Optimal data acquisition in multi-pass geosynchronous SAR tomography

被引:3
|
作者
Hu, Cheng [1 ,2 ]
Zhang, Bin [1 ]
Dong, Xichao [1 ]
Li, Yuanhao [1 ]
Cui, Chang [1 ]
机构
[1] Beijing Inst Technol, Sch Informat & Elect, Radar Res Lab, Beijing, Peoples R China
[2] Beijing Inst Technol, Minist Educ, Key Lab Elect & Informat Technol Satellite Nav, Beijing, Peoples R China
来源
JOURNAL OF ENGINEERING-JOE | 2019年 / 2019卷 / 20期
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
D O I
10.1049/joe.2019.0383
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Geosynchronous SAR tomography (GEO TomoSAR) techniques exploit multi-pass SAR acquisitions of the same scene, taken with slightly different view angles, and allow generating fully 3D images. Compared to low earth orbit (LEO) SAR case, GEO SAR has the advantages of shorter revisit time period and wider coverage, which can greatly shorten the data acquisition time, improve the coherence of collected data and effectively improve the 3D imaging accuracy. However, GEO SAR has curved trajectories and un-parallel repeated trajectories, which introduce the along-track component of the spatial baseline. The obtained GEO TomoSAR data based on the data acquisition method using in LEO TomoSAR have the significant rotation-induced decorrelation. Thus, the imaging performance in the elevation is severely degraded. In this paper, we first analyse the feasibility of GEO TomoSAR to achieve 3D imaging. In view of the special issues existing in GEO TomoSAR, we adopt an optimal minimal rotation-induced decorrelation data acquisition method to obtain repeated trajectories data, which can effectively improve the coherence between the collected data. Then, performance of imaging in elevation was analysed based on the spatial baseline distribution. Finally, the feasibility and validity of GEO TomoSAR techniques are validated through computer simulation.
引用
收藏
页码:6359 / 6363
页数:5
相关论文
共 50 条
  • [1] Multi-Pass Stepped Frequency Imaging of Geosynchronous SAR
    Wang Zhiqian
    Li Chunsheng
    Yu Ze
    Wang Yan
    CONFERENCE PROCEEDINGS OF 2013 ASIA-PACIFIC CONFERENCE ON SYNTHETIC APERTURE RADAR (APSAR), 2013, : 408 - 411
  • [2] Range resolution limits in multi-pass SAR data processing
    Fornaro, G
    Pascazio, V
    Schirinzi, G
    IGARSS 2002: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS: REMOTE SENSING: INTEGRATING OUR VIEW OF THE PLANET, 2002, : 182 - 184
  • [3] Optimal Data Acquisition and Height Retrieval in Repeat-Track Geosynchronous SAR Interferometry
    Hu, Cheng
    Li, Yuanhao
    Dong, Xichao
    Long, Teng
    REMOTE SENSING, 2015, 7 (10): : 13367 - 13389
  • [4] DATA COLLECTION STRATEGIES FOR HIGH QUALITY MULTI-PASS SAR CCD IMAGES
    Wang, Yuanyuan
    Huang, Yulin
    Zha, Yuebo
    Pu, Wei
    Yang, Jianyu
    2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014, : 1843 - 1846
  • [5] Change detection for multi-polarization, multi-pass SAR
    Novak, LM
    Algorithms for Synthetic Aperture Radar Imagery XII, 2005, 5808 : 234 - 246
  • [6] Three-Dimensional Object Reconstruction from Sparse Multi-Pass SAR Data
    Scarnati, Theresa
    Jamora, J. R.
    ALGORITHMS FOR SYNTHETIC APERTURE RADAR IMAGERY XXVIII, 2021, 11728
  • [7] Multi-channel spectral analysis of multi-pass acquisition measurements
    Leclere, Q.
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (05) : 1415 - 1422
  • [8] A new framework for multi-pass SAR Interferometry with distributed targets
    Guarnieri, Andrea Monti
    Tebaldini, Stefano
    IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 5289 - 5293
  • [9] A False Alarm Mitigation Method for Multi-pass SAR CCD
    Kou Xiuli
    Chen Jie
    Li Jun
    Wang Guanyong
    Feng Liang
    Wang Zhirui
    2023 6TH INTERNATIONAL CONFERENCE ON ELECTRONICS AND ELECTRICAL ENGINEERING TECHNOLOGY, EEET 2023, 2023, : 6 - 10
  • [10] Optimal Learning for Multi-pass Stochastic Gradient Methods
    Lin, Junhong
    Rosasco, Lorenzo
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 29 (NIPS 2016), 2016, 29