Volume 9 Issue 2
May  2020
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Article Contents
WANG Chao, QIU Xiaolan, LI Fangfang, et al. An InSAR image simulation and elevation inversion method for buildings[J]. Journal of Radars, 2020, 9(2): 373–385. doi: 10.12000/JR20010
Citation: WANG Chao, QIU Xiaolan, LI Fangfang, et al. An InSAR image simulation and elevation inversion method for buildings[J]. Journal of Radars, 2020, 9(2): 373–385. doi: 10.12000/JR20010

An InSAR Image Simulation and Elevation Inversion Method for Buildings

DOI: 10.12000/JR20010
Funds:  The National Natural Science Foundation of China (61991420, 61991421)
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  • Corresponding author: QIU Xiaolan, xlqiu@mail.ie.ac.cn
  • Received Date: 2020-02-13
  • Rev Recd Date: 2020-04-17
  • Available Online: 2020-05-07
  • Publish Date: 2020-04-01
  • The layover and shadow phenomenon is serious in urban areas, where the interferometric phase is complex and disordered and interpretation of an image is difficult. Therefore, it is always a hot and difficult problem for InSAR processing. SAR image simulation can provide data support for the study of image processing and understanding methods. However, most existing SAR image simulation methods for construction areas cannot obtain coherent interferometric SAR image pairs. This article proposes an InSAR simulation method for buildings. It can simulate complex images, interferograms, and the number of layover components of the construction areas. In addition, based on the analysis of the phase variation characteristics of the simulation, a reference determination method for the unwrapped phase in the layover area is proposed. It solves the problem of discontinuity of the interferometric phase in the construction areas, with which the traditional method of unwrapping cannot deal effectively. We compared the simulated results using the actual SAR images and interferometric phase and verified the correctness of our simulation method. Moreover, we carry out phase unwrapping and elevation inversion experiments using the simulated and real images and verified the effectiveness of our phase unwrapping method in applying the InSAR elevation inversion.

     

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  • [1]
    LIU Dawei, SUN Guoqing, GUO Zhifeng, et al. Three-dimensional coherent radar backscatter model and simulations of scattering phase center of forest canopies[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(1): 349–357. doi: 10.1109/TGRS.2009.2024301
    [2]
    LIU Dawei, DU Yang, SUN Guoqing, et al. Analysis of InSAR sensitivity to forest structure based on radar scattering model[J]. Progress in Electromagnetics Research, 2008, 84: 149–171. doi: 10.2528/PIER08071802
    [3]
    XUE Fengli and XU Feng. Scattering verification and imaging of vegetation and its components[C]. The 2018 12th International Symposium on Antennas, Propagation and EM Theory, Hangzhou, China, 2018: 1–4.
    [4]
    XUE Fengli and XU Feng. Coherent scattering and PolinSAR imaging simulation of fractal trees[C]. 2018 China International SAR Symposium, Shanghai, China, 2018: 1–4.
    [5]
    XU Feng, JIN Yaqiu, and MOREIRA A. A preliminary study on SAR advanced information retrieval and scene reconstruction[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(10): 1443–1447. doi: 10.1109/LGRS.2016.2590878
    [6]
    张红敏, 靳国旺, 徐青, 等. 多基线InSAR干涉图的直接法仿真[J]. 测绘科学技术学报, 2010, 27(2): 127–130. doi: 10.3969/j.issn.1673-6338.2010.02.014

    ZHANG Hongmin, JIN Guowang, XU Qing, et al. Direct algorithm for simulation of multi-baseline InSAR interferograms[J]. Journal of Geomatics Science and Technology, 2010, 27(2): 127–130. doi: 10.3969/j.issn.1673-6338.2010.02.014
    [7]
    靳国旺, 徐青, 张红敏. 合成孔径雷达干涉测量[M]. 北京: 国防工业出版社, 2014: 176–179.

    JIN Guowang, XU Qing, and ZHANG Hongmin. Synthetic Aperture Radar Interferometry[M]. Beijing: National Defense Industry Press, 2014: 176–179.
    [8]
    AUER S, HINZ S, BAMLER R, et al. Ray-tracing simulation techniques for understanding high-resolution SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010, 48(3): 1445–1456. doi: 10.1109/TGRS.2009.2029339
    [9]
    AUER S. 3D synthetic aperture radar simulation for interpreting complex urban reflection scenarios[D]. [Ph.D. dissertation], Technische Universität München, 2011: 62–76.
    [10]
    HAMMER H and SCHULZ K. SAR-simulation of large urban scenes using an extended ray tracing approach[C]. 2011 Joint Urban Remote Sensing Event, Munich, Germany, 2011: 289–292.
    [11]
    孙造宇, 梁甸农, 张永胜. 星载InSAR系统DEM重建及其误差分析[J]. 电子与信息学报, 2008, 30(6): 1336–1340. doi: 10.3724/SP.J.1146.2006.01735

    SUN Zaoyu, LIANG Diannong, and ZHANG Yongsheng. Method and error analysis of DEM reconstruction for spaceborne InSAR[J]. Journal of Electronics &Information Technology, 2008, 30(6): 1336–1340. doi: 10.3724/SP.J.1146.2006.01735
    [12]
    林雪, 李曾玺, 李芳芳, 等. 一种自适应迭代的非局部干涉相位滤波方法[J]. 雷达学报, 2014, 3(2): 166–175. doi: 10.3724/SP.J.1300.2014.13123

    LIN Xue, LI Zengxi, LI Fangfang, et al. An adaptive iterated nonlocal interferometry filtering method[J]. Journal of Radars, 2014, 3(2): 166–175. doi: 10.3724/SP.J.1300.2014.13123
    [13]
    靳国旺. InSAR获取高精度DEM关键处理技术研究[D]. [博士论文], 解放军信息工程大学, 2007: 141–146.

    JIN Guowang. Research on key processing techniques for deriving accurate DEM from InSAR[D]. [Ph.D. dissertation], Information Engineering University, 2007: 141–146.
    [14]
    王彦兵, 洪伟, 李小娟, 等. 基于D-InSAR技术的北京城区地面沉降监测[J]. 测绘通报, 2016(5): 66–68, 79.

    WANG Yanbing, HONG Wei, LI Xiaojuan, et al. Monitoring of land subsidence in Beijing based on D-InSAR[J]. Bulletin of Surveying and Mapping, 2016(5): 66–68, 79.
    [15]
    王青松, 时信华, 黄海风, 等. 星载干涉SAR阴影及叠掩区域相位重构方法[J]. 系统工程与电子技术, 2010, 32(4): 699–702.

    WANG Qingsong, SHI Xinhua, HUANG Haifeng, et al. Method of spaceborne InSAR shadow and layover phase reconstruction[J]. Systems Engineering and Electronics, 2010, 32(4): 699–702.
    [16]
    CELLIER F and COLIN E. Building height estimation using fine analysis of altimetric mixtures in layover areas on polarimetric interferometric X-band SAR images[C]. 2006 IEEE International Symposium on Geoscience and Remote Sensing, Denver, USA, 2006: 4004–4007.
    [17]
    LIU Bin, TUPIN F, LIU Xingzhao, et al. Characterization and extraction of building layovers in urban areas using high resolution SAR imagery[C]. 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, Melbourne, Australia, 2013: 895–898.
    [18]
    张同同, 杨红磊, 李东明, 等. SAR影像中叠掩与阴影区域的识别——以湖北巴东为例[J]. 测绘通报, 2019(11): 85–88.

    ZHANG Tongtong, YANG Honglei, LI Dongming, et al. Identification of layover and shadows regions in SAR images——Taking Badong as an example[J]. Bulletin of Surveying and Mapping, 2019(11): 85–88.
    [19]
    ROSSI C and EINEDER M. High-resolution InSAR building layovers detection and exploitation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(12): 6457–6468. doi: 10.1109/TGRS.2015.2440913
    [20]
    YU Hanwen, LAN Yang, YUAN Zhihui, et al. Phase unwrapping in InSAR: A review[J]. IEEE Geoscience and Remote Sensing Magazine, 2019, 7(1): 40–58. doi: 10.1109/MGRS.2018.2873644
    [21]
    POV-Ray 3.6.1 documentation[EB/OL]. http://www.povray.org/documentation/index-3.6.php.
    [22]
    CHEN Jiankun, PENG Lingxiao, QIU Xiaolan, et al. A 3D building reconstruction method for SAR images based on deep neural network[J]. SCIENTIA SINICA Informationis, 2019, 49(12): 1606–1625.
    [23]
    SUN Y, HUA Y, MOU L, et al. Large-scale building height estimation from single VHR SAR image using fully convolutional network and GIS building footprints[C]. 2019 Joint Urban Remote Sensing Event, Vannes, France, 2019: 1–4.
    [24]
    HERRÁEZ M A, BURTON D R, LALOR M J, et al. Fast two-dimensional phase-unwrapping algorithm based on sorting by reliability following a noncontinuous path[J]. Applied Optics, 2003, 41(35): 7437–7444.
    [25]
    NIU Shengren, QIU Xiaolan, LEI Bin, et al. Parameter prediction method of SAR target simulation based on convolutional neural networks[C]. The 12th European Conference on Synthetic Aperture Radar, Aachen, Germany, 2018: 1–5.
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