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基于检测-跟踪联动的紧凑型高频地波雷达弱目标自适应检测方法

孙伟峰 李小彤 纪永刚 戴永寿

孙伟峰, 李小彤, 纪永刚, 戴永寿. 基于检测-跟踪联动的紧凑型高频地波雷达弱目标自适应检测方法[J]. 电子与信息学报, 2023, 45(8): 2955-2964. doi: 10.11999/JEIT220811
引用本文: 孙伟峰, 李小彤, 纪永刚, 戴永寿. 基于检测-跟踪联动的紧凑型高频地波雷达弱目标自适应检测方法[J]. 电子与信息学报, 2023, 45(8): 2955-2964. doi: 10.11999/JEIT220811
SUN Weifeng, LI Xiaotong, JI Yonggang, DAI Yongshou. An Adaptive Weak Target Detection Method Using Joint Detection and Tracking for Compact High Frequency Surface Ware Radar[J]. Journal of Electronics & Information Technology, 2023, 45(8): 2955-2964. doi: 10.11999/JEIT220811
Citation: SUN Weifeng, LI Xiaotong, JI Yonggang, DAI Yongshou. An Adaptive Weak Target Detection Method Using Joint Detection and Tracking for Compact High Frequency Surface Ware Radar[J]. Journal of Electronics & Information Technology, 2023, 45(8): 2955-2964. doi: 10.11999/JEIT220811

基于检测-跟踪联动的紧凑型高频地波雷达弱目标自适应检测方法

doi: 10.11999/JEIT220811
基金项目: 国家自然科学基金(62071493, 61831010)
详细信息
    作者简介:

    孙伟峰:男,副教授,研究方向为紧凑型高频地波雷达目标探测与跟踪、图像处理等

    李小彤:女,硕士生,研究方向为紧凑型高频地波雷达目标探测与跟踪

    纪永刚:男,教授,研究方向为紧凑型高频地波雷达目标探测、海上目标多手段融合探测、新体制超视距雷达海态监测等

    戴永寿:男,教授,研究方向为地震信号处理、海洋环境监测等

    通讯作者:

    孙伟峰 sunwf@upc.edu.cn

  • 中图分类号: TN953

An Adaptive Weak Target Detection Method Using Joint Detection and Tracking for Compact High Frequency Surface Ware Radar

Funds: The National Natural Science Foundation of China (62071493, 61831010)
  • 摘要: 紧凑型地波雷达发射功率低、回波信噪比低,目标检测难度大,在目标跟踪时由于目标漏检经常出现航迹断裂。为了提升其目标检测性能,提出了一种基于检测-跟踪联动的弱目标自适应检测方法。当跟踪器检测到目标航迹无法关联到新点迹时,将当前目标预测状态反馈至检测器;检测器在距离-多普勒谱上建立局部检测波门,采用二元假设检验法感知波门内的检测背景,根据不同的检测背景选取适用的检测门限调整方法,降低恒虚警检测的门限,判定是否有弱目标被检出。若能够检出目标,对其进行测向后将新点迹发送至跟踪器进行处理。利用实测数据开展了目标检测与跟踪实验,结果表明:与先检测后跟踪方法相比,该方法得到的目标航迹时长增加了29.76%,平均延长了19.25 min。
  • 图  1  先检测后跟踪方法流程图

    图  2  基于检测-跟踪联动的弱目标自适应检测方法示意图

    图  3  地波雷达目标跟踪过程示意图

    图  4  目标航迹个例

    图  5  目标个例1的跟踪结果对比及检测门限自适应调整过程

    图  6  目标个例2跟踪结果对比

    图  7  目标个例3跟踪结果对比

    图  8  目标个例4跟踪结果对比

    图  9  检测门限调整方法选取不当时的跟踪结果对比

    图  10  本文方法与UKF+JPDA方法的跟踪结果对比

    算法1 基于梯度下降法的检测门限调整方法步骤
     输入:门限因子的初值${T_0}$与终值$\hat T$、梯度下降步长$\alpha $、参考单元
     个数$N$、$k + 1$时刻的R-D谱数据、初始虚警率$ {P_{{{\text{f}}_0}}} $、方位角预测
     值$\theta _{k + 1}^{\text{p}}$及点迹-航迹关联波门的方位角阈值${ {\boldsymbol{\varTheta } }_{ {\text{th} } } }$
     输出:新检出目标点迹${\boldsymbol{x}}_{k + 1}^{\text{m}} = {\left[ {v_{k + 1}^{\text{m}},r_{k + 1}^{\text{m}},\theta _{k + 1}^{\text{m}}} \right]^{\text{T}}}$(上角标
     ${\text{m}}$表示量测状态)
     算法步骤:
     (1) 初始化迭代次数$n = 0$,$T = {T_0}$;
     (2) 根据式(8)计算函数$T$在${P_{{{\text{f}}_n}}}$处的梯度$\nabla T$:
          $\nabla T = \dfrac{ {\partial T} }{ {\partial {P_{ { {\text{f} }_n} } } }} = - {P_{ { {\text{f} }_n} } }^{\left( { - \frac{1}{N} - 1} \right)}$      (8)
     (3) 根据式(9)求得当前$T$的下降距离$d$:
              $ d = - \alpha \times \nabla T $           (9)
     (4) $n = n + 1$,将门限因子$T$更新为$T = T - d$,并根据式(2)计
     算$T$对应的虚警率${P_{{{\text{f}}_n}}}$;
     (5) 判断是否满足$T \le \hat T$。若满足,则终止算法;若未满足,则
     转入步骤(6);
     (6) 采用门限因子$T$对应的检测门限在当前R-D谱数据的局部检
     测波门内进行目标检测,若无新目标检出,则转入步骤(2);若
     有新目标检出,则转入步骤(7);
     (7) 对新检出的目标进行方位角估计,判断方位角$\theta _{k + 1}^{\text{m}}$是否满足
     $\left| {\theta _{k + 1}^{\text{m} } - \theta _{k + 1}^{\text{p} } } \right| < { {\boldsymbol{\varTheta } }_{ {\text{th} } } }$,若满足,则认为该目标为与断裂航迹匹
     配的漏检目标,并输出新检出的目标点迹
     ${\boldsymbol{x}}_{k + 1}^{\text{m}} = {\left[ {v_{k + 1}^{\text{m}},r_{k + 1}^{\text{m}},\theta _{k + 1}^{\text{m}}} \right]^{\text{T}}}$;若不满足,则转入步骤(2)。
    下载: 导出CSV

    表  1  基于实测数据的航迹跟踪时长对比(min)

    方法目标个例1目标个例2目标个例3目标个例4
    CMKF+NNDA方法785773100
    本文方法9110285107
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-06-20
  • 修回日期:  2023-02-06
  • 网络出版日期:  2023-02-08
  • 刊出日期:  2023-08-21

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