A Novel 2-D Phase Unwrapping Method Based on PUMA for Aerospace Topographic Mapping Systems

Abstract

Two-dimensional phase unwrapping (PU) is the key step of interferometric synthetic aperture radar technology. The accuracy of the PU results directly affects the quality of the final product. Due to the limitation of the phase continuity assumption, the results obtained by the single-baseline PU in large gradient regions are not ideal. To solve this problem, this article proposes an improved PU max-flow/min-cut algorithm (PUMA) which can efficiently deal with the phase of large gradient regions. First, we construct a quasiconvex function which is the combination of logarithmic and quadratic functions as the potential function in the energy function model of the PUMA method. Then, we use the gradient information of the external digital elevation model to assist in setting the weight of the potential function. Finally, the unwrapped phase is obtained by minimizing the new energy function model. The experimental results on the TanDEM-X dataset show that the improved approach in this article can achieve higher accuracy PU results in the region of large gradient variation than the existing PU methods.