Image quality of Four Dimensional Cone-Beam Computer-Tomography (4DCBCT) is severely impaired by highly insufficient amount of projection data available for each phase. Therefore, making good use of limited projection data is crucial to solve this problem. Noticing that usually only a portion of the images is affected by motion, we separate the moving part (different between phases) of the images from the static part (identical among all phases) with the help of prior image reconstructed using all projection data. Then we update the moving part and the static part of images alternatively through solving minimization problems based on a global (use full projection data) and several local (use projection data for respective phase) linear systems. In the other word, we rebuild a large over-determined linear system for static part from the original under-determined systems and we reduce the number of unknowns in the original system for each phase as well. As a result, image quality for both static part and moving part are greatly improved and reliable 4D CBCT images are then reconstructed.