Ground-Based InSAR Real-Scene Imaging and Deformation-Extraction Dataset

‍ ‍Ground-based interferometric synthetic aperture radar （GB-InSAR） technology， owing to its unique advantages of all-day， all-weather operation as well as long-term stable and continuous operation， presents broad application prospects in numerous fields， including mine-slope monitoring， geological disaster monitoring， building health monitoring， and disaster early warning. Although certain achievements have been realized using this technology， the non-disclosure of relevant actual data limits the innovative development of ground-based radar technology. Hence， this paper publicly discloses a dataset of GB-InSAR real-scene imaging and deformation extraction. This dataset includes echo， imaging， and coherence data obtained using ground-based radar for the same scene and for scenes with multiple corner reflectors placed at different distances. Additionally， it includes full-process GB-InSAR data for both standard bodies and actual measurement scenes. Based on a comprehensive analysis of these data， multidimensional research on the data can be performed. In terms of radar imaging， analysis is performed based on imaging performance indicators， such as radar resolution. By analyzing the coherence coefficient data， the consistency of the target at different times or spaces is investigated， thus providing a more accurate method for target recognition and monitoring. This dataset not only verifies the reliability and stability of the GB-InSAR monitoring technology but also shows that the monitoring technology of GB-InSAR can reach the millimeter or even submillimeter accuracy level， thereby providing an effective method for monitoring minimal deformations of buildings and the Earth’s surface in real time. This dataset fully considers the demands of studies pertaining to radar signal-processing methods， such as radar imaging and system stability， for actual measurement data and provides diversified data resources for relevant scholars. Additionally， deformation analysis can be performed based on these data， thus providing robust data support for the health monitoring of structures and disaster early warning.