LAUSR

Phase unwrapping (PU) based on spatial networks is a key procedure in time series synthetic aperture radar interferometry (TS-InSAR). Although the state-of-the-art techniques have shown good success in common cases, their performance remained uncertain in some challenging cases where the reliability of spatial networks is difficult, e.g., reservoir areas with sparse points. In this context, this letter presents a new 3-D PU method based on the fully connected spatiotemporal network (FCSN) to improve both the accuracy and robustness of PU. The rationale behind this is that we first implement a spatiotemporal network refinement including temporal interferogram pair selection and spatial network optimization. Based on the generated spatiotemporal network, we then establish a 3-D PU mathematical framework by elaborating the 2-D edgelist PU theory into the 3-D domain. In this framework, all interferograms are unwrapped using the integer linear programming (ILP) method under the minimum $L^{1}$ -Norm criterion. The new feature of the proposed method is that after a single solution search, all interferograms are unwrapped with relatively high accuracy. The experimental results on two real datasets confirm its effectiveness.