One of the image pre-processing tasks in the Remote Sensing Satellite Ground Station is the Systematic Correction Processing which may remove almost all the distortions inside the scene. However

the location accuracy is still rough and may probably reach hundred meters or kilometers. A recursive algorithm based on the Kalman Filter rather than the Batch Processing Algorithm using a few number of Ground Control Points will be used to enhance the location accuracy. Moreover

the ephemeric data and the attitude data will also be updated. In a single scene processing

8 or 9 Control Points will be sufficient to reach the good result. In the continual multi-scene processing of a path

this algorithm may be propagated to predict the locations or the ephemeric and attitude data of the next scenes

in which the Control Point may be not available.In the section 2 of this paper

the recursive algorithm and the coefficients of the Transition Matrix and the Measurement Matrix in the Kalman Filter equations will be derived. The results of the simulation experiments including 3 Figures and 2 tables will be presented in the section 3. The section 4 has some discussions about the convergence and the advantages of this algorithm. Finally

6 references will be given for the convenience in the future discussions.