Interference Mitigation for Synthetic Aperture Radar Based on Deep Residual Network
作者: Weiwei FanFeng ZhouMingliang TaoXueru BaiPengshuai RongShuang YangTian Tian
刊名: Remote Sensing, 2019, Vol.11 (14)
来源数据库: Directory of Open Access Journals
DOI: 10.3390/rs11141654
关键词: Radio Frequency Interference (RFI)Interference mitigationSynthetic Aperture Radar (SAR)Deep residual network (ResNet)
原始语种摘要: Radio Frequency Interference (RFI) is a key issue for Synthetic Aperture Radar (SAR) because it can seriously degrade the imaging quality, leading to the misinterpretation of the target scattering characteristics and hindering the subsequent image analysis. To address this issue, we present a narrow-band interference (NBI) and wide-band interference (WBI) mitigation algorithm based on deep residual network (ResNet). First, the short-time Fourier transform (STFT) is used to characterize the interference-corrupted echo in the time−frequency domain. Then, the interference detection model is built by a classical deep convolutional neural network (DCNN) framework to identify whether there is an interference component in the echo. Furthermore, the time−frequency feature of the target signal is...
全文获取路径: DOAJ  (合作)

  • network 网络
  • reconstructed 修]重构[建
  • interference 干涉
  • filtering 滤波
  • algorithm 算法
  • mitigation 水的软化
  • feature 结构元件
  • effectiveness 有效性
  • transform 变换
  • SAR Safe Address Register