Based on the SAR satellite imagery with short revisit periods, this paper proposes a novel SBASInSAR time series analysis technique for efficient and continuous monitoring of surface deformation in the study area. First, standard interferometric processing is carryed out with the existing SAR image set in the study area to obtain the interference map. Then the atmospheric and orbital errors are removed, and the traditional SBAS (small baseline subset) method is used to obtain the surface deformation. On this basis, when a new SAR image is added, the progressive SBAS is adopted to invert the surface deformation at the new moment. The progressive SBAS method integrates the idea of sequential adjustment based on the obtained results derived from existing data set, and combines the newly acquired data to implement incremental calculations, finally achieves the equivalent effect of overall processing. Compared with the traditional SBAS method which needs to resolve all the calculations every time when a new image is added, the progressive SBAS method can reduce redundant operations and improve computing efficiency. The experiment proves that based on the Sentinel-1 satellite SAR data acquired in the Yellow River Delta from May 2018 to August 2016, the surface deformations retrieved by the progressive SBAS method are almost the same as the results of the measured ground level. The correlation coefficient (R) is 0.82, and the difference between the ground deformation rate and the traditional SBAS method is within 1 mm/a. The solution time is shortened by about 40%, and the ground deformation can be efficiently and continuously monitored.