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Flight Target Recognition via Neural Networks and Information Fusion

  • Yang ZhangEmail author
  • Zhenzhen Duan
  • Jian Zhang
  • Jing Liang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 516)

Abstract

The purpose of this research is to increase the target recognition rate by means of neural networks and feature fusion. We analyze the performance of different recognition methods (Bayesian classifier, support vector machine (SVM), and neural networks) based on high-resolution range profile (HRRP). The result shows the superiority of neural networks to Bayesian classifier and SVM in classification. We apply multi-source feature fusion to target recognition based on neural networks. The results show that, in certain cases, the target recognition ratio using fusion feature is higher than that of HRRP only.

Keywords

Target recognition Neural networks Information fusion 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (61671138, 61731006), and was partly supported by the 111 Project No. B17008.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Yang Zhang
    • 1
    Email author
  • Zhenzhen Duan
    • 1
  • Jian Zhang
    • 1
  • Jing Liang
    • 1
  1. 1.University of Electronic Science and Technology of China Information and Communication EngineeringChengduChina

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