Advanced Search
Volume 42 Issue 7
Jul.  2020
Turn off MathJax
Article Contents
Houhong XIANG, Baixiao CHEN, Ting YANG, Minglei YANG. Low-elevation DOA Estimation for VHF Radar Based on Multi-frame Phase Feature Enhancement[J]. Journal of Electronics & Information Technology, 2020, 42(7): 1581-1589. doi: 10.11999/JEIT190432
Citation: Houhong XIANG, Baixiao CHEN, Ting YANG, Minglei YANG. Low-elevation DOA Estimation for VHF Radar Based on Multi-frame Phase Feature Enhancement[J]. Journal of Electronics & Information Technology, 2020, 42(7): 1581-1589. doi: 10.11999/JEIT190432

Low-elevation DOA Estimation for VHF Radar Based on Multi-frame Phase Feature Enhancement

doi: 10.11999/JEIT190432
Funds:  The Natural Science Foundation of China (61571344, 61971323), The Fundamental Research Funds for the Central University, Innovation Fund of Xidian Univerisity
  • Received Date: 2019-06-13
  • Rev Recd Date: 2019-10-08
  • Available Online: 2020-02-05
  • Publish Date: 2020-07-23
  • For the DOA estimation problem of low-elevation target of VHF radar, a new multi-frame phase feature enhancement based method is proposed, which solves effectively the phase feature ambiguity of direct signal, and thus improves the accuracy of DOA estimation. By learning the complex mapping relationship between the phase distribution of the multi-frame data and ideal phase distribution of the direct signal, the fuzzy phase information is enhanced and is used to reconstruct a new data matrix with original amplitude information. The DOA is estimated by conventional methods using new data matrix, which effectively improves the DOA estimation accuracy of the low-elevation target. The effectiveness of proposed method is validated by computer simulation experiments and real data, and it shows higher accuracy compared with physics-driven methods including MUSIC method and state-of-the-art data-driven method including feature reversal and Support Vector Regression (SVR).

  • loading
  • 朱伟. 米波数字阵列雷达低仰角测高方法研究[D]. [博士论文], 西安电子科技大学, 2013.

    ZHU Wei. Study on low-angle altitude measurement in VHF Radar[D]. [Ph.D. dissertation], Xidian University, 2013.
    郑轶松. 米波阵列雷达低仰角测高若干问题研究[D]. [博士论文], 西安电子科技大学, 2017.

    ZHENG Yisong. Study on some issues of low-angle altitude measurement for VHF array radar[D]. [Ph.D. dissertation], Xidian University, 2017.
    李存勖. 米波雷达低仰角测高相关问题研究[D]. [博士论文], 西安电子科技大学, 2018.

    LI Cunxu. Study on some issues of altitude measurement of low-angle target for VHF array radar[D]. [Ph.D. dissertation], Xidian University, 2018.
    陈伯孝, 胡铁军, 郑自良, 等. 基于波瓣分裂的米波雷达低仰角测高方法及其应用[J]. 电子学报, 2007, 35(6): 1021–1025. doi: 10.3321/j.issn:0372-2112.2007.06.003

    CHEN Baixiao, HU Tiejun, ZHENG Ziliang, et al. Method of altitude measurement based on beam Split in VHF radar and its application[J]. Acta Electronica Sinica, 2007, 35(6): 1021–1025. doi: 10.3321/j.issn:0372-2112.2007.06.003
    ZHU Wei and CHEN Baixiao. Altitude measurement based on terrain matching in VHF array radar[J]. Circuits, Systems, and Signal Processing, 2013, 32(2): 647–662. doi: 10.1007/s00034-012-9472-4
    郑轶松, 陈伯孝. 米波雷达低仰角目标多径模型及其反演方法研究[J]. 电子与信息学报, 2016, 38(6): 1468–1474. doi: 10.11999/JEIT151013

    ZHENG Yisong and CHEN Baixiao. Multipath model and inversion method for low-angle target in very high frequency radar[J]. Journal of Electronics &Information Technology, 2016, 38(6): 1468–1474. doi: 10.11999/JEIT151013
    SCHMIDT R. Multiple emitter location and signal parameter estimation[J]. IEEE Transactions on Antennas and Propagation, 1986, 34(3): 276–280. doi: 10.1109/TAP.1986.1143830
    ROY R and KAILATH T. ESPRIT-estimation of signal parameters via rotational invariance techniques[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1989, 37(7): 984–995. doi: 10.1109/29.32276
    ZISKIND I and WAX M. Maximum likelihood localization of multiple sources by alternating projection[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1988, 36(10): 1553–1560. doi: 10.1109/29.7543
    CHOI Y H. Alternating projection for maximum-likelihood source localization using eigendecomposition[J]. IEEE Signal Processing Letters, 1999, 6(4): 73–75. doi: 10.1109/97.752057
    WU Bo, LI Kehuang, GE Fengpei, et al. An end-to-end deep learning approach to simultaneous speech dereverberation and acoustic modeling for robust speech recognition[J]. IEEE Journal of Selected Topics in Signal Processing, 2017, 11(8): 1289–1300. doi: 10.1109/JSTSP.2017.2756439
    WU Bo, LI Kehuang, YANG Minglei, et al. A reverberation-time-aware approach to speech dereverberation based on deep neural networks[J]. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2017, 25(1): 102–111. doi: 10.1109/TASLP.2016.2623559
    XIANG Houhong, CHEN Baixiao, YANG Minglei, et al. Altitude measurement based on characteristics reversal by deep neural network for VHF radar[J]. IET Radar, Sonar & Navigation, 2019, 13(1): 98–103. doi: 10.1049/iet-rsn.2018.5121
    WU Liuli and HUANG Zhitao. Coherent SVR learning for wideband direction-of-arrival estimation[J]. IEEE Signal Processing Letters, 2019, 26(4): 642–646. doi: 10.1109/LSP.2019.2901641
    WERBOS P J. Backpropagation through time: What it does and how to do it[J]. Proceedings of the IEEE, 1990, 78(10): 1550–1560. doi: 10.1109/5.58337
    LECUN Y, BOSER B, DENKER J S, et al. Backpropagation applied to handwritten zip code recognition[J]. Neural Computation, 1989, 1(4): 541–551. doi: 10.1162/neco.1989.1.4.541
    KINGMA D P and BA J. Adam: A method for stochastic optimization[J]. arXiv: 2014, 1412.6980.
    SRIVASTAVA N, HINTON G, KRIZHEVSKY A, et al. Dropout: A simple way to prevent neural networks from overfitting[J]. Journal of Machine Learning Research, 2014, 15(1): 1929–1958.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(25)  / Tables(3)

    Article Metrics

    Article views (2216) PDF downloads(85) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return