【摘要】 时间序列InSAR技术是一种空间遥感技术,可用于获取基础设施的高精度微小形变信息,相比传统测量手段,该技术有较多优点,在桥梁形变检测方面有广阔的应用前景。但现有的时间序列InSAR技术中的相位解缠算法在大型斜拉桥形变检测上存在较大解缠误差,导致目前该技术还难以获取正确的斜拉桥形变结果。提出一种新的时间序列InSAR相位解缠算法。通过构建约束三角网络,对残差点进行分块,利用二分图最优权匹配方法获取最优的正负残差点匹配结果,从而获取正确的解缠相位。在洞庭湖大桥数据上进行实验验证。该算法在解缠精度上明显优于稀疏网络最小费用流(MCF)算法,有效减少了解缠误差。更多还原

【Abstract】 Time series InSAR technique can be used to obtain the deformation of buildings, and its application in the bridge deformation monitoring is important to bridge health monitoring due to many profits of space remote sensing. However, the present phase unwrapping methods of time series InSAR make many errors in deformation monitoring of the cable-stayed bridge. Thus it is difficult to acquire the reasonable deformation results of the bridge. This work proposes a new phase unwrapping algorithm based on bipartite graph matching with partitioned residues. After generating the constrained Delaunay triangulation network, the found residues are then partitioned. Finally, the bipartite graph matching algorithm is used to get the optimal connection of positive and negative residues, and the unwrapped phase is acquired by integration of wrapped phase gradient field. The results, tested on real SAR images of the Dongtinghu Bridge, confirm the effectiveness and reliability of the algorithm.更多还原