Extended Puma Algorithm for Multibaseline SAR Interferograms

Phase unwrapping (PU) is one of the key process in reconstructing the digital elevation model (DEM) of a scene from its interferometric synthetic aperture radar (InSAR) data. Compared with traditional single-baseline PU, the multibaseline PU does not need to obey the phase continuity assumption, which can be applicable to reconstruct the DEM where topography varies drastically. However, the performance of the multibaseline PU is directly concerned with noise level. Contrarily, the single-baseline PU algorithm has good noise robustness, since it is based on the globe wrapped phase information, such as PU-max-flow (PUMA) algorithm. In order to improve the noise robustness of the multibaseline, in this paper, we extend single-baseline PUMA algorithm to multibaseline domain, referred to as multibaseline PUMA algorithm, which allows the unwrapping of multibaseline interferograms for the generation of DEM. The proposed algorithm does not need to obey the phase continuity assumption by taking the advantages of multibaseline diversity and improves the noise robustness by using the global wrapped information both from single- and multibaseline domain. The performance of the proposed algorithm is tested on simulated InSAR data experiments, which demonstrate the effectiveness and noise robustness of the proposed algorithm.

[1]  Xiang-Gen Xia,et al.  Phase Unwrapping and A Robust Chinese Remainder Theorem , 2007, IEEE Signal Processing Letters.

[2]  Dennis C. Ghiglia,et al.  Two-Dimensional Phase Unwrapping: Theory, Algorithms, and Software , 1998 .

[3]  Giampaolo Ferraioli,et al.  Urban Digital Elevation Model Reconstruction Using Very High Resolution Multichannel InSAR Data , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Zheng Bao,et al.  A Cluster-Analysis-Based Efficient Multibaseline Phase-Unwrapping Algorithm , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[5]  V. Pascazio,et al.  Estimation of terrain elevation by multifrequency interferometric wide band SAR data , 2001, IEEE Signal Processing Letters.

[6]  Vito Pascazio,et al.  Maximum a posteriori estimation of height profiles in InSAR imaging , 2004, IEEE Geoscience and Remote Sensing Letters.

[7]  Vito Pascazio,et al.  Multifrequency InSAR height reconstruction through maximum likelihood estimation of local planes parameters , 2002, IEEE Trans. Image Process..

[8]  Giampaolo Ferraioli,et al.  Multichannel Phase Unwrapping With Graph Cuts , 2009, IEEE Geoscience and Remote Sensing Letters.

[9]  José M. Bioucas-Dias,et al.  Phase Unwrapping via Graph Cuts , 2007, IEEE Trans. Image Process..

[10]  Yang Lan,et al.  Robust Two-Dimensional Phase Unwrapping for Multibaseline SAR Interferograms: A Two-Stage Programming Approach , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Fuk K. Li,et al.  Synthetic aperture radar interferometry , 2000, Proceedings of the IEEE.

[12]  Gianfranco Fornaro,et al.  Phase difference-based multichannel phase unwrapping , 2005, IEEE Transactions on Image Processing.

[13]  Mengdao Xing,et al.  A Novel Mixed-Norm Multibaseline Phase-Unwrapping Algorithm Based on Linear Programming , 2015, IEEE Geoscience and Remote Sensing Letters.

[14]  Wei Xu,et al.  Phase-unwrapping of SAR interferogram with multi-frequency or multi-baseline , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[15]  邓云凯 王宇 柳罡 韩晓磊 袁志辉 Multichannel InSAR DEM Reconstruction Through Improved Closed-Form Robust Chinese Remainder Theorem , 2013 .