Matching algorithm of missile tail flame based on back-propagation neural network

Da Huang; Shucai Huang; Yidong Tang; Wei Zhao; Wenhuan Cao

doi:10.1117/12.2305884

20 February 2018 Matching algorithm of missile tail flame based on back-propagation neural network

Da Huang, Shucai Huang, Yidong Tang, Wei Zhao, Wenhuan Cao

Proceedings Volume 10697, Fourth Seminar on Novel Optoelectronic Detection Technology and Application; 1069702 (2018) https://doi.org/10.1117/12.2305884
Event: Fourth Seminar on Novel Optoelectronic Detection Technology and Application, 2017, Nanjing, China

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.

Citation Download Citation

Da Huang, Shucai Huang, Yidong Tang, Wei Zhao, and Wenhuan Cao "Matching algorithm of missile tail flame based on back-propagation neural network", Proc. SPIE 10697, Fourth Seminar on Novel Optoelectronic Detection Technology and Application, 1069702 (20 February 2018); https://doi.org/10.1117/12.2305884

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available