Refined Two-Stage Programming Approach to Multibaseline Phase Unwrapping via Gradient Regularization and Quality-Guided Triangulation

Multibaseline (MB) synthetic aperture radar interferometry (InSAR) is capable of reconstructing steep terrain height profiles, and MB phase unwrapping (PU) is one of the most critical and challenging steps in its processing chain. Existing MB PU algorithms usually suffer from poor noise robustness or low computational efficiency. In this work, we propose a fast and robust MB PU algorithm, including three main steps: 1) construct the triangulation network guided by the quality map; 2) obtain robust estimation of ambiguity number gradients based on the intrinsic relationship between interferograms and gradient regularization; and 3) solve minimum cost flow (MFC) problem with modified weights. The mean absolute errors of the height profiles constructed by the proposed method are 1.6 and 1.3 m for simulated data and real data experiments respectively, verifying the effectiveness of the proposed method.