Volume 11 Issue 4
Aug.  2022
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Article Navigation >  Journal of Radars  > 2022  >  11(4): 637-651
WANG Ruyi, ZHANG Hanqing, HAN Bing, et al. Multiangle SAR dataset construction of aircraft targets based on angle interpolation simulation[J]. Journal of Radars, 2022, 11(4): 637–651. doi: 10.12000/JR21193
Citation: WANG Ruyi, ZHANG Hanqing, HAN Bing, et al. Multiangle SAR dataset construction of aircraft targets based on angle interpolation simulation[J]. Journal of Radars, 2022, 11(4): 637–651. doi: 10.12000/JR21193
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Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation Simulation

doi: 10.12000/JR21193
  • 1.

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China

  • 2.

    Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Beijing 100190, China

  • 3.

    School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

Funds:  The National Natural Science Foundation of China (61431018)
More Information
  • Corresponding author: HAN Bing, han_bing@mail.ie.ac.cn
  • Received Date: 2021-11-27
  • Accepted Date: 2022-01-27
  • Rev Recd Date: 2022-01-26
    • Available Online: 2022-02-11
  • Publish Date: 2022-03-10
    Abstract
  • With the expansion of Synthetic Aperture Radar (SAR) applications and the development of SAR data acquisition technology, multiangle SAR datasets of various typical targets need to be constructed. Presently, a comprehensive multiangle SAR image dataset for aircraft targets is still lacking. This study explores a method of dataset construction based on the acquisition of actual data and intelligent simulation. Multiangle SAR images of aircraft targets are collected through flight tests, and the interpolation simulations of SAR images of specific angles are realized based on scattering analysis and self-attention generative adversarial network, which provide a new solution for dataset construction and expansion. Finally, under the assumption that some data are missing, the similarities between the simulated and actual images are evaluated using six evaluation indices, which verify the effectiveness of the proposed method.

     

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