Synthetic aperture interferometric radiometer (SAIR) is a powerful sensors for high-resolution imaging. However, because of the observation errors and small number of visibility sampling points, the accuracy of reconstructed images is usually low. To overcome this deficiency, a novel super-resolution imaging (SrI) method based on super-resolution reconstruction idea is proposed in this paper. In SrI method, sparse visibility functions are first measured at different observation locations. Then the sparse visibility functions are utilized to simultaneously construct the fusion visibility function and the fusion imaging model. Finally, the high-resolution image is reconstructed by solving the sparse optimization of fusion imaging model. The simulation results demonstrate that the proposed SrI method has higher reconstruction accuracy and can improve the imaging quality of SAIR effectively.