## 4 Discussion  
In Section 3.1, we analyzed the results of each step of the imaging simulation in detail. The results showed that the ocean surface undulations at different wind speeds are different, reflecting the influence of the wind speed on the ocean surface undulations and conforming to real ocean characteristics, which also proves the effectiveness of the imaging simulation results. The calculation of the echo signals is a difficult problem in the whole SAR imaging simulation process. At present, the echo simulation of point targets is mostly realized in the research work, while the echo simulation of area targets such as the ocean surface is seldom realized. The ocean surface SAR echo simulation in this paper can provide a reference for research work in related fields. During simulation, discretization of the constructed ocean surface was considered to be a combination of a series of discrete points. Using the discrete ocean surface as the background field, the slope at each point of the ocean surface was calculated. The backscattering coefficients of all points on the ocean surface were calculated according to the slope, and the calculation method had a high precision. Range migration bending is clearly related to the range and azimuth sampling points. The larger the slant distance or the wider the scanning beam is, the wider the range of the sampling points. The longer the synthetic aperture time or the higher the pulse repetition frequency is, the more azimuth sampling points there are. The larger the number of sampling points is, the more notable the range migration is, and the greater the calculation amount is. In the case that the accuracy of the data is not high, range migration correction can be omitted to reduce the amount of calculation. In Section 3.2, we analyzed the simulation of networked satellites and multiview ocean wave SAR synchronization data in detail. The results showed that the difficulty of simulating was to ensure that the orbits of the three SARs were at an angle based on the orbital parameters of the SARs. After the simulation of the networked satellites, the most important and innovative part of this paper is the generation of the multiview SAR wave synchronization data. The key to this process is that the three SARs can simultaneously observe the same sea area. The working mode of the SAR can be regarded as the stop-go-stop model; therefore, we can make the electromagnetic pulse emission times of the three SARs the same to ensure simultaneous observations. According to Section 2.2, we can summarize the specific steps of the Monte Carlo method. First, the 2D Gaussian white noise is simulated, and then the noise is linearly filtered by the 2D wave spectrum to obtain the FFT of the ocean surface height fluctuation function, and the ocean surface height fluctuation function can be obtained by IFFT. No time factor was added during the ocean simulation, so the Monte Carlo method is used to simulate the freezing ocean surface. Networked SAR satellites can acquire synchronized observation data at the same time and the same place during imaging simulation. Figures 8-10 demonstrate that the ocean surface SAR images and the backscatter coefficient images are horizontally symmetric. This result is because the RD algorithm performs FFTs and IFFTs on the azimuths and ranges of the echo signals, respectively. That's why the observed SAR spectrum is flipped horizontally. When the SAR images are horizontally flipped, the wave stripe trends of the SAR images are basically the same as the stripe trends of the backscattering coefficient figures, but the degrees of blur are different. This situation is consistent with real ocean physical characteristics. It can also be seen that for the same sea area, the results observed by the SAR for different flight directions are different, and the clarity of the wave stripes is related to the flight direction of the SAR.