• Medientyp: E-Artikel
  • Titel: Three-Dimensional Near-Field to Far-Field Transformation for Radar Cross Section Estimation of Elongated Targets via Subdimensional Hybrid Conversion
  • Beteiligte: Kim, Jeong-Kyu; Tae, Hyun-Sung; Seo, Min-Gyeong; Park, Ho-Min
  • Erschienen: Korean Institute of Electromagnetic Engineering and Science, 2022
  • Erschienen in: Journal of Electromagnetic Engineering and Science
  • Sprache: Englisch
  • DOI: 10.26866/jees.2022.4.r.116
  • ISSN: 2671-7255; 2671-7263
  • Schlagwörter: Electrical and Electronic Engineering ; Computer Networks and Communications ; Instrumentation ; Radiation
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  • Beschreibung: <jats:p>Image-based (IB) near-field to far-field transformation (NFFFT) is a useful method for the valid prediction of radar cross sections (RCSs) from short-range monostatic measurements. Many previous studies on the IB NFFFT algorithm have been limited to two-dimensional (2D) measurement cases. In this work, a subdimensional hybrid conversion approach is proposed as a relevant three-dimensional (3D) NFFFT method consisting of the following procedures. First, the spherical-wave information collected through 3D scanning is converted to a cylindrical waveform by applying the 2D circular NFFFT (CNFFFT) method to every vertical subplane (&lt;i&gt;r-θ&lt;/i&gt; plane). Then, a horizontal far-field radar image on the &lt;i&gt;x-y&lt;/i&gt; plane and an RCS pattern are extracted through direct integration of a 2D focusing operator modified to compensate for a magnitude error through distance approximation during the CNFFFT procedure. The results of a comparative study with direct integration of a 3D focusing operator are presented to show the validity and performance of the proposed method.</jats:p>
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