部分均匀环境下适用于空间对称线阵的修正广义似然比检测方法

闫林杰 郝程鹏 殷超然 孙苇轩 侯朝焕

闫林杰, 郝程鹏, 殷超然, 等. 部分均匀环境下适用于空间对称线阵的修正广义似然比检测方法[J]. 雷达学报, 2021, 10(3): 443–452. doi: 10.12000/JR20140
引用本文: 闫林杰, 郝程鹏, 殷超然, 等. 部分均匀环境下适用于空间对称线阵的修正广义似然比检测方法[J]. 雷达学报, 2021, 10(3): 443–452. doi: 10.12000/JR20140
YAN Linjie, HAO Chengpeng, YIN Chaoran, et al. Modified generalized likelihood ratio test detection based on a symmetrically spaced linear array in partially homogeneous environments[J]. Journal of Radars, 2021, 10(3): 443–452. doi: 10.12000/JR20140
Citation: YAN Linjie, HAO Chengpeng, YIN Chaoran, et al. Modified generalized likelihood ratio test detection based on a symmetrically spaced linear array in partially homogeneous environments[J]. Journal of Radars, 2021, 10(3): 443–452. doi: 10.12000/JR20140

部分均匀环境下适用于空间对称线阵的修正广义似然比检测方法

doi: 10.12000/JR20140
基金项目: 国家自然科学基金(61971412)
详细信息
    作者简介:

    闫林杰(1992–),女,山东青岛人,中国科学院声学研究所博士,主要研究方向为信号检测与估计,雷达、声呐信号检测

    郝程鹏(1975–),男,中国科学院声学研究所研究员,博士生导师。IEEE Senior Member、中高会智能信息处理产业化分会副理事长、中国电子学会青年科学家俱乐部会员,担任SCI源刊IEEE Access, EURASIP Journal on Advances in Signal Processing和Signal, Image and Video Processing副主编。主要从事雷达、水声信号处理相关研究

    殷超然(1996–),男,陕西西安人,中国科学院声学研究所博士生,主要研究方向为统计信号处理与自适应目标检测

    孙苇轩(1997–),女,内蒙古赤峰人,中国科学院声学研究所硕士生。主要研究方向为空时自适应处理

    侯朝焕(1936–),男,四川自贡人,中国科学院声学研究所研究员,博士生导师。1958年于北京大学物理系获得学士学位,现担任中国科学院大学教授。主要研究方向为信号信息处理、水声学。目前已发表论文200余篇

    通讯作者:

    郝程鹏 haochengp@mail.ioa.ac.cn

  • 责任主编:谢文冲 Corresponding Editor: XIE Wenchong
  • 1在本文中,将接收回波中目标信号采用目标能量泄漏采样模型、干扰信号采用斜对称先验结构的接收信号模型统称为斜对称泄漏模型。
  • 中图分类号: TN957.51

Modified Generalized Likelihood Ratio Test Detection Based on a Symmetrically Spaced Linear Array in Partially Homogeneous Environments

Funds: The National Natural Science Foundation of China (61971412)
More Information
  • 摘要: 针对部分均匀高斯干扰环境下的点目标检测问题,该文基于广义似然比准则(GLRT)提出一种适用于空间对称线阵的修正GLRT检测方法。考虑到采样时存在的目标能量泄漏,在接收信号建模时采用目标能量泄漏采样模型弥补泄漏损失,并基于干扰协方差矩阵的斜对称结构降低对辅助数据的需求,最终联合待检测数据和辅助数据实现未知参数的估计,得到兼具有良好目标检测和距离估计性能的斜对称修正GLRT检测方法。仿真结果表明,该方法不仅在部分均匀环境下具有恒虚警特性,而且在辅助数据数量受限时,相比其同类型的检测方法具有1 dB以上的检测性能优势。

     

  • 图  1  PM-GLRT-PHE的${P_{\rm{fa}}}$$\gamma $的变化曲线

    Figure  1.  ${P_{\rm{fa}}}$ against $\gamma $ for the PM-GLRT-PHE

    图  2  PM-GLRT-PHE的${P_{\rm{fa}}}$$\rho $的变化曲线

    Figure  2.  ${P_{\rm{fa}}}$ against $\rho $ for the PM-GLRT-PHE

    图  3  辅助数据数量受限时的目标检测和距离估计性能

    Figure  3.  Detection and range estimation performance with small number of auxiliary samples

    图  4  不同$\gamma $下各检测方法的${P_{\rm{d}}}$随SCNR的变化曲线

    Figure  4.  ${P_{\rm{d}}}$ against SCNR for each detection method under different $\gamma $

    图  5  SCNR=18 dB时下各检测方法的${P_{\rm{d}}}$$\gamma $变化曲线

    Figure  5.  ${P_{\rm{d}}}$ against $\gamma $ for each detection method when SCNR=18 dB

    图  6  不同$\gamma $下各检测方法的${\delta _{\rm{rms}}}$随SCNR的变化曲线

    Figure  6.  ${\delta _{\rm{rms}}}$ against SCNR for each detection method under different $\gamma $

    图  7  SCNR=18 dB时各检测方法的${\delta _{\rm{rms}}}$$\gamma $的变化曲线

    Figure  7.  ${\delta _{\rm{rms}}}$ against $\gamma $ for each detection method when SCNR=18 dB

    图  8  辅助数据数量充足时的目标检测和距离估计性能

    Figure  8.  Detection and range estimation performance with sufficient number of auxiliary samples

    表  1  不同场景下PM-GLRT-PHE的阈值

    Table  1.   Thresholds of PM-GLRT-PHE in different cases

    仿真场景干扰数量干扰波达角度阈值$\eta $
    场景1002.0098
    场景212.0484
    场景325°, 10°2.0188
    场景43–15°, 5°, 15°1.9873
    场景54–20°, –10°, 5°, 20°2.0308
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出版历程
  • 收稿日期:  2020-11-16
  • 修回日期:  2020-12-25
  • 网络出版日期:  2021-01-13
  • 刊出日期:  2021-06-28

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