Volume 5 Issue 1
Feb.  2016
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Article Navigation >  Journal of Radars  > 2016  >  5(1): 109-117
Li Liechen, Li Daojing, Huang Pingping. Airship Sparse Array Antenna Radar Real Aperture Imaging Based on Compressed Sensing and Sparsity in Transform Domain[J]. Journal of Radars, 2016, 5(1): 109-117. doi: 10.12000/JR14159
Citation: Li Liechen, Li Daojing, Huang Pingping. Airship Sparse Array Antenna Radar Real Aperture Imaging Based on Compressed Sensing and Sparsity in Transform Domain[J]. Journal of Radars, 2016, 5(1): 109-117. doi: 10.12000/JR14159
shu

Airship Sparse Array Antenna Radar Real Aperture Imaging Based on Compressed Sensing and Sparsity in Transform Domain

doi: 10.12000/JR14159
  • 1.

    (Science and Technology on Microwave Imaging Laboratory, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China)

  • 2.

    (University of Chinese Academy of Sciences, Beijing 100049, China)

  • 3.

    (Radar Research Institute, Inner Mongolia University of Technology, Hohhot 010051, China)

Funds:

The National Natural Science Foundation of China (61271422, 61201433)

  • Received Date: 2014-12-24
  • Rev Recd Date: 2015-04-28
  • Publish Date: 2016-02-28
    Abstract
  • A conformal sparse array based on combined Barker code is designed for airship platform. The performance of the designed array such as signal-to-noise ratio is analyzed. Using the hovering characteristics of the airship, interferometry operation can be applied on the real aperture imaging results of two pulses, which can eliminate the random backscatter phase and make the image sparse in the transform domain. Building the relationship between echo and transform coefficients, the Compressed Sensing (CS) theory can be introduced to solve the formula and achieving imaging. The image quality of the proposed method can reach the image formed by the full array imaging. The simulation results show the effectiveness of the proposed method.

     

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    • References(20)
  • [1]
    Barbier C, Delaur B, and Lavie A. Strategic research agenda for high-altitude aircraft and airship remote sensing applications[C]. USE-High Altitude Aircrafts and Airships Workshop, Antwerp, Belgium, 2006: 44-49.
    [2]
    李道京, 侯颖妮, 滕秀敏, 等. 稀疏阵列天线雷达技术及其应用[M]. 北京: 科学出版社, 2014: 9-40. Li Dao-jing, Hou Ying-ni, Teng Xiu-min, et al.. Sparse A r r a y A n t e n n a R a d a r I m a g i n g T e c h n o l o g y a n d Application[M]. Beijing: Science Press, 2014: 9-40.
    [3]
    Donoho D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.
    [4]
    Candes E and Romberg J. Sparsity and incoherence in compressive sampling[J]. Inverse Problems, 2007, 23(3): 969-988.
    [5]
    滕秀敏, 李道京. 艇载共形稀疏阵列天线雷达成像研究[J]. 电 波科学学报, 2012, 27(4): 644-649, 656.
    [6]
    Teng Xiu-min and Li Dao-jing. Study on airship conformal sparse array radar imaging[J]. Chinese Journal of Radio Sciences, 2012, 27(4): 644-649, 656. Zhu X X and Bamler R. Superresolving SAR tomography for multidimensional imaging of urban areas: compressive sensing-based TomoSAR inversion[J]. Signal Processing Magazine, 2014, 31(4): 51-58.
    [7]
    吴一戎, 洪文, 张冰尘, 等. 稀疏微波成像研究进展[J]. 雷达学 报, 2014, 3(4): 383-395. Wu Yi-rong, Hong Wen, Zhang Bing-chen, et al.. Current developments of sparse microwave imaging[J]. Journal of Radars, 2014, 3(4): 383-395.
    [8]
    Zhang L, Xing M, Qiu C-W, et al.. Achieving higher resolution ISAR imaging with limited pulses via compressed sampling[J]. IEEE Geoscience and Remote Sensing Letters, 2009, 6(3): 567-571.
    [9]
    李烈辰, 李道京. 基于压缩感知的连续场景稀疏阵列SAR三维 成像[J]. 电子与信息学报, 2014, 36(9): 2166-2172. Li Lie-chen and Li Dao-jing. Sparse array SAR 3D imaging for continuous scene based on compressed sensing[J]. Journal of Electronics Information Technology, 2014, 36(9): 2166-2172.
    [10]
    杨波. 一种设计组合巴克码脉冲压缩旁瓣抑制滤波器的新方法[J]. 现代雷达, 2001, 23(5): 41-45. Yang Bo. A new method for designing range-sidelobe suppression filter for combined Barker code[J]. Modern Radar, 2001, 23(5): 41-45.
    [11]
    Li L and Li D. Airship sparse array antenna radar performance analysis[C]. 2013 IEEE International Geoscience Remote Sensing Symposium, Melbourne, Australia, 2013: 628-631.
    [12]
    Li D, Zhang Q, Li L, et al.. Sparsity analysis of SAR signal and three-dimensional imaging of sparse array SAR[C]. 2013
    [13]
    IEEE International Geoscience Remote Sensing Symposium, Melbourne, Australia, 2013: 891-894. 张清娟, 李道京. 干涉SAR图像数据压缩[J]. 中国科学院研究 生院学报, 2013, 30(3): 380-386. Zhang Qing-juan and Li Dao-jing. InSAR imaging data compression[J]. Journal of Graduate University of Chinese Academy of Sciences, 2013, 30(3): 380-386.
    [14]
    Li L, Li D, and Pan Z. InSAR signal sparse sampling and processing based on compressed sensing[C]. 10th European Conference on Synthetic Aperture Radar, Berlin, Germany, 2014: 1041-1044.
    [15]
    Xu G, Xing M D, Xia X G, et al.. Sparse regularization of interferometric phase and amplitude for InSAR image formation based on Bayesian representation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(4): 2123-2136.
    [16]
    Zeng J, Fang J, and Xu Z. Sparse SAR imaging based on L1/2 regularization[J]. SCIENCE CHINA Information Sciences, 2012, 55(8): 1755-1775.
    [17]
    Zeng J, Xu Z, Zhang B, et al.. Accelerated L1/2 regularization based SAR imaging via BCR and reduced Newton skills[J]. Signal Processing, 2013, 93(7): 1831-1844.
    [18]
    辛肖明, 陈琼. m序列优选对及平衡Gold码序列[J]. 北京理工 大学学报, 1990, 10(4): 106-113. Xin Xiao-ming and Chen Qiong. Optimum m-sequence pairs and balanced gold group[J]. Journal of Beijing Institute of Technology, 1990, 10(4): 106-113.
    [19]
    Kim J H, Younis M, and Moreira A. A novel OFDM chirp waveform scheme for use of multiple transmitters in SAR[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 6(3): 568-572.
    [20]
    Wang W Q. MIMO SAR OFDM chirp waveform diversity design with random matrix modulation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(3): 1615-1625.
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