Remote Sensing (Jun 2023)

Modified Auto-Focusing Algorithm for High Squint Diving SAR Imaging Based on the Back-Projection Algorithm with Spectrum Alignment and Truncation

  • Anqi Gao,
  • Bing Sun,
  • Mengyuan Yan,
  • Chen Xue,
  • Jingwen Li

DOI
https://doi.org/10.3390/rs15122976
Journal volume & issue
Vol. 15, no. 12
p. 2976

Abstract

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The study focuses on addressing the image defocusing issue caused by motion errors in highly squinted Synthetic Aperture Radar (SAR). The traditional auto-focusing algorithm, Phase Gradient Autofocus (PGA), is not effective in this mode due to difficulties in estimating the phase gradient accurately from strong point targets. Two main reasons contribute to this problem. Firstly, the direction of the energy-distributed lines in the Point Spread Function (PSF) does not align with the image’s azimuth direction in highly squinted mode. Secondly, the wavenumber spectrum of high squint SAR images obtained using the Back-Projection Algorithm (BPA) varies spatially, causing aliasing in the azimuth spectrum of all targets. In this paper, a new auto-focusing method is proposed for highly squinted SAR imaging. The modifications to the BP imaging grids have been implemented to address the first problem, while a novel wavenumber spectrum shifting and truncation method is proposed to accurately extract the phase gradient and tackle the spatial variation issue. The feasibility of the proposed algorithm is verified through simulations with point targets and processing of real data. The evaluation of the image shows an average improvement of four times in PSLR (Peak-Sidelobe-to-Noise Ratio).

Keywords