State Prediction of Missile Guidance System Based on FA-RBF Neural Network

LI Haijun; WANG Wenshuang; ZHAO Jianzhong

doi:10.15892/j.cnki.djzdxb.2023.01.001

Journal of Projectiles, Rockets, Missiles and Guidance >

2023 , Vol. 43 >Issue 1: 1 - 7

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2023.01.001

State Prediction of Missile Guidance System Based on FA-RBF Neural Network

LI Haijun ,
WANG Wenshuang ,
ZHAO Jianzhong

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Naval Aviation University, Yantai 264001, Shandong, China

Received date: 2022-07-20

Online published: 2025-02-01

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Abstract

Missile guidance system is a relatively high failure rate part of missile components. The prediction and preventive maintenance of its state are the key links to maintain the integrity rate of missiles and ensure operational efficiency. Missile guidance system has the characteristics of complex internal composition, many test indicators, and difficult to determine the system state. In order to predict the state of missile guidance system quickly and accurately, a state prediction method based on FA-RBF neural network is proposed. According to the system test index data given by the automatic test equipment, this method uses the factor analysis(FA) method to reduce the dimension of the test index data, obtain the potential key factors, and calculate the factor score. Then take factor score as the input and the internal measuring points that can reflect the system state as the output to establish the training samples. Radial basis function (RBF) neural network is used to predict the state of missile guidance system. Finally, an example is given to illustrate the practicality and effectiveness of the method.

Key words： missile guidance system; data collection; factor analysis; artificial neural network; radial basis function (RBF)

Cite this article

LI Haijun , WANG Wenshuang , ZHAO Jianzhong . State Prediction of Missile Guidance System Based on FA-RBF Neural Network[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2023 , 43(1) : 1 -7 . DOI: 10.15892/j.cnki.djzdxb.2023.01.001

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