3D Gaussian splash substitutes traditional point clouds with Gaussian bases, utilizing their smooth characteristics. While maintaining data accuracy, it effectively processes and visualizes scattered data in three-dimensional space, achieving a more continuous and natural image rendering effects. This has made significant achievements in the field of optical imaging and has become a recent research hotspot. In the application domain of SAR imaging, the attribute scattering center model is often used as the basis for images. In this paper, an attempt is made to use Gaussian bases instead of attribute scattering center model. Through experimental comparisons, the performance of Gaussian bases, the attribute scattering center model, and the commonly used simplified attribute scattering center model in SAR image reconstruction tasks are analyzed. The results show that the Gaussian basis method offers superior image reconstruction quality, with significantly better performance in terms of speed and stability compared to the attribute scattering center model. These findings provide new insights for feature and target information extraction in SAR images.