• DocumentCode
    13109
  • Title

    Time Variant RFI Suppression for SAR Using Iterative Adaptive Approach

  • Author

    Zhiling Liu ; Guisheng Liao ; Zhiwei Yang

  • Author_Institution
    State Key Lab. for Radar Signal Process., Xidian Univ., Xi´an, China
  • Volume
    10
  • Issue
    6
  • fYear
    2013
  • fDate
    Nov. 2013
  • Firstpage
    1424
  • Lastpage
    1428
  • Abstract
    Under the condition of time variant RFI, the limitation of training sample size causes great performance degradation of the conventional Radio Frequency Interference (RFI) suppression algorithm based on eigen-subspace projection (ESP) method. A novel RFI suppression method using iterative adaptive approach (IAA) and orthogonal subspace projection (OSP) method is proposed for synthetic aperture radar (SAR). Dispensing with parametric search and model order estimation, the proposed method estimates the RFI power spectrum adaptively and iteratively, utilizing few training samples and filtering the RFI based on the OSP method. Both the simulation and experimental results are provided to illustrate the performance of the proposed method.
  • Keywords
    atmospheric techniques; iterative methods; radiofrequency interference; remote sensing by radar; synthetic aperture radar; ESP method; IAA; OSP method; RFI filtering; RFI power spectrum; RFI suppression algorithm; SAR; conventional radio frequency interference suppression algorithm; eigen-subspace projection method; iterative adaptive approach; model order estimation; orthogonal subspace projection method; parametric search dispensing; performance degradation; synthetic aperture radar; time variant RFI suppression method; training sample size limitation; Iterative adaptive approach (IAA); Radio Frequency Interference (RFI) suppression; orthogonal subspace projection (OSP); synthetic aperture radar (SAR);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2013.2259575
  • Filename
    6547986