Efficient 3D imaging method of MIMO radar for moving target

被引：0
|
作者：
Wang W. [1 ]
Hu Z. [1 ]
Yue J. [1 ]
机构：
[1] College of Automation, Harbin Engineering University, Harbin
来源：
Tongxin Xuebao/Journal on Communications | 2019年 / 40卷 / 07期
基金：
中央高校基本科研业务费专项资金资助; 中国国家自然科学基金;
关键词：
Doppler frequency; Method efficiency; MIMO radar; Moving target; Mutual coherence; Three-dimensional imaging;
D O I：
10.11959/j.issn.1000-436x.2019140
中图分类号：
学科分类号：
摘要：
When compressive sensing (CS) was used to achieve sparse imaging of moving targets, the Doppler frequency caused by motion will increase the processing dimension, change the center frequency of echo and worsen the mutual coherence property of measurement matrix. In order to improve the three-dimensional (3D) imaging performance of MIMO radar for moving targets, an efficient method was proposed. In each dimension, the distribution information of targets was searched respectively and a new low-dimensional measurement matrix was reconstructed accordingly, so the targets' area was narrowed down. At the same time, in order to optimize the mutual coherence property of measurement matrix, Bayesian method was used to optimize the velocity-dimensional projection matrix to reduce the strong mutual coherence brought by sampling of Doppler frequency, then the efficient sparse imaging could be achieved. The simulation results show that proposed method can improve the efficiency, accurate imaging performance with efficient. © 2019, Editorial Board of Journal on Communications. All right reserved.
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页码：38 / 47
页数：9
相关论文
共 21 条
  • [1] Bao Z., Xing M.D., Wang T., Radar Imaging Technology, pp. 24-30, (2010)
  • [2] Fishler E., Haimovich A., Blum R., MIMO radar: an idea whose time has come, IEET International Radar Conference, pp. 71-78, (2004)
  • [3] Zhu Y., Su Y., A type of M2-transmitter N2-recevier MIMO radar array and 3D imaging theory, Science China, 54, 10, pp. 2147-2157, (2011)
  • [4] Ding S., Tong N., Zhang Y., Super-resolution 3D imaging in MIMO radar using spectrum estimation theory, IET Radar Sonar & Navigation, 11, 2, pp. 304-312, (2017)
  • [5] Hu X., Tong N., Song B., Joint sparsity-driven three-dimensional imaging method for multiple-input multiple-output radar with sparse antenna array, IET Radar Sonar & Navigation, 11, 5, pp. 709-720, (2017)
  • [6] Welch L., Lower bounds on the maximum cross correlation of signals (Corresp.), IEEE Transaction Information Theory, 20, 3, pp. 397-399, (1974)
  • [7] Roberts W., Li J., Stoica P., MIMO radar angle-range-Doppler imaging, Radar Conference, pp. 1-6, (2009)
  • [8] Zhang H., Lu G., Yu H., Imaging of moving target for distributed MIMO radar using improved SBL technique, IEEE International Conference on Signal Processing, Communications and Computing, pp. 194-198, (2014)
  • [9] Dai L., Cui C., Yu J., Sensing matrix restriction method for compressed sensing radar, Wireless Personal Communications, 84, 1, pp. 605-621, (2015)
  • [10] Hong T., Bai H., Li S., An efficient algorithm for designing projection matrix in compressive sensing based on alternating optimization, Signal Processing, 125, C, pp. 9-20, (2016)
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