Journal of Information Processing Systems

  • 제13권4호
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  • Pages.677-688
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  • 2017
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Time-Delay and Amplitude Modified BP Imaging Algorithm of Multiple Targets for UWB Through-the-Wall Radar Imaging

  • Zhang, Huamei (School of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications) ;
  • Li, Dongdong (School of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications) ;
  • Zhao, Jinlong (School of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications) ;
  • Wang, Haitao (School of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications)
  • 투고 : 2014.11.17
  • 심사 : 2015.12.08
  • 발행 : 2017.08.31
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초록

In order to solve the undetected probability of multiple targets in ultra-wideband (UWB) through-the-wall radar imaging (TWRI), a time-delay and amplitude modified back projection (BP) algorithm is proposed. The refraction point is found by Fermat's principle in the presence of a wall, and the time-delay is correctly compensated. On this basis, transmission loss of the electromagnetic wave, the absorption loss of the refraction wave, and the diffusion loss of the spherical wave are analyzed in detail. Amplitude compensation is deduced and tested on a model with a single-layer wall. The simulating results by finite difference time domain (FDTD) show that it is effective in increasing the scattering intensity of the targets behind the wall. Compensation for the diffusion loss in the spherical wave also plays a main role. Additionally, the two-layer wall model is simulated. Then, the calculating time and the imaging quality are compared between a single-layer wall model and a two-layer wall model. The results illustrate the performance of the time-delay and amplitude-modified BP algorithm with multiple targets and multiple-layer walls of UWB TWRI.

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참고문헌

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피인용 문헌

  1. Interaction Multipath in Through-the-Wall Radar Imaging Based on Compressive Sensing vol.18, pp.2, 2018, https://doi.org/10.3390/s18020549