IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2023)

Performance Analysis of Wavenumber Domain Algorithms for Highly Squinted SAR

  • Xing Chen,
  • Zhenyu Hou,
  • Zhen Dong,
  • Zhihua He

DOI
https://doi.org/10.1109/JSTARS.2023.3237552
Journal volume & issue
Vol. 16
pp. 1563 – 1575

Abstract

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Wavenumber domain algorithms have unique advantages in processing highly squinted synthetic aperture radar data. This article studies the performance of three commonly used wavenumber domain algorithms including the classical wavenumber domain (CWD) algorithm, extended wavenumber domain (EWD) algorithm, and squint wavenumber domain (SWD) algorithm. First, the wavenumber domain signal expression under the zero-Doppler and acquisition-Doppler reference geometries are both derived. Second, the internal relationship between three wavenumber domain algorithms is analyzed. A new interpretation of the relationship between the three algorithms and an interpolation strategy are given. The analysis not only provides a deeper understanding of the three algorithms, but also provides a basis for comparing them. Then, the performance of the three wavenumber domain algorithms is evaluated from the perspectives of computational complexity, image quality, and geometric position through theoretical analysis and simulation experiments. Aiming at the problem that the range and azimuth profiles are not orthogonal, a method to calculate resolution and extract profile is proposed. The results show that all three algorithms can obtain a well-focused images if full-resolution interpolation is performed, and the computational complexities of CWD and SWD are less than that of EWD.

Keywords