Target classification using radar cross-section statistics of millimeter-wave scattering

• Aysu Coşkun ^[1] ; Sándor Bilicz ^[1]
  1. [1] Budapest University of Technology and Economics

     Budapest University of Technology and Economics

     Hungría

     
• Localización: Compel: International journal for computation and mathematics in electrical and electronic engineering, ISSN 0332-1649, Vol. 42, Nº Extra 5, 2023, págs. 1199-1211
• Idioma: inglés
• Enlaces
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• Resumen

  • Purpose This paper aims to discuss the classification of targets based on their radar cross-section (RCS). The wavelength, the dimensions of the targets and the distance from the antenna are in the order of 1 mm, 1 m and 10 m, respectively.

    Design/methodology/approach The near-field RCS is considered, and the physical optics approximation is used for its numerical calculation. To model real scenarios, the authors assume that the incident angle is a random variable within a narrow interval, and repeated observations of the RCS are made for its random realizations. Then, the histogram of the RCS is calculated from the samples. The authors use a nearest neighbor rule to classify conducting plates with different shapes based on their RCS histogram.

    Findings This setup is considered as a simple model of traffic road sign classification by millimeter-wavelength radar. The performance and limitations of the algorithm are demonstrated through a set of representative numerical examples.

    Originality/value The proposed method extends the existing tools by using near-field RCS histograms as target features to achieve a classification algorithm.