226 / 2020-01-03 01:28:00
Aircraft Target Classification Based on CNN
CNN; Micro-Doppler; Aircraft Target,; Recognition
全文录用
Qingyuan Zhao / Beijing Insititute of Radio Measurement, China
In this paper, we applied the idea of deep learning to aircraft targets recognition based on time-frequency diagram. Firstly we introduced application of Convolutional Neural Network (CNN), and the methods of radar target recognition. Secondly, Short Time Fourier Transformation (STFT) was introduced. Thirdly, the structure of improved LeNet CNN was described, considering the character of radar echo wave. Fourthly, 4 kinds of aircraft targets were introduced. Then, the algorithm based on CNN and STFT was validated based on measured data, and was compared with Support Vector Machine (SVM). The accuracy rate could reaches up to 99.98%, 25% higher than SVM. Finally, we summarized advantages of the method proposed in this paper and give the suggestion in engineering application.
重要日期
  • 会议日期

    06月08日

    2020

    06月11日

    2020

  • 01月12日 2020

    初稿截稿日期

  • 04月15日 2020

    提前注册日期

  • 12月31日 2020

    注册截止日期

主办单位
IEEE Signal Processing Society
承办单位
Zhejiang University
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