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Laser & Optoelectronics Progress, Volume. 59, Issue 2, 0210018(2022)

Aerial Target Classification Algorithm Based on Double-Layer Feature Selection

Zhigang Su1,2、* and Xuemeng Wang1
Author Affiliations
  • 1College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
  • 2Sino-European Institute of Aviation Engineering, Civil Aviation University of China, Tianjin 300300, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (10)
    Equations (18)
    References (22)
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    Figures & Tables(10)
    Framework of air target feature selection and classification algorithm

    Fig. 1. Framework of air target feature selection and classification algorithm

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    Structure of ELM

    Fig. 2. Structure of ELM

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    Relationship between number of experimental repetitions and average score

    Fig. 3. Relationship between number of experimental repetitions and average score

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    Comparison of experimental effects of different transfer functions

    Fig. 4. Comparison of experimental effects of different transfer functions

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    Relationship between training error, test error and number of hidden layer neurons

    Fig. 5. Relationship between training error, test error and number of hidden layer neurons

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    Comparison of feature quantity and precision of each algorithm

    Fig. 6. Comparison of feature quantity and precision of each algorithm

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    Comparison of training time

    Fig. 7. Comparison of training time

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    • Table 1. Comparison of accuracy and standard deviation of different feature selection algorithms

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      Table 1. Comparison of accuracy and standard deviation of different feature selection algorithms

      AlgorithmPrecisionStandard deviation
      K-S test+De-relief99.78±0.02
      FCBF97.75±0.08

      EDA

      Lasso

      99.11

      95.10

      ±0.12

      ±0.06

    • Table 2. Comparison of classification performance of various classification algorithms

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      Table 2. Comparison of classification performance of various classification algorithms

      AlgorithmPrecision /%TPRFPR
      Ret-OSELM99.70.9960.016
      LSTM98.50.9830.036
      DNN97.80.9790.055
      Naive Bayes92.10.9350.081
      Decision tree95.60.9620.058

    • Table 3. Comparison of test time of different feature extraction algorithms

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      Table 3. Comparison of test time of different feature extraction algorithms

      AlgorithmTest time /ms
      TSFRESH extract features52.13
      TSFRESH extract+K-S test15.87

      TSFRESH extracts+K-S test+relief

      TSFRESH extracts+K-S test+De-relief

      2.11

      1.26

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    Zhigang Su, Xuemeng Wang. Aerial Target Classification Algorithm Based on Double-Layer Feature Selection[J]. Laser & Optoelectronics Progress, 2022, 59(2): 0210018

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    Paper Information

    Category: Image Processing

    Received: Jan. 12, 2021

    Accepted: Mar. 16, 2021

    Published Online: Dec. 23, 2021

    The Author Email: Zhigang Su (ssrsu@vip.sina.com)

    DOI:10.3788/LOP202259.0210018

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology