Seismic signal recognition using improved BP neural network and combined feature extraction method

Seismic signal is generally employed in moving target monitoring due to its robust characteristic. A recognition method for vehicle and personnel with seismic signal sensing system was proposed based on improved neural network. For analyzing the seismic signal of the moving objects, the seismic sign...

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Bibliographic Details
Published inJournal of Central South University Vol. 21; no. 5; pp. 1898 - 1906
Main Authors Peng, Zhao-qin, Cao, Chun, Huang, Jiao-ying, Liu, Qiu-sheng
Format Journal Article
LanguageEnglish
Published Heidelberg Central South University 01.05.2014
Subjects
Engineering
Metallic Materials
seismic signal
BP neural network
signal identification
feature extraction
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Summary:Seismic signal is generally employed in moving target monitoring due to its robust characteristic. A recognition method for vehicle and personnel with seismic signal sensing system was proposed based on improved neural network. For analyzing the seismic signal of the moving objects, the seismic signal of person and vehicle was acquisitioned from the seismic sensor, and then feature vectors were extracted with combined methods after filter processing. Finally, these features were put into the improved BP neural network designed for effective signal classification. Compared with previous ways, it is demonstrated that the proposed system presents higher recognition accuracy and validity based on the experimental results. It also shows the effectiveness of the improved BP neural network.
ISSN:2095-2899
2227-5223
DOI:10.1007/s11771-014-2136-8