20 February 2018 Matching algorithm of missile tail flame based on back-propagation neural network
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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.
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Da Huang, Da Huang, Shucai Huang, Shucai Huang, Yidong Tang, Yidong Tang, Wei Zhao, Wei Zhao, Wenhuan Cao, 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); doi: 10.1117/12.2305884; https://doi.org/10.1117/12.2305884

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