一种InSAR建筑物图像仿真及高程反演方法

王超 仇晓兰 李芳芳 雷斌

王超, 仇晓兰, 李芳芳, 等. 一种InSAR建筑物图像仿真及高程反演方法[J]. 雷达学报, 2020, 9(2): 373–385. doi: 10.12000/JR20010
引用本文: 王超, 仇晓兰, 李芳芳, 等. 一种InSAR建筑物图像仿真及高程反演方法[J]. 雷达学报, 2020, 9(2): 373–385. doi: 10.12000/JR20010
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

一种InSAR建筑物图像仿真及高程反演方法

doi: 10.12000/JR20010
基金项目: 国家自然科学基金(61991420, 61991421)
详细信息
    作者简介:

    王超:王 超(1995–),男,籍贯山西,天津大学学士,中国科学院空天信息创新研究院在读硕士生,研究方向为InSAR典型建筑三维重建。E-mail: wangchao173@mails.ucas.edu.cn

    仇晓兰(1982–),女,籍贯江苏,中国科学院空天信息创新研究院研究员,博士生导师,研究方向为合成孔径雷达成像处理与应用、遥感大数据分析与信息提取。E-mail: xlqiu@mail.ie.ac.cn

    李芳芳(1986–),女,籍贯山西,中国科学院空天信息创新研究院副研究员,研究方向为干涉合成孔径雷达信号处理、SAR三维成像。E-mail: ffli1@mail.ie.ac.cn

    雷斌:雷 斌(1978–),男,中国科学院空天信息创新研究院研究员,研究方向为合成孔径雷达数据处理与图像理解、遥感图像处理与信息提取、空间信息处理系统体系结构。E-mail: leibin@mail.ie.ac.cn

    通讯作者:

    仇晓兰 xlqiu@mail.ie.ac.cn

  • 责任主编:靳国旺 Corresponding Editor: JIN Guowang
  • 中图分类号: TN959.1+7

An InSAR Image Simulation and Elevation Inversion Method for Buildings

Funds: The National Natural Science Foundation of China (61991420, 61991421)
More Information
  • 摘要: 城市建筑区域叠掩、阴影严重,图像理解困难且干涉相位变化复杂紊乱,一直是InSAR处理的困难区域。SAR图像仿真能为图像理解和处理方法研究提供数据支撑,然而现有建筑区域SAR图像仿真方法大多无法获得具有相干性的干涉SAR图像对。该文提出了一种面向建筑区域的干涉SAR复图像对仿真方法,能够获得建筑的复数图像对、干涉相位图以及叠掩成分数目等信息,为城区干涉SAR处理及信息提取研究提供仿真数据支撑。同时,基于仿真中对相位变化规律的分析,提出叠掩区相位解缠时的基准确定方法,解决传统解缠方法面临的叠掩区域干涉相位不连续问题,进而反演建筑高程信息。最后,通过建模仿真结果与实际SAR图像和干涉相位的对比,验证了仿真方法的正确性,并对仿真及实际干涉相位进行解缠和高程反演处理,验证了该文高程反演方法的有效性。

     

  • 图  1  SAR图像对仿真流程

    Figure  1.  The simulation method for SAR image pair

    图  2  SAR图像仿真几何设定

    Figure  2.  The simulation geometry for SAR image

    图  3  散射点投影几何

    Figure  3.  The projection geometry of scattering points

    图  4  叠掩成分数目分析示意图

    Figure  4.  Illustration for the number of layover contributors

    图  5  叠掩区域散射点的角度关系

    Figure  5.  The angle of layover points

    图  6  叠掩成分数目计算流程

    Figure  6.  Calculation method for the number of layover contributors

    图  7  干涉SAR测量几何

    Figure  7.  InSAR measurement geometry

    图  8  叠掩掩膜图指导下的相位解缠流程

    Figure  8.  The phase-unwrapping method guided by the layover mask

    图  9  解缠相位基准确定

    Figure  9.  Determination of the unwrapped phase reference

    图  10  两栋建筑物的实际干涉SAR图像与相位和其光学图

    Figure  10.  The real SAR image pair, interferometric phase, and optical image of the two buildings

    图  11  建筑三维模型

    Figure  11.  3D model for the buildings

    图  12  建筑仿真图像

    Figure  12.  The simulation results of the buildings

    图  13  仿真图像与实际图像配准后伪彩色显示结果

    Figure  13.  The pseudo-color image for the registration result of the simulated and the real images

    图  14  叠掩成分数目分析

    Figure  14.  Analysis of the number of layover contributors

    图  15  对本文InSAR仿真数据的建筑高程反演结果

    Figure  15.  The elevation inversion results of the simulated images using our method

    图  16  TerraSAR-X重轨干涉SAR数据的建筑高程反演结果

    Figure  16.  The elevation inversion results of the TerraSAR-X InSAR images

    表  1  TerraSAR参数及仿真参数

    Table  1.   Parameters of TerraSAR images and simulation

    图像参数取值
    TerraSAR
    及仿真
    距离向分辨率(m)0.4547
    方位向分辨率(m)0.1670
    主图像下视角(°)54.52
    辅图像下视角(°)54.49
    仿真图像大小(距离,方位)(500, 600)
    主雷达位置(m)(0, 500160.3, –356368.6)
    基线向量(m)(51.52, –188.1, –238.0)
    相位噪声模型标准差为π/4的高斯随机噪声
    下载: 导出CSV

    表  2  建筑物高程反演结果

    Table  2.   The elevation inversion results of the buildings

    建筑序号三维模型建筑
    高度(m)
    仿真图像重建高度真实图像重建高度
    均值(m)标准差(m)均值(m)标准差(m)
    1100.5101.391.2099.754.48
    291.692.842.5693.692.31
    398.499.902.3599.103.17
    488.3\\\\
    下载: 导出CSV
  • [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.
  • 加载中
图(16) / 表(2)
计量
  • 文章访问数:  2143
  • HTML全文浏览量:  600
  • PDF下载量:  305
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-02-13
  • 修回日期:  2020-04-17
  • 网络出版日期:  2020-05-07
  • 刊出日期:  2020-04-01

目录

    /

    返回文章
    返回