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Analysis of Scattering Characteristics Based on Crank-Nicolson Direct-Splitting Algorithm for Remote Sensing Problems

  • Shida Gao
  • , Hua Jiang
  • , Yong Fan
  • , Yongjun Xie
  • , Haolin Jiang
  • , Peiyu Wu*
  • *Corresponding author for this work
  • China Aerospace Science and Technology Corporation
  • Beijing Engineering Research Center of EMC and Antenna Test Technology
  • Nanjing University of Information Science & Technology

Research output: Contribution to journalArticlepeer-review

Abstract

In remote sensing problems, broadband scattering investigation becomes increasingly important than ever before. The scattering characteristic changes significantly with the variation of range. Thus, the conventional evaluation method becomes invalid in many situations. Meanwhile, an efficient method for the simulation of electromagnetic wave propagation in electrically large remote sensing problem is also an urgently demanding. In order to alleviate such problems, an alternative Crank-Nicolson Direct-Splitting algorithm is proposed in open regions. To infinite extension of the computational domain, convolutional perfectly match layer with higher order formulation is proposed not only to further enhance the absorption at low-frequency band but also to decrease the reflections during the entire time domain simulation. Efficient method is proposed for scattering characteristics evaluation which ranges from near-field to far-field. Radar remote sensing Problems including ground penetrating radar and early warning radar are introduced to demonstrate the effectiveness of the algorithm. Through the results, it can be concluded that the proposed algorithm shows considerable performance in the simulation of remote sensing problems.

Original languageEnglish
Pages (from-to)573-586
Number of pages14
JournalIEEE Open Journal of Antennas and Propagation
Volume5
Issue number3
DOIs
StatePublished - 1 Jun 2024

Keywords

  • Crank-Nicolson direct-splitting
  • finite-difference time-domain (FDTD)
  • near-field scattering characteristics
  • perfectly match layer (PML)
  • remote sensing

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