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Proceedings Paper

Matching algorithm of missile tail flame based on back-propagation neural network
Author(s): Da Huang; Shucai Huang; Yidong Tang; Wei Zhao; Wenhuan Cao
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Paper Abstract

This work presents a spectral matching algorithm of missile plume detection that based on neural network. The radiation value of the characteristic spectrum of the missile tail flame is taken as the input of the network. The network’s structure including the number of nodes and layers is determined according to the number of characteristic spectral bands and missile types. We can get the network weight matrixes and threshold vectors through training the network using training samples, and we can determine the performance of the network through testing the network using the test samples. A small amount of data cause the network has the advantages of simple structure and practicality. Network structure composed of weight matrix and threshold vector can complete task of spectrum matching without large database support. Network can achieve real-time requirements with a small quantity of data. Experiment results show that the algorithm has the ability to match the precise spectrum and strong robustness.

Paper Details

Date Published: 20 February 2018
PDF: 10 pages
Proc. SPIE 10697, Fourth Seminar on Novel Optoelectronic Detection Technology and Application, 1069702 (20 February 2018); doi: 10.1117/12.2305884
Show Author Affiliations
Da Huang, Air Force Engineering Univ. (China)
Shucai Huang, Air Force Engineering Univ. (China)
Yidong Tang, Air Force Engineering Univ. (China)
Wei Zhao, Air Force Engineering Univ. (China)
Wenhuan Cao, Air Force Engineering Univ. (China)


Published in SPIE Proceedings Vol. 10697:
Fourth Seminar on Novel Optoelectronic Detection Technology and Application
Weiqi Jin; Ye Li, Editor(s)

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