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FANG Yuxin, FAN Chenqing, MENG Junmin, et al. A quasi-linear inversion algorithm for retrieving sea surface elevation from gf-3 SAR images[J]. Journal of Radars, in press. doi: 10.12000/JR25146
Citation: FANG Yuxin, FAN Chenqing, MENG Junmin, et al. A quasi-linear inversion algorithm for retrieving sea surface elevation from gf-3 SAR images[J]. Journal of Radars, in press. doi: 10.12000/JR25146
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A Quasi-linear Inversion Algorithm for Retrieving Sea Surface Elevation from GF-3 SAR Images

DOI: 10.12000/JR25146 CSTR: 32380.14.JR25146
  • 1.

    China University of Petroleum (East China), Qingdao 266580, China

  • 2.

    First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China

Funds:  The National Natural Science Foundation of China (42206178)
More Information
  • Corresponding author: YAN Qiushuang, yanqiushuang@upc.edu.cn
  • Received Date: 2025-08-01
  • Rev Recd Date: 2026-02-01
    • Available Online: 2026-02-05
    Abstract
  • Sea surface elevation is crucial for characterizing individual waves, wave groups, and freak waves, offering an accurate representation of inhomogeneous sea states. This study presents a quasi-linear inversion strategy for retrieving sea surface elevation from GF-3 Synthetic Aperture Radar (SAR) images. The algorithm enables rapid inversion within 10 s per scene without the need for external data and effectively resolves range-traveling waves. Case studies conducted under three distinct sea states demonstrate its ability to extract maximum wave heights and identify wave groups. Additionally, inversion results from 2405 GF-3 wave mode SAR images following quality control are compared with ERA5 reanalysis spectra and altimeter data. The comparisons reveal that the retrieved Significant Wave Height (SWH) has a root mean square error of 0.48 m compared with ERA5 data. In low-to-moderate sea states, with significant wave heights below 3 m, the retrieved SWH shows strong consistency with ERA5 spectra and altimeter measurements. This algorithm serves as an effective tool for rapid monitoring and analysis of sea states using GF-3 SAR.

     

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