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<p>The research on ocean dynamics information plays a crucial role in understanding ocean phenomena, assessing marine environmental impacts, and guiding engineering designs. The Doppler information observed by radars reflects sea surface dynamics, to which ocean waves make important contributions. Low-incidence-angle real aperture radar (RAR) demonstrates great potential for independently observing vectorial Doppler information on the ocean surface. To systematically characterize and accurately estimate the wave-induced Doppler frequency shift (WVF) from low-incidence-angle RAR, this study conducts comprehensive influencing factor analysis and establishes sea-state-parameterized WVF models. First, a simulated WVF dataset is generated under a rotating low-incidence-angle RAR. The feature parameters of WVF are then determined by analysing contributing factors including wind waves, swells, and sea state parameters. Furthermore, two WVF models (WVF_KuP9 with 9 inputs and WVF_KuP4 with 4 inputs) are constructed by the Transformer encoder for different application scenarios. Both models achieve high accuracy for WVF estimation with root mean square errors (RMSE) of 1.874 Hz and 2.716 Hz, respectively. The reliability and superiority of the proposed models are validated through comparisons with the KaDOP, which is a typical geophysical model function (GMF). The findings in this paper advance the understanding of WVF characteristics and generation mechanisms. The proposed estimation models can provide reliable estimates, offering critical references for low-incidence-angle RAR applications such as ocean surface current retrieval.</p>

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Analysis and estimation of wave-induced Doppler shift from low-incidence-angle RAR based on sea state parameters

  • 期刊论文

  • 发表日期：

    2025年9月1日

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  • Jing Ye,
  • Yong Wan,
  • Chenqing Fan,
  • Yongshou Dai,
  • Yisen Yang,
  • Xiangying Miao

摘要

The research on ocean dynamics information plays a crucial role in understanding ocean phenomena, assessing marine environmental impacts, and guiding engineering designs. The Doppler information observed by radars reflects sea surface dynamics, to which ocean waves make important contributions. Low-incidence-angle real aperture radar (RAR) demonstrates great potential for independently observing vectorial Doppler information on the ocean surface. To systematically characterize and accurately estimate the wave-induced Doppler frequency shift (WVF) from low-incidence-angle RAR, this study conducts comprehensive influencing factor analysis and establishes sea-state-parameterized WVF models. First, a simulated WVF dataset is generated under a rotating low-incidence-angle RAR. The feature parameters of WVF are then determined by analysing contributing factors including wind waves, swells, and sea state parameters. Furthermore, two WVF models (WVF_KuP9 with 9 inputs and WVF_KuP4 with 4 inputs) are constructed by the Transformer encoder for different application scenarios. Both models achieve high accuracy for WVF estimation with root mean square errors (RMSE) of 1.874 Hz and 2.716 Hz, respectively. The reliability and superiority of the proposed models are validated through comparisons with the KaDOP, which is a typical geophysical model function (GMF). The findings in this paper advance the understanding of WVF characteristics and generation mechanisms. The proposed estimation models can provide reliable estimates, offering critical references for low-incidence-angle RAR applications such as ocean surface current retrieval.