Abstract:   Objectives:   Mine slope instability is one of the main factors restricting the safety production of open-pit mines in China.   Methods:   Ground-based SAR(synthetic aperture radar) interferometry technology has been gradually introduced into the application of slope safety monitoring and early warning prediction in open-pit mines. However, the high-frequency rolling update characteristics of ground radar interferometry data lead to large data error accumulation and unobvious curve mutation characteristics. Processing the original data by dislocation subtraction and velocity reciprocal method can effectively reduce the vibration of high-frequency data, improve the readability of critical sliding data. After data processing, it can highlight the trend characteristics of key deformation data. The research is based on the analysis of cumulative displacement curve, velocity curve and reciprocal velocity curve group treated with different periods. It is found that there are three characteristic points in the curve group:sudden deformation increase point, velocity increase point and stable vibration point.   Results:   Through these characteristic points, the slope landslide disaster can be predicted and predicted. The trend of key deformation data can be highlighted by using the three feature points of deformation sudden increase point, velocity growth point and stable vibration point.   Conclusions:   Through the identification of three feature points, the possible landslide can be effectively identified in advance and the landslide time can be predicted, which provides a new technical path and solution for landslide early warning and prediction analysis based on ground-based Interferometric Radar.