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Study of Radar Target Range Profile Recognition Algorithm Based on Optimized Neural Network

  • Xiaokang Guo
  • Tao Jian
  • Yunlong Dong
  • Xiaolong Chen
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 251)

Abstract

Neural network as an important aspect of artificial intelligence has received extensive research and long-term development. Radar target range profile recognition is a commonly used method in radar target recognition, in this paper, it is combined with neural network. The LVQ (Learning Vector Quantization) neural network has excellent classification and identification capabilities. This paper applies it to radar target one-dimensional range image recognition and achieves good results. This paper studies the problem of LVQ neural network sensitive to initial connection weights, and uses PSO (Particle Swarm Optimization) algorithm to optimize it of recognition classification. The experimental results show that the study of radar target range profile recognition algorithm based on optimized neural network can overcome the sensitivity of the LVQ neural network to the initial weight and improve its recognition ability.

Keywords

1-D range profile recognition LVQ (Learning Vector Quantization) PSO (Particle Swarm Optimization) 

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018

Authors and Affiliations

  • Xiaokang Guo
    • 1
  • Tao Jian
    • 1
  • Yunlong Dong
    • 1
  • Xiaolong Chen
    • 1
  1. 1.Research Institute of Information FusionNaval Aviation UniversityYantaiChina

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