Phase Cost Indicator-Guided Central Difference Information Filter 2-D Phase Unwrapping Approach

Phase unwrapping (PU) as an ill-posed inverse scientific problem has invariably been the significant difficulty in interferometric synthetic aperture radar technique for topographic mapping. Conventional PU approaches may produce a local or global unwrapping bias in severe phase changes caused by noise and large gradient terrain because the phase continuity assumption is not satisfied. To address this issue, we have created a novel phase quality-guided integrated filtering and unwrapping process for PU. In particular, the PU path is guided by an innovative phase cost indicator, which can automatically coordinate contributions from several phase quality estimation methods so that the unwrapping path can circumvent phase discontinuity regions and delay unwrapping these pixels. Since the central difference transform is another extra effective nonlinear transformation mode based on sigma points and only has one regulation parameter, we have employed the central difference information filter (CDIF) for the first time to realize the dynamic estimation of the unwrapped phase in the PU process. We tested the proposed approach using two real datasets with different mountainous areas. The results demonstrate that the PU accuracy of the proposed approach based on these two datasets is improved by 25.2% and 40.4% compared to the unscented information filtering (UIF) PU method, and the anti-noise capacity and unwrapping efficiency of the CDIF are both slightly superior to the UIF.