The microwave scatterometer is one of the most effective instruments in ocean remote sensing, which urges the need for some theoretical models to accurately estimate the scattering coefficient of the sea surface. For the simulation of the scattering from an ocean surface, the sea spectrum, or its inverse Fourier transform, autocorrelation function is essential. Currently, many sea spectral models have been proposed for describing sea waves. However, which spectrum should be adopted during electromagnetic (EM) computations? A systematic comparison of these models is needed to evaluate their accuracies. In this paper, we focus on numerical simulations of scattering from a rough sea surface in monostatic and bistatic configurations by using six different sea spectral models and the first-order small slope approximation (SSA-1). First, sea spectral models proposed by Elfouhaily et al., Hwang et al., Romeiser et al., Apel et al., Fung et al., and Pierson et al., are compared with each other from different points of view, e.g., the omnidirectional parts, the angular spreading functions, the autocorrelation functions, and the slope variances. We find that the spectra given by Elfouhaily and Hwang could reflect realistic wind sea waves more accurately. Then, the scattering coefficients are simulated in fully monostatic and bistatic configurations. Regarding the monostatic scattering, the results simulated using EM scattering models are compared with those obtained from the measured UAVSAR data in the L band and the empirical model CMOD5 in the C band. Comparisons are made for various incident angles, wind speeds, and wind directions. Meanwhile, special attention is paid to low to moderate incident angles. The comparisons show that, it is difficult to find one certain spectral model to simulate scattering coefficient accurately under all wind speeds or wind directions. Accurate estimations will be obtained using different methods according to different situations.

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.

The interferometric radar altimeter (IRA) is one of the main payloads of the “Guanlan” ocean science satellite proposed by the National Laboratory for Marine Science and Technology of China. To evaluate the effectiveness and accuracy of the IRA in retrieving the ocean dynamic parameters, such as sea surface height (SSH), ocean wave spectrum, and wind speed, two airborne IRA experiments were carried out at Qingdao Xiaomaidao (XMD) sea area on March 31, 2019, and Rizhao sea area on November 16, 2020. In the present work, wave-induced sea surface elevation (SSE) and its spectrum have been retrieved based on the interferograms acquired by the airborne IRA. To suppress the random phase noise, a mean filtering algorithm has been used in the multilook process of calculating the complex IRA images. The results show that the size of the filter window has a significant effect on the retrieved SSE. If the size of the filter window along THE range direction is too large, the flat earth would cause the spectral density of the retrieved ocean wave to be higher. In addition, the comparisons of the retrieved spectra with the buoy measurements demonstrate that the swell can be well-retrieved by IRA images at low sea-state conditions with significant wave height (SWH) less than 0.7 m. However, for wind wave, because of the effect of the velocity bunching along the azimuth direction, the wind wave spectrum can be extracted only when it propagates approximately along the ground-range direction of the IRA images.

Within the framework of the two-scale scattering model, Doppler shift and bandwidth of microwave scattering field from two-dimensional (2-D) sea surface have been simulated. And the comparisons of the simulated results with the Doppler anomaly measurements from Envisat ASAR demonstrate the rationality of the formulas proposed by us. Meanwhile, the influences of the tilt and the hydrodynamic modulations due to large-scale underlying waves on Doppler shift and bandwidth have also been discussed in detail. Numerical results show that the Doppler shifts for HH-and VV-polarizations are both observably affected by the tilt and the hydrodynamic modulations and the values of the predicted Doppler shifts are always larger than Bragg frequency. Because the radar scattering coefficient is more sensitive to sea surface slope in HH polarization than in VV, the predicted Doppler shifts in HH polarization are always somewhat larger than those in VV. Moreover, we also find that there is a remarkable difference between the Doppler shift predicted in upwind and downwind direction due to the hydrodynamic modulations. Relative to Doppler shift, bandwidth of Doppler spectrum is mainly affected by orbit velocity of large-scale waves and is insensitive to the modulations and radar polarizations.

The tilt modulation is one of the key factors affecting sea wave inversion accuracy based on some microwave sensors such as SAR, microwave spectrometer, and so on. Up to now, the traditional tilt modulation-transfer functions (MTFs) based on the Bragg scattering model and Phillips spectrum have been used in the sea wave spectrum retrieval algorithm for microwave sensors operating at medium incident angles. The traditional tilt MTFs are only related to radar polarization and incident angle, but not affected by wind speed and wind direction. However, the values of the tilt MTFs evaluated on the basis of the C-band empirical geophysical model function (GMF) CMOD5.na demonstrate that wind speed and wind direction also have significant effects on the tilt MTFs. In addition, the comparisons show that the values of the traditional tilt MTFs for both HH (horizontal) and VV (vertical) polarization cases are obviously smaller, which indicates that the traditional tilt MTFs would underestimate the influence of the local incident angle change on the scattering fields. On the other hand, the difference between the horizontal and the vertical polarization tilt MTFs, however, is overestimated by the traditional tilt MTFs. Finally, by fitting the data evaluated based on the C-band empirical GMF, we propose new tilt MTFs, which can overcome the shortcomings of the traditional tilt MTFs.