## 3 Results and Analysis
### Accuracy Assessment of the Multiview Ocean Wave SAR Synchronization Data  
In Sections 3.1 and 3.2, we showed the results of the networked SAR imaging simulation, but the feasibility of the data is not clear. In this section, we would evaluate the accuracy of the data to show that the data are usable. For simulated SAR imaging data, the backscatter coefficients are equivalent to the input parameters, and the echo signals are generated in the middle of the simulation process. With this in mind, we only evaluate the accuracy of the backscatter coefficients and the ocean surface SAR images.  
The value of the backscatter coefficients is related to the roughness of the ocean surface, while the surface roughness is determined by the wind speed. Therefore, wind speed is the key factor affecting the backscatter coefficients of the ocean surface. When the incident angle of the SAR beam is fixed with the angle of wind direction, the backscatter coefficient increases with the increase of wind speed, however, the growth rate of backscatter coefficient decreases [34]. As can be seen from Figure 4, when the wind speed increases, the backscatter coefficients increase indeed. The simulated results are in agreement with the theory, indicating that the accuracy of the simulated backscattering coefficients is relatively high. As initial input parameters, the accuracy of backscatter coefficients can also be verified by the simulated ocean wave data.  
In order to analyze the accuracy of the simulated ocean wave data, we used the Max Plank Institute (MPI) algorithm [35] to invert the wave spectrum of ocean wave data. The MPI algorithm is derived describing the mapping of a 2D ocean wave spectrum into a SAR image spectrum. The inversion results of the ocean wave data observed by SAR-1 are shown in the figures below.  
As can be seen from the figures, the direction of wave propagation is consistent with the initial input angle. The first guess wave spectrum is in line with the magnitude and shape of the fit wave spectrum. The fit SAR spectrum is also consistent with the magnitude of the fit wave spectrum. The above phenomenon shows that the wave spectrum inverted from the ocean wave data is ideal.  
For SAR-2, the wave propagation direction is the same as the SAR-1, which is also 45\({}^{\circ}\). The orbital angle of SAR-2 and SAR-1 is 30\({}^{\circ}\), and it can be calculated that the angle between the wave propagation direction and the range direction of SAR-2 is 75\({}^{\circ}\). The inversion results of ocean wave data observed by SAR-2 are shown in the figures below.  
For SAR-3, the wave propagation direction is also 45\({}^{\circ}\). The orbital angle of SAR-3 and SAR-1 is \(-\)50\({}^{\circ}\), and it can be calculated that the angle between the wave propagation direction and the range direction of SAR-3 is 5\({}^{\circ}\). The inversion results of ocean wave data observed by SAR-3 are shown in the figures below.  
Figure 7: Networked SAR satellite observations of the same sea area.  
As can be seen from Figures 11-13, the SAR wave synchronization data obtained by networked SAR satellites can invert the fit wave spectrum and the fit SAR spectrum, ideally. In this way, it can be proved that the accuracy of the SAR imaging simulation data is relatively high.