Volume 9 Issue 4
Aug.  2020
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Article Navigation >  Journal of Radars  > 2020  >  9(4): 608-621
Xu Zhen, Wang Robert, Li Ning, et al.. A novel approach to change detection in SAR images with CNN classification[J]. Journal of Radars, 2017, 6(5): 483–491. DOI: 10.12000/JR17075
Citation: WEN Gongjian, MA Conghui, DING Baiyuan, et al. SAR target physics interpretable recognition method based on three dimensional parametric electromagnetic part model[J]. Journal of Radars, 2020, 9(4): 608–621. doi: 10.12000/JR20099
shu

SAR Target Physics Interpretable Recognition Method Based on Three Dimensional Parametric Electromagnetic Part Model

DOI: 10.12000/JR20099
  • 1.

    National Key Laboratory of Science and Technology on Automatic Target Recognition, College of Electronic Science, National University of Defense Technology, Changsha 410073, China

  • 2.

    Space Engineering University, Beijing 101416, China

  • 3.

    Unit 96901 of People’s Liberation Army, Beijing 100094, China

Funds:  The National Minstries Foundation
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  • Corresponding author: WEN Gongjian, wengongjian@sina.com
  • Received Date: 2020-07-08
  • Rev Recd Date: 2020-08-19
    • Available Online: 2020-08-26
  • Publish Date: 2020-08-28
    Abstract
  • In this paper, a target’s electromagnetic scattering phenomenon is characterized by the Three Dimensional Parametric Electromagnetic Part Model (3D-PEPM) and a novel Synthetic Aperture Radar (SAR) target recognition method is proposed based on the model. The proposed method projects the individual scatterers in the 3D-PEPM to the 2D image plane to predict the location and appearance for each scatterer according to the radar parameters firstly. Then based on the prior information provided by the 3D-PEPM, the similarities between the 3D-PEPM and SAR data are evaluated. Finally, a view angle adjusting method is utilized to optimize the whole process to produce the final match score between the model and SAR data, and the recognition decision is made according to the match score. The proposed recognition method identifies clearly the correspondences of the scatterers between SAR data and 3D-PEPM and enjoys the explicit physical interpretability, so it can deal with SAR recognition problems under various extended operating conditions. Experiments on simulated data reveal the effectiveness of the proposed method.

     

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    • References(34)
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