MA Zhangfeng, YUE Dongjie, JIANG Mi, LIU Lian. Co-registration of Image Stacks for Sentinel-1A TOPS Mode Based on Dijkstra's Algorithm[J]. Geomatics and Information Science of Wuhan University, 2020, 45(6): 904-913. DOI: 10.13203/j.whugis20180412
Citation: MA Zhangfeng, YUE Dongjie, JIANG Mi, LIU Lian. Co-registration of Image Stacks for Sentinel-1A TOPS Mode Based on Dijkstra's Algorithm[J]. Geomatics and Information Science of Wuhan University, 2020, 45(6): 904-913. DOI: 10.13203/j.whugis20180412

Co-registration of Image Stacks for Sentinel-1A TOPS Mode Based on Dijkstra's Algorithm

Funds: The National Key Research and Development Program of China (2018YFC0407900); the National Natural Science Foundation of China (41774003); the Natural Science Foundation of Jiangsu Province (BK20171432); the Fundamental Research Funds for the Central Universities (2018B17714).
More Information
  • Author Bio:

    MA Zhangfeng, PhD candidate, specializes in InSAR data processing and geophysics.jspcmazhangfeng@hhu.edu.cn

  • Corresponding author:

    YUE Dongjie, PhD, professor. E-mail:yuedongjie@163.com

  • Received Date: June 19, 2019
  • Published Date: June 04, 2020
  • Today, Sentinel-1A data with terrain observation with progressive scanning (TOPS) imaging mode is increasingly used in earth observation aiming at consistent monitoring of surface change and its deformation. However, due to the limited accuracy of coarse co-registration, spectral aliasing along the azimuth direction enables the presence of phase jumping in overlapping area of neighboring bursts. Although geometrical co-registration in conjunction with enhanced spectral diversity (ESD) is proven to be a feasible strategy to correct such error and has been widely used in some open source softwares (e.g. DORIS (Delft object-oriented radar interferometric software), SNAP (sentinel applications platform), ISCE (InSAR scientific computing environment)), the performance of ESD is still not satisfactory and relies strongly on spatiotemporal decorrelation. Given that decorrelation is generally quantized by interferometric coherence, this paper presents and assesses a new methodology to improve the accuracy of ESD by fully exploring the high coherent targets. Specifically, this method focuses on mitigating the spatiotemporal decorrelation in fine co-registration procedures by:(1) Selecting stable targets with moderate and high coherence using accurate coherence estimation. (2) Maximizing coherence magnitude by optimal interferometric subset chosen from Dijkstra algorithm. We compare and test this method against current favorites based on single master image and network-based enhanced spectral diversity (NESD), and the experimental results demonstrate the value of our method. It can make up for the shortage of NESD method.
  • [1]
    Torres R, Snoeij P, Geudtner D, et al. GMES Sentinel-1 Mission[J]. Remote Sensing of Environment, 2012, 120:9-24 doi: 10.1016/j.rse.2011.05.028
    [2]
    Geudtner D, Torres R. Sentinel-1 System Overview and Performance[C]. 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany, 2012
    [3]
    De Zan F, Guarnieri A M. TOPSAR:Terrain Observation by Progressive Scans[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(9):2352-2360 doi: 10.1109/TGRS.2006.873853
    [4]
    Sansosti E, Berardino P, Manunta M, et al. Geometrical SAR Image Registration[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(10):2861-2870 doi: 10.1109/TGRS.2006.875787
    [5]
    De Zan F. Accuracy of Incoherent Speckle Tracking for Circular Gaussian Signals[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 11(1):264-267 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=820f951d82b3f68db785abb6bc0be039
    [6]
    吴文豪, 周志伟, 李陶, 等. 精密轨道支持下的哨兵卫星TOPS模式干涉处理[J]. 测绘学报, 2017, 46(9):1156-1164 http://d.old.wanfangdata.com.cn/Periodical/chxb201709011

    Wu Wenhao, Zhou Zhiwei, Li Tao, et al. A Study of Sentinel-1 TOPS Mode Co-registration[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(9):1156-1164 http://d.old.wanfangdata.com.cn/Periodical/chxb201709011
    [7]
    李振洪, 宋闯, 余琛, 等. 卫星雷达遥感在滑坡灾害探测和监测中的应用:挑战与对策[J]. 武汉大学学报·信息科学版, 2019, 44(7):967-979 doi: 10.13203/j.whugis20190098

    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, 2019, 44(7):967-979 doi: 10.13203/j.whugis20190098
    [8]
    Tian X, Malhotra R, Xu B, et al. Modeling Orbital Error in InSAR Interferogram Using Frequency and Spatial Domain Based Methods[J]. Remote Sensing, 2018, 10(4):508 doi: 10.3390/rs10040508
    [9]
    Scheiber R, Moreira A. Coregistration of Interferometric SAR Images Using Spectral Diversity[J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38(5):2179-2191 doi: 10.1109/36.868876
    [10]
    Prats-Iraola P, Scheiber R, Marotti L, et al. TOPS Interferometry with TerraSAR-X[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(8):3179-3188 doi: 10.1109/TGRS.2011.2178247
    [11]
    Bamler R, Eineder M. Accuracy of Differential Shift Estimation by Correlation and Split-Bandwidth Interferometry for Wideband and Delta-k SAR Systems[J]. IEEE Geoscience and Remote Sensing Letters, 2005, 2(2):151-155 doi: 10.1109/LGRS.2004.843203
    [12]
    Yague-Martinez N, Prats-Iraola P, Gonzalez F R, et al. Interferometric Processing of Sentinel-1 TOPS Data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(4):2220-2234 doi: 10.1109/TGRS.2015.2497902
    [13]
    Veci L, Lu J, Foumelis M, et al. ESA's Multi-mission Sentinel-1 Toolbox[C]. The EGU General Assembly Conference, Vienna, Austria, 2017
    [14]
    Kampes B, Usai S. Doris:The Delft Object-Oriented Radar Interferometric Software[C]. The 2nd International Symposium on Operationalization of Remote Sensing, Enschede, Netherlands, 1999
    [15]
    Rosen P A, Gurrola E, Sacco G F, et al. The InSAR Scientific Computing Environment[C]. The 9th European Conference on Synthetic Aperture Radar, Nuremberg, Germany, 2012
    [16]
    Fattahi H, Agram P, Simons M. A Network-Based Enhanced Spectral Diversity Approach for TOPS Time-Series Analysis[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 55(2):777-786 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=f2005014546cd683023c17e807ec04c0
    [17]
    Yague-Martinez N, de Zan F, Prats-Iraola P. Coregistration of Interferometric Stacks of Sentinel-1 Tops Data[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(7):1002-1006 doi: 10.1109/LGRS.2017.2691398
    [18]
    Xu B, Li Z, Feng G, et al. Continent-Wide 2-d Co-seismic Deformation of the 2015 Mw 8.3 Illapel, Chile Earthquake Derived from Sentinel-1A Data:Correction of Azimuth Co-registration Error[J]. Remote Sensing, 2016, 8(5):376 doi: 10.3390/rs8050376
    [19]
    Berardino P, Fornaro G, Lanari R, et al. A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms[J]. IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11):2375-2383 doi: 10.1109/TGRS.2002.803792
    [20]
    Dijkstra E W. A Note on Two Problems in Connexion with Graphs[J]. Numerische Mathematik, 1959, 1(1):269-271 doi: 10.1007/BF01386390
    [21]
    Rocca F. Modeling Interferogram Stacks[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(10):3289-3299 doi: 10.1109/TGRS.2007.902286
    [22]
    Guarnieri A M, Tebaldini S. Hybrid Cramér-Rao Bounds for Crustal Displacement Field Estimators in SAR Interferometry[J]. IEEE Signal Processing Letters, 2007, 14(12):1012-1015 doi: 10.1109/LSP.2007.904705
    [23]
    Jiang M, Ding X, Li Z, et al. InSAR Coherence Estimation for Small Data Sets and Its Impact on Temporal Decorrelation Extraction[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(10):6584-6596 doi: 10.1109/TGRS.2014.2298408
    [24]
    Jiang M, Ding X, Li Z. Hybrid Approach for Unbiased Coherence Estimation for Multitemporal InSAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 52(5):2459-2473 https://www.researchgate.net/publication/261296082_Hybrid_Approach_for_Unbiased_Coherence_Estimation_for_Multitemporal_InSAR
    [25]
    蒋弥, 丁晓利, 李志伟, 等. 基于时间序列的InSAR相干性量级估计[J]. 地球物理学报, 2013, 56(3):799-811 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dqwlxb201303009

    Jiang Mi, Ding Xiaoli, Li Zhiwei, et al. InSAR Coherence Magnitude Estimation Based on Data Stack[J]. Chinese Journal of Geophysics, 2013, 56(3):799-811 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dqwlxb201303009
    [26]
    Wang T, Liao M, Perissin D. InSAR Coherence-Decomposition Analysis[J]. IEEE Geoscience and Remote Sensing Letters, 2009, 7(1):156-160 http://d.old.wanfangdata.com.cn/Periodical/hwyhmb201604013
    [27]
    Refice A, Bovenga F, Nutricato R. MST-Based Stepwise Connection Strategies for Multipass Radar Data, with Application to Coregistration and Equalization[J]. IEEE Transactions on Geoscience and Remote Sensing, 2006, 44(8):2029-2040 doi: 10.1109/TGRS.2006.872907
  • Related Articles

    [1]ZHU Shaolin, YUE Dongjie, HE Lina, CHEN Jian, LIU Shengnan. BDS-2/BDS-3 Joint Triple-Frequency Precise Point Positioning Models and Bias Characteristic Analysis[J]. Geomatics and Information Science of Wuhan University, 2023, 48(12): 2049-2059. DOI: 10.13203/j.whugis20210273
    [2]GENG Jianghui, YAN Zhe, WEN Qiang. Multi-GNSS Satellite Clock and Bias Product Combination: The Third IGS Reprocessing Campaign[J]. Geomatics and Information Science of Wuhan University, 2023, 48(7): 1070-1081. DOI: 10.13203/j.whugis20230071
    [3]LIU Mingliang, AN Jiachun, WANG Zemin, ZHANG Baojun, SONG Xiangyu. Performance Analysis of BDS-3 Multi-frequency Pseudorange Positioning[J]. Geomatics and Information Science of Wuhan University, 2023, 48(6): 902-910. DOI: 10.13203/j.whugis20200714
    [4]YUAN Haijun, ZHANG Zhetao, HE Xiufeng, XU Tianyang, XU Xueyong. Stability Analysis of BDS-3 Satellite Differential Code Bias and Its Impacts on Single Point Positioning[J]. Geomatics and Information Science of Wuhan University, 2023, 48(3): 425-432. DOI: 10.13203/j.whugis20200517
    [5]ZHOU Ren-yu, HU Zhi-gang, CAI Hong-liang, ZHAO Zhen, RAO Yong-nan, CHEN Liang, ZHAO Qi-le. Analysis of Pseudorange and Carrier Ranging Deviation of BDS-3 Using Parabolic Directional Antenna[J]. Geomatics and Information Science of Wuhan University, 2021, 46(9): 1298-1308. DOI: 10.13203/j.whugis20200182
    [6]ZHANG Hui, HAO Jinming, LIU Weiping, ZHOU Rui, TIAN Yingguo. GPS/BDS Precise Point Positioning Model with Receiver DCB Parameters for Raw Observations[J]. Geomatics and Information Science of Wuhan University, 2019, 44(4): 495-500, 592. DOI: 10.13203/j.whugis20170119
    [7]ZOU Xuan, LI Zongnan, CHEN Liang, LI Min, TANG Weiming, SHI Chuang. Modeling BeiDou IGSO and MEO Satellites Code Pseudorange Variations[J]. Geomatics and Information Science of Wuhan University, 2018, 43(11): 1661-1666. DOI: 10.13203/j.whugis20160275
    [8]LI Xin, ZHANG Xiaohong, ZENG Qi, PAN Lin, ZHU Feng. The Estimation of BeiDou Satellite-induced Code Bias and Its Impact on the Precise Positioning[J]. Geomatics and Information Science of Wuhan University, 2017, 42(10): 1461-1467. DOI: 10.13203/j.whugis20160062
    [9]LOU Yidong, GONG Xiaopeng, GU Shengfeng, ZHENG Fu, YI Wenting. The Characteristic and Effect of Code Bias Variations of BeiDou[J]. Geomatics and Information Science of Wuhan University, 2017, 42(8): 1040-1046. DOI: 10.13203/j.whugis20150107
    [10]FAN Lei, ZHONG Shiming, LI Zishen, OU Jikun. Effect of Tracking Stations Distribution on the Estimation of Differential Code Biases by GPS Satellites Based on Uncombined Precise Point Positioning[J]. Geomatics and Information Science of Wuhan University, 2016, 41(3): 316-321. DOI: 10.13203/j.whugis20140114
  • Cited by

    Periodical cited type(28)

    1. 吕峥,孙群,温伯威,张付兵,马京振. 顾及形状相似性的道路与居民地协同化简方法. 地球信息科学学报. 2024(05): 1270-1282 .
    2. 铁占琦. 利用改进的Hausdorff距离匹配多尺度线要素. 地理空间信息. 2024(05): 62-65 .
    3. 王庆社,王雅欣,姜青香,郭思慧. “天地图·北京”多源道路数据融合关键技术研究. 北京测绘. 2024(06): 874-879 .
    4. 陈钉均,梁芮嘉. 基于特征聚类驾驶员服从度跟驰模型参数标定. 计算机仿真. 2024(10): 126-132 .
    5. 齐杰,王中辉,李驿言. 基于图卷积神经网络的道路网匹配. 测绘通报. 2023(12): 19-24+44 .
    6. 吴冰娇,王中辉,杨飞. 用于多尺度道路网匹配的语义相似性计算模型. 测绘科学. 2022(03): 166-173 .
    7. 蒋阳升,俞高赏,胡路,李衍. 基于聚类站点客流公共特征的轨道交通车站精细分类. 交通运输系统工程与信息. 2022(04): 106-112 .
    8. 周秀华,李乃强. 基于多种相似度特征的道路实体融合方法. 测绘通报. 2021(08): 102-105+157 .
    9. 秦育罗,宋伟东,张在岩,孙小荣. 顾及几何特征和拓扑连续性的道路网匹配方法. 测绘通报. 2021(08): 55-60 .
    10. 杨飞,王中辉. 河系几何相似性的层次度量方法. 地球信息科学学报. 2021(12): 2139-2150 .
    11. 程绵绵,孙群,季晓林,赵云鹏. 改进平均Fréchet距离法及在化简评价中的应用. 测绘科学. 2020(03): 170-177 .
    12. 赵元棣,田英杰,吴佳馨. 航空器飞行轨迹相似性度量及聚类分析. 中国科技论文. 2020(02): 249-254 .
    13. Wenyue GUO,Anzhu YU,Qun SUN,Shaomei LI,Qing XU,Bowei WEN,Yuanfu LI. A Multisource Contour Matching Method Considering the Similarity of Geometric Features. Journal of Geodesy and Geoinformation Science. 2020(03): 76-87 .
    14. 秦育罗,郭冰,孙小荣. 改进Hausdorff距离及其在多尺度道路网匹配中的应用. 测绘科学技术学报. 2020(03): 313-318 .
    15. 郝志伟,李成名,殷勇,武鹏达,吴伟. 一种基于Fréchet距离的断裂等高线内插算法. 测绘通报. 2019(01): 65-68+74 .
    16. 郭文月,刘海砚,孙群,余岸竹,丁梓越. 顾及几何特征相似性的多源等高线匹配方法. 测绘学报. 2019(05): 643-653 .
    17. 宗琴,彭荃,秦万英. 一种基于模糊矩阵的空间面对象相似性度量算法. 北京测绘. 2019(10): 1218-1221 .
    18. 李兆兴,翟京生,武芳. 线要素综合的形状相似性评价方法. 武汉大学学报(信息科学版). 2019(12): 1859-1864 .
    19. 周家新,陈建勇,单志超,陈长康. 航空磁探中潜艇目标的联合估计检测方法研究. 兵工学报. 2018(05): 833-840 .
    20. 郭宁宁,盛业华,吕海洋,黄宝群,张思阳. 径向基函数神经网络的路网自动匹配算法. 测绘科学. 2018(03): 45-50 .
    21. 张瀚,李静,吕品,徐永志,刘格林. 六角格网的弧线矢量数据量化拟合方法. 计算机辅助设计与图形学学报. 2018(04): 557-567 .
    22. 邵世维,刘辉,肖立霞,王恒. 一种基于Fréchet距离的复杂线状要素匹配方法. 武汉大学学报(信息科学版). 2018(04): 516-521 .
    23. 苏满佳,张逸鸿,谢荣臻,朱海飞,管贻生,毛世鑫. 连续软体机器人的结构范型与形态复现. 机器人. 2018(05): 640-647+672 .
    24. 宗琴,姜树辉,刘艳霞. 多尺度矢量地图中模糊相似变换及其度量模型. 测绘科学. 2018(11): 72-78 .
    25. 郭文月,刘海砚,孙群,余岸竹,季晓林. 利用最长公共子序列度量线要素相似性的方法. 测绘科学技术学报. 2018(05): 518-523 .
    26. 郭宁宁,盛业华,黄宝群,吕海洋,张思阳. 基于人工神经网络的多特征因子路网匹配算法. 地球信息科学学报. 2016(09): 1153-1159 .
    27. 杨亚辉. 利用几何相似性快速测量鱼重的数学模型. 电子技术与软件工程. 2016(20): 182-183 .
    28. 逯跃锋,张奎,刘硕,吴跃,赵硕,李强,冯晨. 一种基于斜率差和方位角的矢量数据匹配算法. 山东大学学报(工学版). 2016(06): 31-39 .

    Other cited types(30)

Catalog

    Article views (1510) PDF downloads (87) Cited by(58)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return