Volume 10 Issue 2
Apr.  2021
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Article Navigation >  Journal of Radars  > 2021  >  10(2): 296-303
NIAN Yiheng, ZHOU Ningning, ZHU Shitao, et al. Differential coincidence imaging based on randomly modulated metamaterial surface[J]. Journal of Radars, 2021, 10(2): 296–303. doi: 10.12000/JR20136
Citation: NIAN Yiheng, ZHOU Ningning, ZHU Shitao, et al. Differential coincidence imaging based on randomly modulated metamaterial surface[J]. Journal of Radars, 2021, 10(2): 296–303. doi: 10.12000/JR20136
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Differential Coincidence Imaging Based on a Randomly Modulated Metamaterial Surface

DOI: 10.12000/JR20136 CSTR: 32380.14.JR20136

  • School of Information and Communication Engineering, Xi’an Jiaotong University, Key Laboratory of Multifunctional Materials and Structures, Ministry of Education, Xi’an 710049, China

Funds:  The National Natural Science Foundation of China (62071371), The Key Laboratory of High-Speed Circuit Design and EMC Ministry of Education (LHJJ/2020-04), The National Key Lab of Radar Signal Processing
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  • Corresponding author: ZHU Shitao, shitaozhu@xjtu.edu.cn
  • Received Date: 2020-11-01
  • Rev Recd Date: 2021-01-11
    • Available Online: 2021-01-29
  • Publish Date: 2021-04-28
    Abstract
  • The coincidence imaging system based on a metamaterial surface solves the problem of low detection efficiency. Nevertheless, the number of effective imaging points is limited owing to the lack of the detection mode. To solve this problem, based on the first-order statistical characteristics of a reference-radiation field, a correlation-imaging signal model based on a randomly-modulated metamaterial surface is established, and the imaging error is analyzed. This study presents a robust coincidence imaging called Differential Coincidence Imaging (DCI), which uses the differential of different modes to form a new detection mode. The DCI analysis proves that it can improve the imaging quality. At the same time, the resolution of a special DCI method called the Gradient Coincidence Imaging (GCI) method is analyzed, which effectively improves the ability of extracting a target edge. With the special design of a metasurface unit, the edge information of a target can be extracted directly in the imaging process without obtaining an image. Finally, the proposed methods are validated through simulation experiments.

     

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