The study selected Qingdao Jiaozhou Bay Bridge as the study object and gathered information on deep mining based on InSAR deformation data acquired from Jan 2014 to May 2016. Two new deformation models with seasonal variation and temperature variation were first introduced in data analysis. These two models and the traditional linear model were utilized to decompose the deformation evolution data. Thereafter, the performance of the different models was evaluated by calculating the deviation component among the three models and the measured data. After analyzing the data of a section of the bridge, the deformation information along the longitudinal direction was acquired. The deformation characteristics of the PS points on both sides of the expansion joint and bridge structure were discussed. Results were used to confirm that the periodic deformation component was the main deformation component on the bridge, thus validating the performance of the Linear–Periodical model as the best among the models. Meanwhile, the thermal effect of the bridge panels caused the difference in the deformation between the two sides of the expansion joint. The analysis of measured data confirms that InSAR technology has the capacity to monitor the microdeformation information of the bridge. In the future, it can identify the bridge with deformation risk early, and search the bridge with risk and its corresponding area in advance. At the same time, the measurement data could also be used for risk cause analysis. Finally, it can provide technical support for urban bridge risk management.