高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

广义逆高斯纹理杂波背景下的自适应失配检测器

范一飞 陈铎 粟嘉 郭子薰 陶明亮 王伶

范一飞, 陈铎, 粟嘉, 郭子薰, 陶明亮, 王伶. 广义逆高斯纹理杂波背景下的自适应失配检测器[J]. 电子与信息学报. doi: 10.11999/JEIT231440
引用本文: 范一飞, 陈铎, 粟嘉, 郭子薰, 陶明亮, 王伶. 广义逆高斯纹理杂波背景下的自适应失配检测器[J]. 电子与信息学报. doi: 10.11999/JEIT231440
FAN Yifei, CHEN Duo, SU Jia, GUO Zixun, TAO Mingliang, WANG Ling. Adaptive Detectors for Mismatched Signal under Sea Clutter Background with Generalized Inverse Gaussian Texture[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231440
Citation: FAN Yifei, CHEN Duo, SU Jia, GUO Zixun, TAO Mingliang, WANG Ling. Adaptive Detectors for Mismatched Signal under Sea Clutter Background with Generalized Inverse Gaussian Texture[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT231440

广义逆高斯纹理杂波背景下的自适应失配检测器

doi: 10.11999/JEIT231440
基金项目: 国家自然科学基金(62171379,62301435),中国博士后科学基金(2023M732870),博士后创新人才支持计划(BX20230497),上海航天科技创新基金(SAST2023-044)
详细信息
    作者简介:

    范一飞:男,副研究员,博士,主要研究方向为雷达信号处理、海面微弱目标检测

    陈铎:男,硕士,要研究方向为海杂波背景下的微弱目标检测

    粟嘉:男,副教授,博士,主要研究方向为雷达信号处理、雷达干扰抑制

    郭子薰:女,博士后,博士,主要研究方向为雷达信号处理、海面微弱目标检测

    陶明亮:男,副教授,博士,主要研究方向为雷达信号处理、雷达干扰抑制

    王伶:男,教授,博士,主要研究方向为阵列信号处理、抗干扰处理

    通讯作者:

    范一飞 fanyifei888@163.com

  • 中图分类号: TN95

Adaptive Detectors for Mismatched Signal under Sea Clutter Background with Generalized Inverse Gaussian Texture

Funds: National Natural Science Foundation of China (62171379, 62301435), China Postdoctoral Science Foundation (2023M732870), Postdoctoral Innovation Talents Support Program (BX20230497), ShangHai Aerospace Science and Technology Innovation Fund (SAST2023-044)
  • 摘要: 针对雷达对海探测过程中理论导向矢量与实际导向矢量之间不匹配导致的虚警概率升高的问题,该文在复合高斯模型(CGM)下设计自适应失配检测器。为了抑制失配信号,在零假设中引入与理论导向矢量正交的虚拟信号,从而给出存在失配信号的目标检测模型。将CGM的纹理分量建模为广义逆高斯分布,分别基于两步广义似然比(GLRT)和最大后验GLRT(MAP GLRT)准则发展类似于自适应波束形成器正交抑制检测(ABORT)的自适应失配检测器,并通过理论证明所提失配检测器对散斑协方差矩阵和目标多普勒导向矢量具有恒虚警(CFAR)特性。仿真和实测数据实验结果表明,所提失配检测器在导向矢量匹配情况下的检测性能和失配情况下的抗失配性能之间具有良好的折衷。
  • 图  1  失配示意图

    图  2  在匹配情况下提出的检测器与对比检测器的目标检测性能

    图  3  在失配情况下提出的检测器与对比检测器的目标检测性能

    图  4  检测器虚警概率曲线

    图  5  实测海杂波数据背景下检测器性能分析

    图  6  检测器抗失配性能对比

    表  1  导向矢量匹配时上述检测器检测概率达到$90\% $时所需要的SCR(dB)

    检测器类型ANMFABORTGIG-GLRTMAP-GLRTα-AMFA-CGGIGAM-GIGIG
    信杂比8.407.615.705.715.825.805.93
    下载: 导出CSV

    表  2  导向矢量匹配时上述检测器检测概率达到$90\% $时所需要的SCR(dB)

    检测器类型ANMFABORTGIG-GLRTMAP-GLRTα-AMFA-CGGIGAM-GIGIG
    信杂比12.8812.1611.3411.5011.4311.3711.53
    下载: 导出CSV
  • [1] 许述文, 白晓惠, 郭子薰, 等. 海杂波背景下雷达目标特征检测方法的现状与展望[J]. 雷达学报, 2020, 9(4): 684–714. doi: 10.12000/JR20084.

    XU Shuwen, BAI Xiaohui, GUO Zixun, et al. Status and prospects of feature-based detection methods for floating targets on the sea surface[J]. Journal of Radars, 2020, 9(4): 684–714. doi: 10.12000/JR20084.
    [2] XIN Zhihui, LIAO Guisheng, YANG Zhiwei, et al. Analysis of distribution using graphical goodness of fit for airborne SAR sea-clutter data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(10): 5719–5728. doi: 10.1109/TGRS.2017.2712700.
    [3] LIANG Xiang, YU Han, ZOU Pengjia, et al. Multiscan recursive Bayesian parameter estimation of large-scene spatial-temporally varying generalized Pareto distribution model of sea clutter[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5115416. doi: 10.1109/TGRS.2022.3191467.
    [4] 水鹏朗, 田超, 封天. 逆高斯纹理复合高斯杂波对异常样本稳健的三分位点估计方法[J]. 电子与信息学报, 2023, 45(2): 542–549. doi: 10.11999/JEIT211483.

    SHUI Penglang, TIAN Chao, and FENG Tian. Outlier-robust tri-percentile parameter estimation method of compound-Gaussian clutter with inverse Gaussian textures[J]. Journal of Electronics & Information Technology, 2023, 45(2): 542–549. doi: 10.11999/JEIT211483.
    [5] XUE Jian, XU Shuwen, LIU Jun, et al. Model for non-Gaussian sea clutter amplitudes using generalized inverse Gaussian texture[J]. IEEE Geoscience and Remote Sensing Letters, 2019, 16(6): 892–896. doi: 10.1109/LGRS.2018.2886782.
    [6] CONTE E, LOPS M, and RICCI G. Asymptotically optimum radar detection in compound-Gaussian clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 1995, 31(2): 617–625. doi: 10.1109/7.381910.
    [7] DONG Yunhan. Optimal coherent radar detection in a K-distributed clutter environment[J]. IET Radar, Sonar & Navigation, 2012, 6(5): 283–292. doi: 10.1049/iet-rsn.2011.0273.
    [8] SANGSTON K J, GINI F, and GRECO M S. Coherent radar target detection in heavy-tailed compound-Gaussian clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012, 48(1): 64–77. doi: 10.1109/TAES.2012.6129621.
    [9] CHEN Sijia, KONG Lingjiang, and YANG Jianyu. Adaptive detection in compound-Gaussian clutter with inverse Gaussian texture[J]. Progress in Electromagnetics Research M, 2013, 28: 157–167. doi: 10.2528/PIERM12121209.
    [10] 薛健. 复合高斯海杂波背景雷达目标检测算法[D]. [博士论文], 西安电子科技大学, 2020: 80–88. doi: 10.27389/d.cnki.gxadu.2020.000039.

    XUE Jian. Radar target detection methods in compound-Gaussian sea clutter[D]. [Ph. D. dissertation], Xidian University, 2020: 80–88. doi: 10.27389/d.cnki.gxadu.2020.000039.
    [11] XU Shuwen, WANG Zhexiang, BAI Xiaohui, et al. Optimum and near-optimum coherent CFAR detection of radar targets in compound-Gaussian clutter with generalized inverse Gaussian texture[J]. IEEE Transactions on Aerospace and Electronic Systems, 2022, 58(3): 1692–1706. doi: 10.1109/TAES.2021.3120045.
    [12] 施赛楠, 水鹏朗, 刘明. 基于复合高斯杂波纹理结构的相干检测[J]. 电子与信息学报, 2016, 38(8): 1969–1976. doi: 10.11999/JEIT151194.

    SHI Sainan, SHUI Penglang, and LIU Ming. Coherent detection based on texture structure in compound-Gaussian clutter[J]. Journal of Electronics & Information Technology, 2016, 38(8): 1969–1976. doi: 10.11999/JEIT151194.
    [13] WANG Zhihang, HE Zishu, HE Qin, et al. Persymmetric range-spread targets detection in compound Gaussian sea clutter with inverse Gaussian texture[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 8018305. doi: 10.1109/LGRS.2021.3101369.
    [14] PULSONE N B and RADER C M. Adaptive beamformer orthogonal rejection test[J]. IEEE Transactions on Signal Processing, 2001, 49(3): 521–529. doi: 10.1109/78.905870.
    [15] WANG Zhihang, HE Zishu, HE Qin, et al. Adaptive CFAR detectors for mismatched signal in compound Gaussian sea clutter with inverse Gaussian texture[J]. IEEE Geoscience and Remote Sensing Letters, 2022, 19: 3502705. doi: 10.1109/LGRS.2020.3047390.
    [16] WANG Zeyu, GANG Li, and LI Ming. Adaptive detection of distributed target in the presence of signal mismatch in compound Gaussian clutter[J]. Digital Signal Processing, 2020, 102: 102755. doi: 10.1016/j.dsp.2020.102755.
    [17] 王喆祥. 海杂波背景下雷达目标自适应检测算法研究[D]. [硕士论文], 西安电子科技大学, 2021: 12, 16. doi: 10.27389/d.cnki.gxadu.2021.001059.

    WANG Zhexiang. Research on adaptive detection algorithm of radar targets in sea clutter[D]. [Master dissertation], Xidian University, 2021: 12, 16. doi: 10.27389/d.cnki.gxadu.2021.001059.
    [18] PASCAL F, FORSTER P, OVARLEZ J P, et al. Performance analysis of covariance matrix estimates in impulsive noise[J]. IEEE Transactions on Signal Processing, 2008, 56(6): 2206–2217. doi: 10.1109/TSP.2007.914311.
  • 加载中
图(6) / 表(2)
计量
  • 文章访问数:  65
  • HTML全文浏览量:  23
  • PDF下载量:  9
  • 被引次数: 0
出版历程
  • 收稿日期:  2024-01-02
  • 修回日期:  2024-04-24
  • 网络出版日期:  2024-05-15

目录

    /

    返回文章
    返回