Interferometry Synthetic Aperture Radar (InSAR) is capable of accurately capturing the minute deformation of the surface, particularly the alteration of the edge of the subsidence funnel. Nevertheless, with regard to the precipitated land subsidence in the mining area, the interference signal will lose coherence on account of the excessive sedimentation gradient, leading to heightened uncertainty of the monitoring results and making it arduous to accurately reflect the actual settlement circumstances. To address this issue, a novel method for surface settlement detection is proposed by us. This method combines the advantages of SBAS InSAR technology with probability integration method, enhancing its precision in detecting complex deformation patterns. The method uses probability integral method to invert the center of the basin and integrates with the settlement monitoring results obtained by SBAS to obtain the complete surface subsidence results of the mining area. To verify its effectiveness, we used SBAS InSAR technology to perform time series processing on 49 Sentinel-1A data images from Yuncheng coal mine in Heze City, Shandong Province, and the land subsidence rate and cumulative deformation subsidence in the study area were obtained. The feasibility and accuracy of the method are verified by using the results from December 2016 to June 2018 and the measured data of working face leveling. The results show that the surface subsidence of Yuncheng coal mine is relatively serious. Two subsidence funnels appeared during the monitoring period, and the amount of ground subsidence increased year by year. The maximum subsidence monitored was 2477 mm, and the maximum subsidence rate reached -194.09 mm/a. The fused results of SBAS-InSAR and the probability integration model had a maximum relative error of settlement of 3.7% and 5.2% in terms of strike and dip compared to the leveling data. This method provided more accurate and reliable subsidence information than the single SBAS-InSAR processing, significantly improving the reliability of mining subsidence monitoring and offering a new application reference for mining area subsidence monitoring.