›› 2019, Vol. 39 ›› Issue (1): 32-.doi: 10.16708/j.cnki.1000-758X.2018.0064

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Research on spatial target structure recognition based on deep neural network

ZHOU Chi,LI Zhi,XU Can   

  1. 1Graduate School,Space Engineering University,Beijing101416,China 2Academy of Space and Command,Space Engineering University,Beijing101416,China
  • Online:2019-02-25 Published:2019-02-25

Abstract: The use of Radar Cross Section (RCS) sequences for spatial target structure recognition is an important part of space situational awareness. RCS sequence is easily affected by the target physical characteristics and attitude characteristics,and the nonstationary characteristics of the sequence signal are obvious. In this paper, deep neural network (DNN) algorithm was used to solve the problem of spatial target structural feature recognition. For the problem of feature extraction without distinguishing degree, fractal features were used to extract the fractal features of RCS sequences, and the Fisher′s decision rate was used for selecting traditional features. What′s more, the DNN algorithm and data processing process were introduced. Finally, a set of simulation test data were used to verify the algorithm. The analysis results show that the DNN algorithm is robust and accurate in solving the problem of using RCS sequence to identify the target structure.

Key words: Deep Neural Network, Radar Cross Section sequence, structural identification, fractal analysis, Fisher decision rate