Multi-baseline phase unwrapping breaks through the limit of phase continuity assumption through extending the am-biguity boundary of single-baseline phase unwrapping.However,phase noise is still challenging the multi-baseline unwrap-ping.The clustering analysis algorithm can suppress the noise to a certain extent,but it is hard to guarantee continuity of clus-ter edges.In this paper,a discrete-optimization-based multi-baseline InSAR phase unwrapping algorithm is proposed,which transforms the classical multi-baseline unwrapping into a discrete optimization problem and constructs a multi-baseline unwrap-ping analytical framework.The method solves the phase ambiguity in the bidirectional form,and introduces block clustering to correct the abrupt change of the phase ambiguities caused by heavy noise,improving the robustness of the algorithm and over-coming the cluster boundary hopping.The effectiveness of the method has been validated through simulation and real data tests.The results show that the proposed algorithm reduces the root mean square error by about 20％compared with the tradi-tional clustering method.
维普
万方数据