Xiaoliang Chu

The wind and wave-induced Doppler shift (WDS) significantly affects the accuracy of ocean surface current fields retrieved from synthetic aperture radar (SAR). Understanding how different factors affect WDS is therefore essential for improving current inversion accuracy. Existing studies have predominantly focused on single-band WDS, mainly in the C-band, while investigations across other radar bands remain limited. In this study, we simulate the dynamic ocean surface height field and velocity field, and the radar backscatter from the ocean surface that includes the effect of breaking waves. Based on the Doppler shift theory of ocean surface motion proposed by Chapron, we develop a WDS simulation model with potential applicability to multiple radar bands. The performance of the model is verified by comparing its results with those from the CDOP, KaDOP and KuMOD models. The correlation coefficient between the proposed model and the CDOP model reaches 0.97, with mean deviation (MD), mean absolute error (MAE), and root-mean-square error (RMSE) not exceeding −2.07 Hz, 3.35 Hz, and 4.49 Hz, respectively. For comparisons with the KaDOP model, the correlation coefficient is 0.93, and the MD, MAE, and RMSE are within −21.23 Hz, 42.37 Hz, and 52.20 Hz. For comparisons with the KuMOD model, the correlation coefficient is 0.98, and the MD, MAE, and RMSE are within −2.60 Hz, 7.13 Hz, and 9.08 Hz. These results demonstrate that the proposed model can effectively predict the WDS for both C-, Ka-, and Ku-band radar returns. Furthermore, we investigate the impacts of radar parameters, including frequency band, polarization, and incidence angle, as well as wind field forcing on WDS, showing the model’s applicability across multiple radar bands. Finally, the proposed model is applied to current retrieval using Sentinel-1 ocean (OCN) data, and the inversion accuracy is assessed against collocated high-frequency (HF) radar observations. The MD, MAE, and RMSE of the current retrieval using the proposed model are −0.04 m/s, 0.26 m/s, and 0.32 m/s, which are close to those from the CDOP-based retrieval (MD, MAE, and RMSE of −0.02 m/s, 0.25 m/s, and 0.30 m/s). These results demonstrate that the proposed model performs well in ocean surface current inversion and shows potential for further application to ocean current retrieval based on radar data across different frequency bands.

We develop an experiment to obtain the sea state parameters using HF surface-wave radar (HFSWR) and the in situ instruments. The wind direction is extracted, and the results are compared with the in situ data. In addition, the wind direction ambiguity was eliminated by the maximum likelihood (ML) method. The results from the radar are compared with the in situ data, which show that the wind direction can be obtained from the HFHSSWR, although the accuracy is not as good as the HFSWR. The error may be affected by the HFHSSWR system. In addition, the low wind speeds during the experiment can produce large error. The ML method is more suitable for the elimination of the wind direction ambiguity for the experiment data. In the calculation, we find the results retrieved by the ML method would be worse when the spreading parameter β is not fixed and is selected by the ML method. Whether ML method is effective for the HFHSSWR needs more experimental data for examination. In addition, the use of two radar sites to eliminate the wind direction ambiguity for the HFHSSWR is seen as reliable.

In this study, an algorithm is presented to eliminate the ambiguity of the wind direction from the monostatic radar. The true wind direction can be obtained by comparing three angles that reflect the differences between wind direction and three adjacent radar beams. The correlation coefficient and the root‐mean‐square (RMS) error between the inversion data and the anemometer data are 0.67 and 49.8°, respectively. When the data whose wind speed is greater than the threshold 4.67 m/s are used, the correlation coefficient and the RMS error are 0.93 and 24.6°. Therefore, the effect of the wind speed threshold on the radar measurements should be put into consideration in the data processing. The results make clear that the algorithm can remove the ambiguity of the wind direction effectively, and authors can utilise the algorithm to estimate the wind direction.

The Wen's wave spectrum model is adopted to describe the rough sea surface, and the relation between wind and ocean waves using sea wave spectrum theory is derived. The improved discrete mixed Fourier transform algorithm and the modified rader scattering coefficient model are used to calculate radio propagation loss and radar cross section respectively. On this basis, the influence of wind waves on radar echoes in the environment of atmosphere ducts is analysed by using numerical calculations. The results show that the influences of wind on propagation loss at different heights are different; wich respect to the propagation loss, rader scattering coefficient influenced by waves of factors is large, which results in large change in the radar echo power.