Generalized pseudopolar format algorithm for radar imaging with highly suboptimal aperture length

被引:7
|
作者
Han KuoYe [1 ,3 ]
Wang YanPing [1 ]
Chang XiangKe [2 ,3 ]
Tan WeiXian [1 ]
Hong Wen [1 ]
机构
[1] Chinese Acad Sci, Inst Elect, Sci & Technol Microwave Imaging Lab MITL, Beijing 100190, Peoples R China
[2] Chinese Acad Sci, ICMSEC, Beijing 100190, Peoples R China
[3] UCAS, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
pseudopolar format; epsilon-algorithm; convergence acceleration; suboptimal imaging; radar imaging; synthetic aperture radar (SAR);
D O I
10.1007/s11432-014-5224-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Different from conventional spaceborne or airborne synthetic aperture radar (SAR) with optimal aperture length, an imaging radar with highly suboptimal aperture length acquires the data in short bursts by a geometry spreading over a large range. A polarlike or pseudopolar format grid is introduced to sample data close to the resolution, which presents the design of a separable kernel for efficient FFT implementation. The proposed imaging algorithm formulates the reflectivity image of the target scene as an interpolation-free double image series expansion with two usual approximation-induced phase error terms being taken into account, whereby more generalized application scenarios with high frequency, large bandwidth or larger aperture length for imaging a target scene located within either the far-field or the near-field of the radar aperture are processable with high accuracy. In addition, convergence acceleration methods in computational mathematics are introduced to accelerate the convergence of the image series expansion, so as to make the algorithm more efficient. The proposed algorithm has been validated both qualitatively and quantitatively with an extensive collection of numerical simulations and field measurements of ground-based SAR (GB-SAR) data set.
引用
收藏
页码:1 / 15
页数:15
相关论文
共 50 条
  • [1] Generalized pseudopolar format algorithm for radar imaging with highly suboptimal aperture length
    KuoYe Han
    YanPing Wang
    XiangKe Chang
    WeiXian Tan
    Wen Hong
    Science China Information Sciences, 2015, 58 : 1 - 15
  • [2] Generalized pseudopolar format algorithm for radar imaging with highly suboptimal aperture length
    HAN KuoYe
    WANG YanPing
    CHANG XiangKe
    TAN WeiXian
    HONG Wen
    Science China(Information Sciences), 2015, 58 (04) : 63 - 77
  • [3] A Fast and Accurate Far-Field Pseudopolar Format Radar Imaging Algorithm
    Fortuny-Guasch, Joaquim
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2009, 47 (04): : 1187 - 1196
  • [4] Polar format algorithm of synthetic aperture radar imaging on spiral trajectory
    Li, Feng
    Yang, Wengu
    Wang, Zhou
    Yao, Di
    JOURNAL OF ENGINEERING-JOE, 2019, 2019 (19): : 5580 - 5583
  • [5] MIMO radar virtual aperture imaging based on fast polar format algorithm
    Wang, H.-Q. (haiqingw@126.com), 1600, China Spaceflight Society (34):
  • [6] Stepped-Frequency Synthetic Aperture Radar Imaging via Polar Format Algorithm
    Makarov, Pavel A.
    Arici, Mustafa
    2017 SENSOR SIGNAL PROCESSING FOR DEFENCE CONFERENCE (SSPD), 2017, : 193 - 197
  • [7] Polar format algorithm for circular synthetic aperture radar
    Lin Y.
    Tan W.-X.
    Hong W.
    Wang Y.-P.
    Wu Y.-R.
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2010, 32 (12): : 2802 - 2807
  • [8] Pseudopolar Format Matrix Description of Near-Range Radar Imaging and Fractional Fourier Transform
    Zou, Lilong
    Li, Ying
    Alani, Amir M.
    REMOTE SENSING, 2024, 16 (13)
  • [9] Sub-Aperture Polar Format Algorithm for Curved Trajectory Millimeter Wave Radar Imaging
    Liu, Yanqi
    Tao, Manyi
    Shi, Tianyue
    Wang, Jiping
    Wang, Jiahui
    Mao, Xinhua
    IEEE Transactions on Radar Systems, 2024, 2 : 67 - 83
  • [10] STUDY ON CONNOTATION OF GENERALIZED APERTURE RADAR IMAGING
    Wang, Tianyun
    Liu, Bing
    Wei, Qiang
    Kang, Kai
    Yu, Qinghua
    2019 18TH INTERNATIONAL CONFERENCE ON OPTICAL COMMUNICATIONS AND NETWORKS (ICOCN), 2019,