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基于BiGRU-CNN的宽带电磁图像条带噪声去除方法研究

朱艳菊 赵梓寒 高志伟

朱艳菊, 赵梓寒, 高志伟. 基于BiGRU-CNN的宽带电磁图像条带噪声去除方法研究[J]. 强激光与粒子束, 2023, 35: 123002. doi: 10.11884/HPLPB202335.230238
引用本文: 朱艳菊, 赵梓寒, 高志伟. 基于BiGRU-CNN的宽带电磁图像条带噪声去除方法研究[J]. 强激光与粒子束, 2023, 35: 123002. doi: 10.11884/HPLPB202335.230238
Zhu Yanju, Zhao Zihan, Gao Zhiwei. Research on wideband electromagnetic image striping noise removal method based on BiGRU-CNN[J]. High Power Laser and Particle Beams, 2023, 35: 123002. doi: 10.11884/HPLPB202335.230238
Citation: Zhu Yanju, Zhao Zihan, Gao Zhiwei. Research on wideband electromagnetic image striping noise removal method based on BiGRU-CNN[J]. High Power Laser and Particle Beams, 2023, 35: 123002. doi: 10.11884/HPLPB202335.230238

基于BiGRU-CNN的宽带电磁图像条带噪声去除方法研究

doi: 10.11884/HPLPB202335.230238
基金项目: 河北省教育厅基金项目(CXY2023005);河北省重点研发计划基金项目(21350701D)
详细信息
    作者简介:

    朱艳菊,zhuyanju1309@163.com

    通讯作者:

    高志伟,gao_zhiwei@163.com

  • 中图分类号: TP391

Research on wideband electromagnetic image striping noise removal method based on BiGRU-CNN

  • 摘要: 电磁探测成像系统能够对电磁干扰源进行大范围、宽频带且快速的定位,系统主要由抛物反射面和多通道超宽频带信号采集系统组成。由于各个通道器件参数受限于制造工艺的影响不可能完全一致,探测不同频率干扰源的响应特性也不相同,导致获得的电磁图像中存在的条带噪声随干扰源的频率变化而呈现出不同的特征,严重地影响定位的精度。构建了双向门控循环单元(BiGRU)-卷积神经网络(CNN)模型,根据实测数据构建数据集作为模型的输入,BiGRU和CNN利用图像相邻行间的强相关性,从过去和未来的输入中广泛收集冗余信息,对条带噪声进行提取并对空间信息进行整合处理,利用数据之间的差值对这个过程进行循环迭代。通过大量的实验对模型进行验证,BiGRU-CNN方法与测试的经典方法相比更优,在垂直梯度能量方面降低了15.2%,在残差非均匀性方面降低了21.9%。
  • 图  1  BiGRU-CNN:整体网络架构图

    Figure  1.  BiGRU-CNN: overall network architecture

    图  2  不同方法在6 GHz下的去条带结果

    Figure  2.  De-striping results of various methods for 6 GHz

    图  3  不同方法在1 GHz下的去条带结果

    Figure  3.  De-striping results of various methods for 1 GHz

    图  4  不同方法在1 GHz、3 GHz和4 GHz下的去条带结果

    Figure  4.  De-striping results of various methods for 1 GHz, 3 GHz and 4 GHz

    图  5  各种方法处理后的结果评价指标比较

    Figure  5.  Comparison of evaluation metrics for the results obtained by various methods

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  • 被引次数: 0
出版历程
  • 收稿日期:  2023-07-29
  • 修回日期:  2023-10-25
  • 录用日期:  2023-10-25
  • 网络出版日期:  2023-11-04
  • 刊出日期:  2023-12-15

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