Based on the simulated signal, a numerical simulation method of synthetic aperture radar (SAR) imaging for time-varying sea surfaces is proposed, which is helpful to study the SAR imaging mechanism of time-varying sea surfaces so as to better extract ocean wave parameters from SAR images. Not only are the modulation of ocean waves, speckle noise, and temporal decorrelation of the small-scale waves considered, but the velocity bunching (VB) effect caused by the motion of large-scale waves is also effectively added to the simulation of the SAR echo signal. To verify the reliability of the simulation method, the simulated SAR images using the parameters of the RADARSAT-2 SAR, the corresponding wind wave information measured by an in-situ buoy, and the reanalysis wave spectra have been compared with the actual RADARSAT-2 SAR images. The comparisons demonstrate that the characteristics of simulated SAR images, such as the intensity distribution and the image spectra, are consistent with those of actual RADARSAT-2 SAR images. Based on the numerical simulation method proposed by us, SAR images of ocean waves for different marine environments and radar platform parameters are simulated. The imaging results indicate that the texture feature of the wind waves would be severely damaged due to the VB effect, while the texture of swells in the simulated SAR images may not be damaged or even becomes clearer. From the simulated SAR image spectrum, it can be found that the azimuth wavenumber is cut off when the VB effect is considered in the simulation process, and the azimuth cut-off wavelength increases with the range-to-velocity ratio.

Accurate acquisition of wave parameters is important for marine monitoring and target identification. Traditional methods are limited in sea state adaptability, real-time observation, and inversion accuracy. Tower-based non-scanning pulsed radar, as a low-cost near-shore method, provides all-weather, high temporal resolution observations without beam scanning. However, it yields two-dimensional range-pulse echo data blocks without azimuth information, making traditional wave spectrum inversion difficult to apply directly. To address this, we propose a wave parameter inversion method based on a ResNet–Transformer hybrid network. It takes sea clutter characteristics, radar parameters, and wind parameters as inputs, and uses 1D ResNet for local feature extraction and a Transformer encoder for cross-feature global interaction modeling, achieving simultaneous inversion of relative wave direction, mean wave period, and significant wave height. Experimental results on measured sea clutter samples demonstrate that the proposed method achieves high accuracy across all tasks. The RMSEs are 24.4 degrees, 0.5s, and 0.3 m for relative wave direction, mean wave period, and significant wave height. Experimental results on the measured dataset demonstrate that the model effectively captures the nonlinear mappings. These results support the feasibility of wave parameter estimation from tower-based non-scanning radar measurements under the evaluated conditions.