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Citation: Wei WANG, Ziying HU, Linshu GONG. Adaptive Off-grid Calibration Method for MIMO Radar 3D Imaging[J]. Journal of Electronics and Information Technology, ;2019, 41(6): 1294-1301. doi: 10.11999/JEIT180145 shu

Adaptive Off-grid Calibration Method for MIMO Radar 3D Imaging

  • Corresponding author: Wei WANG, wangwei407@hrbeu.edu.cn
  • Received Date: 2018-02-02
    Accepted Date: 2019-03-22
    Available Online: 2019-06-01

Figures(7) / Tables(1)

  • In Compressive Sensing (CS) imaging algorithms, the true targets usually can not locate on the pre-defined grids exactly. Such Off-grid problems result in mismatch between true echo and measurement matrix, which seriously degrades the performance of radar imaging. An adaptive calibration method is proposed to solve the off-grid problems in MIMO radar Three-Dimensional (3D) imaging. Bayesian probability density functions can be constructed based on the sparse echo model of Off-grid targets, and the Maximum A Posteriori (MAP) method is used to obtain sparse imaging with mismatch errors. Compared with the traditional methods, the proposed method can make full use of mismatch parameters’ priori information and adaptively update the parameters, which can reduce the influence of mismatch errors, and achieve high-precision estimation for sparse targets and noise power. Finally, the simulation results confirm that the proposed method can effectively optimize mismatch errors with accurate and stable imaging performance.
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    1. [1]

      保铮, 邢孟道, 王彤. 雷达成像技术[M]. 北京: 电子工业出版社, 2010: 24–30.

    2. [2]

      FISHLER E, HAIMOVICH A, BLUM R, et al. MIMO radar: An idea whose time has come[C]. Proceedings of 2004 IEEE Radar Conference, Philadelphia, USA, 2004: 71–78.

    3. [3]

      DUARTE M F and ELDAR Y C. Structured compressed sensing: From theory to applications[J]. IEEE Transactions on Signal Processing, 2011, 59(9): 4053–4085. doi: 10.1109/TSP.2011.2161982

    4. [4]

      谢晓春. 压缩感知理论在雷达成像中的应用研究[D]. [博士论文], 中国科学院空间科学与应用研究中心, 2010.
      XIE Xiaochun. Study on the appilcation of compressive sensing in radar imaging[D]. [Ph.D. dissertation], The Center for Space Science and Applied Research, Chinese Academy of Sciences, 2010.

    5. [5]

      ZHU Yutao and SU Yi. A type of M2-transmitter N2-receiver MIMO radar array and 3D imaging theory[J]. Science China Information Sciences, 2011, 54(10): 2147–2157. doi: 10.1007/s11432-011-4400-y

    6. [6]

      HU Xiaowei, TONG Ningning, WANG Jianye, et al. Matrix completion-based MIMO radar imaging with sparse planar array[J]. Signal Processing, 2017, 131: 49–57. doi: 10.1016/j.sigpro.2016.07.034

    7. [7]

      HU Xiaowei, TONG Ninging, ZHANG Yongshun, et al. Multiple-input–multiple-output radar super-resolution three-dimensional imaging based on a dimension-reduction compressive sensing[J]. IET Radar, Sonar & Navigation, 2016, 10(4): 757–764. doi: 10.1049/iet-rsn.2015.0345

    8. [8]

      DING Shanshan, TONG Ninging, ZHANG Yongshun, et al. Super-resolution 3D imaging in MIMO radar using spectrum estimation theory[J]. IET Radar, Sonar & Navigation, 2017, 11(2): 304–312. doi: 10.1049/iet-rsn.2016.0233

    9. [9]

      HU Xiaowei, TONG Ningning, SONG Baojun, et al. Joint sparsity-driven three-dimensional imaging method for multiple-input multiple-output radar with sparse antenna array[J]. IET Radar, Sonar & Navigation, 2017, 11(5): 709–720. doi: 10.1049/iet-rsn.2016.0108

    10. [10]

      CANDÈS E and ROMBERG J. Sparsity and incoherence in compressive sampling[J]. Inverse Problems, 2007, 23(3): 969–985. doi: 10.1088/0266-5611/23/3/008

    11. [11]

      BAO Qian, HONG Wen, HAN Kuoye, et al. Off-grid effect free imaging method based on improved OMP approach for DLLA 3D SAR[C]. Proceedings of 2015 IET International Radar Conference, Hangzhou, 2015: 1–4.

    12. [12]

      BAO Qian, HAN Kuoye, PENG Xueming, et al. DLSLA 3-D SAR imaging algorithm for off-grid targets based on pseudo-polar formatting and atomic norm minimization[J]. Science China Information Sciences, 2016, 59(6): 062310. doi: 10.1007/s11432-015-5477-5

    13. [13]

      LIU Changchang, DING Li, and CHEN Weidong. A correction and generalization to the sparse learning via iterative minimization method for target off the grid in MIMO radar imaging[C]. Proceedings of 2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 2012: 895–899.

    14. [14]

      HE Xuezhi, LIU Changchang, LIU Bo, et al. Sparse frequency diverse MIMO radar imaging for off-grid target based on adaptive iterative MAP[J]. Remote Sensing, 2013, 5(2): 631–647. doi: 10.3390/rs5020631

    15. [15]

      丁丽. MIMO雷达稀疏成像的失配问题研究[D]. [博士论文], 中国科学技术大学, 2014.
      DING Li. Research on observation matrix mismatch for MIMO radar sparse imaging[D]. [Ph.D. dissertation], University of Science and Technology of China, 2014.

    16. [16]

      王天云, 陆新飞, 丁丽, 等. 基于贝叶斯压缩感知的FD-MIMO雷达Off-Grid目标稀疏成像[J]. 电子学报, 2016, 44(6): 1314–1321. doi: 10.3969/j.issn.0372-2112.2016.06.008
      WANG Tianyun, LU Xinfei, DING Li, et al. Bayesian compressive sensing-based sparse imaging for Off-Grid target in frequency diverse MIMO radar[J]. Acta Electronica Sinica, 2016, 44(6): 1314–1321. doi: 10.3969/j.issn.0372-2112.2016.06.008

    17. [17]

      王超宇, 贺亚鹏, 胡恒, 等. 基于贝叶斯压缩感知的噪声MIMO雷达目标成像[J]. 南京理工大学学报, 2013, 37(2): 262–268. doi: 10.3969/j.issn.1005-9830.2013.02.011
      WANG Chaoyu, HE Yapeng, HU Heng, et al. Noise MIMO radar target imaging based on Bayesian compressive sensing[J]. Journal of Nanjing University of Science and Technology, 2013, 37(2): 262–268. doi: 10.3969/j.issn.1005-9830.2013.02.011

    18. [18]

      JI Shihao, XUE Ya, and CARIN L. Bayesian compressive sensing[J]. IEEE Transactions on Signal Processing, 2008, 56(6): 2346–2356. doi: 10.1109/TSP.2007.914345

    19. [19]

      王伟, 张斌, 李欣. 基于混合匹配追踪算法的MIMO雷达稀疏成像方法[J]. 电子与信息学报, 2016, 38(10): 2415–2422. doi: 10.11999/JEIT151453
      WANG Wei, ZHANG Bin, and LI Xin. An imaging method for MIMO radar based on hybrid matching pursuit[J]. Journal of Electronics &Information Technology, 2016, 38(10): 2415–2422. doi: 10.11999/JEIT151453

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