• Opto-Electronic Engineering
  • Vol. 46, Issue 7, 190082 (2019)
Pan Weijun, Duan Yingjie, Zhang Qiang*, Wu Zhengyuan, and Liu Haochen
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.12086/oee.2019.190082 Cite this Article
    Pan Weijun, Duan Yingjie, Zhang Qiang, Wu Zhengyuan, Liu Haochen. Research on aircraft wake vortex recognition using AlexNet[J]. Opto-Electronic Engineering, 2019, 46(7): 190082 Copy Citation Text show less
    References

    [1] Hallock J N, Holz.pfel F. A review of recent wake vortex re-search for increasing airport capacity[J]. Progress in Aerospace Sciences, 2018, 98: 27–36.

    [2] Gerz T, Holz.pfel F, Darracq D. Commercial aircraft wake vortices[J]. Progress in Aerospace Sciences, 2002, 38(3): 181–208.

    [3] Frehlich R, Sharman R. Maximum likelihood estimates of vor-tex parameters from simulated coherent Doppler Lidar data[J]. Journal of Atmospheric and Oceanic Technology, 2005, 22(2): 117–130.

    [4] Choroba P. Comprehensive study of the wake vortex pheno-mena to the assessment of its incorporation to ATM for safety and capacity improvements[D]. Slovakia: The University of Zi-lina, 2006.

    [5] Wei Z Q. The Research on modeling and simulation on flow field and safety spacing for wake vortex[D]. Tianjin: Civil Avia-tion University of China, 2008.

    [6] K.pp F, Rahm S, Smalikho I. Characterization of aircraft wake vortices by 2-μm pulsed Doppler lidar[J]. Journal of Atmos-pheric and Oceanic Technology, 2004, 21(2): 194–206.

    [7] Holz.pfel F, Gerz T, K.pp F, et al. Strategies for circulation evaluation of aircraft wake vortices measured by lidar[J]. Journal of Atmospheric and Oceanic Technology, 2003, 20(8): 1183–1195.

    [8] Barbaresco F, Jeantet A, Meier U. Wake vortex detection & monitoring by X-band doppler radar: paris orly radar campaign results[C]//Proceedings of 2007 IET International Conference on Radar Systems, Edinburgh, UK, 2007.

    [9] Barbaresco F, Meier U. Radar monitoring of a wake vortex: electromagnetic reflection of wake turbulence in clear air[J]. Comptes Rendus Physique, 2010, 11(9): 54–67.

    [10] Profeta A, Rodriguez A, Clouse H S. Convolutional neural networks for synthetic aperture radar classification[J]. Pro-ceedings of SPIE, 2006, 9843: 98430M.

    [11] Wu Y H, Hu Y H, Dai D C, et al. Research on the technique of aircraft wake vortex detection based on 1.5 μm doppler lidar[J]. Acta Photonica Sinica, 2011, 40(6): 811–817.

    [12] Li C, Liu J W, Zhao P E, et al. Correction method of tilt wind field of mobile wind lidar[J]. Laser Technology, 2017, 41(3): 385–390.

    [13] Arel I, Rose D C, Karnowski T P. Deep machine learning -a new frontier in artificial intelligence research [Research Fron-tier][J]. IEEE Computational Intelligence Magazine, 2010, 5(4): 13–18.

    [14] Yuan Q Z, Wei S J, Luo N. Research on SAR satellite target recognition system based on deep learning neural network[J]. Aerospace Shanghai, 2017, 34(5): 46–53.

    [15] Yin B C, Wang W T, Wang L C. Review of deep learning[J]. Journal of Beijing University of Technology, 2015, 41(1): 48–59.

    [16] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[C]//Proceedings of the 25th International Conference on Neural Information Processing Systems, South Lake Tahoe, USA: 2012: 1097–1105.

    [17] Zhang S H. Research on facial landmark localization based on deep convolutional neural network[D]. Wuhan: Huazhong Uni-versity of Science and Technology, 2016.

    [18] Hu Y H, Wu Y H. Study on the characteristic of aircraft wake vortex and lidar detection technique[J]. Infrared and Laser En-gineering, 2011, 40(6): 1063–1069.

    [19] Duan M, Wang G P, Niu C Y. Method of small sample size image recognition based on convolution neural network[J]. Computer Engineering and Design, 2018, 39(1): 224–229.

    [20] Dai W C, Jin L X, Li G N, et al. Real-time airplane detection algorithm in remote-sensing images based on improved YO-LOv3[J]. Opto-Electronic Engineering, 2018, 45(12): 180350.

    [21] Pan W J, Zhang Q Y, Zhang Q, et al. Identification method of aircraft wake vortex based on doppler lidar[J]. Laser Technol-ogy, 2019, 43(2): 233–237.

    Pan Weijun, Duan Yingjie, Zhang Qiang, Wu Zhengyuan, Liu Haochen. Research on aircraft wake vortex recognition using AlexNet[J]. Opto-Electronic Engineering, 2019, 46(7): 190082
    Download Citation