Coherent microwave radar can provide reasonable wave heights, while wave periods are always overestimated. The “group-line” in the wavenumber–frequency spectrum is a possible mechanism to interpret the overestimation, but the previous model cannot fully explain it. To address the issue, a new model integrating with the breaking and its evolution is proposed for microwave composite sea surface scattering. The upwind-grazing Doppler characteristics for coherent microwave radar under VV polarization are analyzed. The model is validated by comparing the results between the simulation and the radar observation. It explains the creation of “group-lines” in the wavenumber–frequency spectra and indicates that the short waves generated after breaking and their evolution should be the dominant reason for the overestimation of wave period using coherent microwave radar. The result can provide a theoretical basis for improving the performance of wave measurements with coherent microwave radar and for microwave ocean remote sensing.

Coherent microwave radar, which is a rapidly emerging tool to sense waves, usually utilizes the orbit velocities extracted from either temporal or spatial radar echoes. The distribution of energy in the wavenumber-frequency spectrum is changed by some nonlinear features, and correspondingly, this kind of method always provides a significantly overestimated wave period. To address this problem, a novel inversion algorithm, which utilizes the spatial and temporal returns collected with a recently developed coherent S-band radar, is proposed for retrieving wave parameters. A 2-D Fourier transform is applied to the spatial-temporal matrix of velocities to estimate the wavenumber-frequency spectrum. Then the wavenumber-frequency spectrum is integrated over the wavenumber domain to obtain the 1-D velocity spectrum. And the wave height spectrum is estimated from the 1-D velocity spectrum by the direct transform relationship between the 1-D velocity spectrum and the wave height spectrum. Later, significant wave heights and mean wave periods can be derived by the zeroth and first moments of the wave height spectra, respectively. The algorithm is validated using simulation and real data. An approximately four-day dataset collected with a shore-based coherent S-band radar deployed at Beishuang island during a typhoon period is reanalyzed and used to retrieve significant wave heights and mean wave periods. Comparisons between the measurements of radar and wave buoy are conducted, and radar-derived and buoy-measured wave parameters are in a reasonable agreement with a coherent coefficient over 0.9. The results indicate that the proposed method is effective for wave measurements using coherent S-band radar.

The peak wave direction is a crucial parameter to quantify the physical characteristics of the ocean waves. For shipboard coherent microwave radar, the radar-illuminated space changes with the movement of the ship, and this fact leads to an unsolved problem for wave direction estimation. To address the issue, an approach is proposed to estimate peak wave direction using shipboard coherent microwave radar. After estimating water particles’ radial velocity and obtaining the peak wave energy from the radar echoes received with antennas, the 180° ambiguity is removed by comparing the variance of the left and right boundaries of sea echoes in the range-Doppler spectrum. The approach is validated using the datasets collected with a shipboard coherent S-band wave radar and a wave buoy in the South China Sea in 2019. The comparison with the wave buoy data shows that the root-mean-square error (RMSE) of peak wave direction is 10.6°. This result indicates that the method can work effectively.

The amplitude and phase errors in array elements lead to uncertainties in the estimation of arrival angles (DOA), which, in turn, affect the accuracy of current measurements for high-frequency surface wave radar (HFSWR). To address this issue, this paper proposes a passive amplitude-phase self-calibration method for a wide-beam HFSWR system with a nonlinear array. This method utilizes the aggregation of the amplitude ratio among array elements to screen reception matrices of single DOA sources. Based on the differences in reception matrices, the amplitude error is calibrated. Moreover, the cost function is calculated using the multiple signal classification (MUSIC) algorithm, and the initial phase error is first obtained after triangular array dimensionality reduction. Then, the phase error is further calibrated through quadratic-form iterative optimization. This method has been validated through simulations and real measurements. An approximately 4-day dataset obtained via HFSWR is reanalyzed in this paper. After data calibration, the radar-estimated currents were in good agreement with the buoy-measured results, with a root mean square error (RMSE) as low as 0.06 m/s and a correlation coefficient (CC) of up to 0.88. The results indicate that this method is suitable for the amplitude and phase error calibration of nonlinear arrays in wide-beam HFSWR systems.