A multi-baseline phase unwrapping method based on a discrete optimization framework

被引：0
|
作者：
Yue J. [1 ]
Huang Q. [1 ]
Liu H. [2 ]
Ma Z. [3 ]
机构：
[1] School of Earth Sciences and Engineering THohai University, Nanjing
[2] College of Surveying and Geo-Information, North China University of Water Resources and Electric Power, Zhengzhou
[3] Nanyang Technological University, Earth Observatory of Singapore
来源：
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica | 2024年 / 53卷 / 03期
基金：
中国国家自然科学基金;
关键词：
cluster analysis; discrete optimization; multi-baseline) InSAR phase unwrapping; phase continuity assumption;
D O I：
10.11947/j.AGCS.2024.20220617
中图分类号：
学科分类号：
摘要：
Multi-baseline phase unwrapping breaks through the limit of phase continuity assumption through extending the ambiguity boundary of single-baseline phase unwrapping. However, phase noise is still challenging the multi-baseline unwrapping. The clustering analysis algorithm can suppress the noise to a certain extent, but it is hard to guarantee continuity of cluster 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 unwrapping 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 overcoming 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 traditional clustering method. © 2024 SinoMaps Press. All rights reserved.
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收藏
页码：473 / 481
页数：8
相关论文
共 38 条
  • [1] BAMLER R, HARTL P., Synthetic aperture radar interferometry, Inverse Problems, 14, 4, pp. R1-R54, (1998)
  • [2] XING Mengdao, PASCAZIO V, YU Hanwen, A special issue on synthetic aperture radar interferometry[J], IEEE Geoscience and Remote Sensing Magazine, 8, 1, pp. 6-7, (2020)
  • [3] BIOUCAS-DIAS J M, VALADAO G., Phase unwrapping via graph cuts[J], IEEE Transactions on Image Processing, 16, 3, pp. 698-709, (2007)
  • [4] TANG Xinming, LI Tao, GAO Xiaoming, Et al., Research on key technologies of precise InSAR surveying and mapping applications using automatic SAR imaging[J], Journal of Geodesy and Geoinformation Science, 2, 1, (2019)
  • [5] ZHU Jianjun, LI Zhiwei, HU Jun, Research progress and methods of InSAR for deformation monitoring[J], Acta Geodaetica et Cartographica Sinica, 46, 10, pp. 1717-1733, (2017)
  • [6] LIU Guang, ZBIGNIEW P, STEFANO S, Et al., Land surface displacement geohazards monitoring using multi-temporal InSAR techniques[J], Journal of Geodesy and Geoinformation Science, 4, 1, pp. 77-87, (2021)
  • [7] Chen YU, LI Zhenhong, BAI Lin, Et al., Successful applications of generic atmospheric correction online service for InSAR (GACOS) to the reduction of atmospheric effects on InSAR observations[J], Journal of Geodesy and Geoinformation Science, 4, 1, pp. 109-115, (2021)
  • [8] LI Zhenhong, ZHU Wu, YU Chen, Et al., Interferometric synthetic aperture radar for deformation mapping:opportunities, challenges and the outlook[J], Acta Geodaetica et Cartographica Sinica, 51, 7, pp. 1485-1519, (2022)
  • [9] GHIGLIA D C, PRITT M D., Two-dimensional phase unwrapping:theory, algorithms, and software, (1998)
  • [10] LI Zhenhong, SONG Chuang, YU Chen, Et al., Application of satellite radar remote sensing to landslide detection and monitoring:challenges and solutions[J], Geomatics and Information Science of Wuhan University, 44, 7, pp. 967-979, (2019)
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