An Efficient Approach to Spatio-Temporal 3D Phase Unwrapping

Phase unwrapping is a key problem in several technical fields, among which SAR interferometry (InSAR). In this work, a new computationally efficient approach to spatio-temporal three-dimensional (3D) phase unwrapping is proposed. The method makes it feasible to process very large datasets fully exploiting the information from the spatial and temporal structures of the data. The global 3D phase unwrapping problem is separated into smaller subproblems, each of them global spatially or temporally, which are solved iteratively till convergence to a suboptimal but still very good solution. Moreover, to further improve computational efficiency, we propose an iterative least-squares strategy for phase unwrapping that exploits the integer character of the phase ambiguities to be recovered and the repeated structures in the subproblems to be solved. As a third element, which can additionally improve computational performance and result robustness, a pyramidal solution strategy can be considered, consisting of successive phase unwrapping of subsets of points, typically with increasing noise, each constrained by the previous results. The tests performed on simulated and real satellite InSAR data confirm the validity of the proposed approach.