中文摘要：

在对不规则网格中残差计算的性质进行分析的基础上,提出了用于离散数据的相位解缠的MST-FloodFill方法,该方法利用Delaunay三角网连接离散数据,在每个三角形中计算残差值,通过最小跨越树（MST）算法建立正负残差平衡的最小生成树,利用FloodFill算法绕过枝切线进行积分得到离散数据的解缠相位,从而实现离散数据的相位解缠。利用模拟数据和真实数据进行的实验以及将所得结果与真实结果进行的比对显示,利用这种离散数据解缠方法得出的结果完全正确,而且有较高的解缠效率,从而验证了该方法对于离散数据解缠的正确性和有效性。

英文摘要：

To get rid of the limitations caused by baseline and spatial baseline wihen using conventional differential synthetic aperture radar interferometry and fully use acquired data to study ground deformation time-series, this paper presents the MST-Flood Fill, a new algorithm for sparse data, which can solve the problem that the existing methods that extract information of ground deformation by analyzing phases of regular grid data can not be used for phase unwrapping for sparse stable scatters. The algorithm constructs Delaunay triangle mesh to connect sparse data and compute residues in each triangle. It generates the minimum spanning tree （MST） which connects all the negative and positive residues to each other, and integrates phases using Flood Fill algorithm. The method was tested by the experiment with simulated data and real data, and the results were compared with the real ones. The comparison proved the correctness and the effectiveness of the algorithm presented in this paper.