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The Experimental Method of Sparse Measurement Based on Target’s Radar Cross Section Data

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  • Author(s): Wei, Ziran; Du, Wei; Huang, Yulu; Zhang, Ting
  • Source:
    Journal of Physics: Conference Series ; volume 2755, issue 1, page 012035 ; ISSN 1742-6588 1742-6596
  • Document Type:
    article in journal/newspaper
  • Language:
    unknown
  • Additional Information
    • Publication Information:
      IOP Publishing
    • Publication Date:
      2024
    • Abstract:
      In experiments of testing targets’ radar cross section (RCS), RCS is a measure of the target’s ability to reflect radar signals in the direction of radar reception. In order to take non blurry spatial-domain imaging of the target, sampling or measuring the target’s RCS signal must meet the Nyquist sampling theorem. However, RCS testing in microwave darkroom would produce a significant amount of sampling data, which requires a very long testing period. Based on the sparsity of spatial-domain RCS data after sparsifying transformation, a sparse projection measurement experimental method is designed for frequency-domain RCS data by sparsely sampling frequency-domain signals, fully utilizing the correlation between row and column information of two-dimensional frequency-domain data and the global sparsity of two-dimensional spatial-domain data. Finally, based on sparsely sampled data in the frequency-domain, the original RCS data is reconstructed by reconstruction algorithms, achieving the goal of effectively reducing RCS sampling data in RCS testing experiments.
    • Accession Number:
      10.1088/1742-6596/2755/1/012035
    • Accession Number:
      10.1088/1742-6596/2755/1/012035/pdf
    • Online Access:
      https://doi.org/10.1088/1742-6596/2755/1/012035
      https://iopscience.iop.org/article/10.1088/1742-6596/2755/1/012035
      https://iopscience.iop.org/article/10.1088/1742-6596/2755/1/012035/pdf
    • Rights:
      https://creativecommons.org/licenses/by/4.0/ ; https://iopscience.iop.org/info/page/text-and-data-mining
    • Accession Number:
      edsbas.4A6AAB78