基于矩阵信息几何的飞机尾流目标检测方法

刘俊凯 李健兵 马梁 陈忠宽 蔡益朝

刘俊凯, 李健兵, 马梁, 陈忠宽, 蔡益朝. 基于矩阵信息几何的飞机尾流目标检测方法[J]. 雷达学报, 2017, 6(6): 699-708. doi: 10.12000/JR17058
引用本文: 刘俊凯, 李健兵, 马梁, 陈忠宽, 蔡益朝. 基于矩阵信息几何的飞机尾流目标检测方法[J]. 雷达学报, 2017, 6(6): 699-708. doi: 10.12000/JR17058
Liu Junkai, Li Jianbing, Ma Liang, Chen Zhongkuan, Cai Yichao. Radar Target Detection Method of Aircraft Wake Vortices Based on Matrix Information Geometry[J]. Journal of Radars, 2017, 6(6): 699-708. doi: 10.12000/JR17058
Citation: Liu Junkai, Li Jianbing, Ma Liang, Chen Zhongkuan, Cai Yichao. Radar Target Detection Method of Aircraft Wake Vortices Based on Matrix Information Geometry[J]. Journal of Radars, 2017, 6(6): 699-708. doi: 10.12000/JR17058

基于矩阵信息几何的飞机尾流目标检测方法

doi: 10.12000/JR17058
基金项目: 国家自然科学基金(61302193,61401503)
详细信息
    作者简介:

    刘俊凯(1979–),男,河北景县,博士,讲师,主要研究方向为新体制雷达探测技术、目标检测、相控阵雷达建模仿真。E-mail: liujkradar@163.com

    李健兵(1979–),男,博士,副研究员,硕士生导师,IEEE Senior Member,中国电子学会高级会员,主要研究方向为大尺度分布式复杂目标的雷达特性与探测。E-mail: jianbingli@nudt.edu.cn

    马梁:马   梁(1983–),男,博士,讲师,主要研究方向为极化信息处理、目标识别、相控阵雷达建模仿真

    通讯作者:

    刘俊凯   liujkradar@163.com

Radar Target Detection Method of Aircraft Wake Vortices Based on Matrix Information Geometry

Funds: The National Natural Science Foundation of China (61302193, 61401503)
  • 摘要:

    矩阵信息几何在雷达信号处理和目标检测中的应用是一个正在引起关注的研究方向。飞机尾流回波经过傅里叶变换后,其功率谱是展宽的,传统动目标检测(MTD)方法未能对展宽的功率谱进行有效积累。针对飞机尾流目标检测问题,基于矩阵信息几何理论,该文提出了一种矩阵恒虚警率(CFAR)检测方法,该方法中观测数据协方差矩阵构成一个矩阵流形,类比CFAR检测的思想,利用检测单元协方差矩阵与参考单元协方差矩阵均值间定义的距离作为检测统计量。最后利用噪声中仿真的尾流回波数据,分析了黎曼均值的迭代估计性能、尾流目标协方差矩阵与噪声协方差矩阵的测地线距离随信噪比的变化,比较了常规MTD检测方法和矩阵CFAR检测方法的检测性能。

     

  • 图  1  仿真的飞机尾流雷达回波

    Figure  1.  Simulation of the aircraft wake radar echo

    图  2  马可尼研究中心X波段雷达测量的功率谱[16]

    Figure  2.  The Power Spectrum measured by the X-band radar in Marconi Research Center

    图  3  基于信息几何的矩阵CFAR检测器框图

    Figure  3.  Block diagram of CA-CFAR detector based on information geometry

    图  4  脉冲个数为16时的自相关函数与功率谱

    Figure  4.  Autocorrelation function and power spectrum when the pulse number is 16

    图  5  协方差矩阵降低维数之前与之后的功率谱

    Figure  5.  The power spectrum before and after the covariance matrix reduces the dimension

    图  6  随SNR的变化测地线距离的变化

    Figure  6.  The variation of geodesic distance with the variation of SNR

    图  7  矩阵均值迭代估计性能

    Figure  7.  Iterative estimation performance of matrix mean

    图  8  有无尾流情况下检测统计量的统计直方图

    Figure  8.  The statistical histogram of detection statistics with and without the vortex target

    图  9  基于矩阵CFAR的尾流目标的检测概率

    Figure  9.  Detection probability of the vortex target based on matrix CFAR

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出版历程
  • 收稿日期:  2017-06-15
  • 修回日期:  2017-07-24
  • 网络出版日期:  2017-12-28

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