基金(61921001),湖南省杰出青年基金(2022JJ10063)
详细信息
    作者简介:

    杨 政,博士生,主要研究方向为雷达目标检测和信息几何

    程永强,教授,主要研究方向为雷达目标检测、信息几何和雷达前视成像

    吴 昊,博士生,主要研究方向为雷达目标检测和信息几何

    黎 湘,教授,主要研究方向为目标识别、信号检测和雷达成像

    王宏强,研究员,主要研究方向为太赫兹技术、量子雷达和雷达目标特性

    通讯作者:

    程永强 nudtyqcheng@gmail.com

  • 责任主编:陈小龙 Corresponding Editor: CHEN Xiaolong
  • 中图分类号: TN957.51

Subband Information Geometry Detection Method Based on Orthogonal Projection for Weak Radar Targets

Funds: The National Natural Science Foundation of China (61921001), Distinguished Youth Science Foundation of Hunan Province (2022JJ10063)
More Information
  • 摘要: 基于信息几何理论的雷达目标检测是一种新兴的技术,它将目标检测问题转化为流形上目标与杂波的区分问题,在低信杂比检测中具有优势。对于复杂背景下的弱小目标检测,目标与杂波难以区分,限制着检测性能。因此,该文基于矩阵信息几何检测器,提出一种基于正交投影的子带信息几何目标检测方法。该文利用滤波器组对雷达回波信号进行子带分解,并在矩阵流形上稳健估计子带内强杂波信号子空间,提出基于流形的正交投影方法以抑制强杂波,增强目标与杂波的区分性。最后,采用仿真数据和实测海杂波数据验证所提方法的有效性。结果表明,所提方法能够有效抑制强杂波,具有较好的检测性能。

     

  • 图  1  矩阵信息几何检测器原理框图

    Figure  1.  Block scheme of MIG detector

    图  2  HPD矩阵流形的几何解释

    Figure  2.  Geometric interpretation on HPD matrix manifold

    图  3  子带滤波器组频率幅度响应

    Figure  3.  Amplitude frequency response of subband filter bank

    图  4  代数均值与几何均值的对比

    Figure  4.  Comparison between arithmetic mean and geometric mean

    图  5  基于正交投影的子带信息几何检测流程图

    Figure  5.  Flowchart of subband geometric detection based on orthogonal projection

    图  6  加入干扰信号后不同方法的平均影响函数值

    Figure  6.  Mean value of the influence function for different methods after adding interferences

    图  7  K分布杂波下的检测概率($K = n$)

    Figure  7.  Probabilities of detection for K distribution clutter ($K = n$)

    图  8  K分布杂波下的检测性能曲线($K = 2n$)

    Figure  8.  Probabilities of detection for K distribution clutter ($K = 2n$)

    图  9  数据集杂波谱

    Figure  9.  Clutter power spectrum of the data set

    图  10  IPIX雷达数据的归一化检测统计量(${f_{\rm{d}}} = 160$ Hz)

    Figure  10.  Normalized detection statistics of the IPIX radar data (${f_{\rm{d}}} = 160$ Hz)

    图  11  基于IPIX雷达数据的检测概率(${f_{\rm{d}}} = 160$ Hz)

    Figure  11.  Probabilities of detection for the IPIX radar data (${f_{\rm{d}}} = 160$ Hz)

    图  12  基于IPIX雷达数据的检测概率(${f_{\rm{d}}} = 350$ Hz)

    Figure  12.  Probabilities of detection for the IPIX radar data (${f_{\rm{d}}} = 350$ Hz)

    图  13  海杂波与目标探测数据采集的试验场景

    Figure  13.  Sea clutter and target detection experimental scenario

    图  14  数据集20210106150614_02_staring的归一化距离-脉冲图

    Figure  14.  Normalized range-pulse of data set 20210106150614_02_staring

    图  15  NAU实验数据(目标位于4.84 km处)

    Figure  15.  Experimental data of NAU (the target is located at 4.84 km)

    图  16  NAU数据的归一化检测统计量

    Figure  16.  Normalized detection statistics of the NAU data

    图  17  归一化一维距离像

    Figure  17.  Normalized range profile

    图  18  NAU数据的接收机工作特性曲线

    Figure  18.  ROC curves of different methods for the NAU data

    1  基于正交投影的子带信息几何检测方法

    1.   Subband MIG detection method based on orthogonal projection

     输入:雷达待检测单元回波信号$ {{\boldsymbol{z}}_D} $和杂波参考单元回波信号$ {\left\{ {{{\boldsymbol{z}}_k}} \right\}_{k \in \left[ K \right]}} $。
     输出:检测决策:${\mathcal{D}^{(l)} }\left( {\Re \left( { { {\boldsymbol{z} }_D} } \right),\bar \Re \left( { { {\left\{ { { {\boldsymbol{z} }_k} } \right\} }_{k \in \left[ K \right]} } } \right)} \right)\mathop \gtrless \limits_{ {\mathcal{H}_0} }^{ {\mathcal{H}_1} } {\eta ^{(l)} }, \;\;{l = - L,-(L-1), \cdots ,0, \cdots ,L}$。
     For $l = - L,-(L-1), \cdots ,0, \cdots ,L$:
      1:首先基于子带滤波器,对雷达回波信号进行子带滤波,获得子带滤波信号$ {\boldsymbol{z}}_D^{(l)} = \mathfrak{L}\left( {{{\boldsymbol{z}}_D}} \right) $和$ {\left\{ {{\boldsymbol{z}}_k^{(l)} = \mathfrak{L}\left( {{{\boldsymbol{z}}_k}} \right)} \right\}_{k \in \left[ K \right]}} $;
      2:基于流形估计子带内的杂波信号子空间,并进行稳健的正交投影,得到目标增强信号$ {\boldsymbol{\tilde z}}_D^{(l)} = \mathfrak{P}\left( {{\boldsymbol{z}}_D^{(l)}} \right) $和$ {\left\{ {{\boldsymbol{\tilde z}}_k^{(l)} = \mathfrak{P}\left( {{\boldsymbol{z}}_k^{(l)}} \right)} \right\}_{k \in \left[ K \right]}} $;
      3:将基于流形正交投影后的信号表征为HPD矩阵,计算待检测单元HPD矩阵$ \Re \left( {{{\boldsymbol{z}}_D}} \right) $和杂波参考单元HPD矩阵$ {\left\{ {\Re \left( {{{\boldsymbol{z}}_k}} \right)} \right\}_{k \in \left[ K \right]}} $,并计算
        几何均值$ \bar \Re \left( {{{\left\{ {{{\boldsymbol{z}}_k}} \right\}}_{k \in \left[ K \right]}}} \right) $;
      4:计算几何检测统计量$ {\mathcal{D}^{(l)}}\left( {\Re \left( {{{\boldsymbol{z}}_D}} \right),\bar \Re \left( {{{\left\{ {{{\boldsymbol{z}}_k}} \right\}}_{k \in \left[ K \right]}}} \right)} \right) $,并与门限$ {\eta ^{(l)}} $进行比较,完成检测判决
        $ {\mathcal{D}^{(l)}}\left( {\Re \left( {{{\boldsymbol{z}}_D}} \right),\bar \Re \left( {{{\left\{ {{{\boldsymbol{z}}_k}} \right\}}_{k \in \left[ K \right]}}} \right)} \right)\mathop \gtrless \limits_{{\mathcal{H}_0}}^{{\mathcal{H}_1}} {\eta ^{(l)}} $。
     End
    下载: 导出CSV

    表  1  不同方法的计算复杂度

    Table  1.   The computation complexity of different methods

    方法计算复杂度
    本文方法$ \mathcal{O}\left( {M\left( {K{n^3} + {n^3} + \left( {n + Q} \right)\log \left( {n + Q} \right)} \right)} \right) $
    RD$ \mathcal{O}\left( {\nu K{n^3}} \right) $
    LE$ \mathcal{O}\left( {K{n^3}} \right) $
    KLD$ \mathcal{O}\left( {K{n^3}} \right) $
    LD$ \mathcal{O}\left( {\varepsilon K{n^3}} \right) $
    FFT$ \mathcal{O}\left( {n\log n + Kn} \right) $
    ANMF$ \mathcal{O}\left( {{n^3} + K{n^2}} \right) $
    SANMF$ \mathcal{O}\left( {M\left( {{n^3} + K{n^2}} \right)} \right) $
    ME$ \mathcal{O}\left( {K\left( {{n^3} + n} \right)} \right) $
    PS-GLRT$ \mathcal{O}\left( {{n^3} + K{n^2}} \right) $
    2S-Rao$ \mathcal{O}\left( {{n^3} + K{n^2}} \right) $
    下载: 导出CSV

    表  2  数据文件19980204_155537_ANTSTEP参数

    Table  2.   Parameters of data file 19980204_155537_ANTSTEP

    参数数值
    载频(GHz)9.39
    脉冲重复频率(Hz)1000
    距离单元数28
    脉冲数60000
    距离分辨率(m)30
    下载: 导出CSV

    表  3  数据文件20210106150614_02_staring参数

    Table  3.   Parameters of data file 20210106150614_02_staring

    参数数值
    载频(GHz)9.3~9.5
    脉冲重复频率(Hz)1704
    距离单元数4346
    脉冲数6000
    采样频率(MHz)60
    目标位置(km)4.84
    下载: 导出CSV
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    LIU Ningbo, DING Hao, HUANG Yong, et al. Annual progress of the sea-detecting X-band radar and data acquisition program[J]. Journal of Radars, 2021, 10(1): 173–182. doi: 10.12000/JR21011
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出版历程
  • 收稿日期:  2023-05-09
  • 修回日期:  2023-06-13
  • 网络出版日期:  2023-07-06
  • 刊出日期:  2023-08-28

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