An InSAR Deformation Phase Retrieval Method Combined with Reference Phase in Mining Areas - Zhihong Wang; Huayang Dai; Yueguan Yan; Jintong Ren; Yanjun Zhang; Jibo Liu (Remote Sensing, 2023)
The acquisition of precise deformation data, including the entirety of the subsidence basin resulting from subterranean mining operations, assumes critical significance in the context of surface impairment monitoring during the course of mining activities. In light of the constraints associated with InSAR technology when applied to the surveillance of expansive deformation gradient mining regions, an innovative approach is advanced herein for InSAR deformation phase retrieval. This approach integrates a reference phase, derivable through a variety of means, including pre-existing models or measurements. Initially, the reference deformation phase is subjected to subtraction from the wrapped InSAR deformation phase, culminating in the derivation of the wrapped phase indicative of the residual phase. Notably, it is posited that the fringe density characterizing the wrapped phase of the residual phase is theoretically diminished in comparison to that of the InSAR wrapped phase. This reduction in complexity in phase unwrapping ensues as a direct consequence. Subsequent to this, the phase retrieval process is effectuated through the summation of the reference phase and the unwrapped phase pertaining to the residual phase. The study harnesses Sentinel-1A and ALOS PALSAR-2 data, employing the PIM-predicted outcomes and GNSS-RTK monitoring outcomes as reference phases for the execution of phase retrieval experiments in two designated study areas. The computation of subsidence is subsequently realized through the combination of the displacement vector depression angle model and the retrieved phase, with the accuracy thereof corroborated through the utilization of leveling data. The experimental findings underscore the efficacy of the reference phase retrieval methodology in securing a more precise deformation phase characterization within expansive deformation gradient mining regions, thereby demonstrating the suitability of this methodological approach.