DocumentCode :
641747
Title :
Radar emitter signal recognition based on time-frequency analysis
Author :
Yang, L.B. ; Zhang, Sasa ; Xiao, Baihua
Author_Institution :
Res. Inst. of Electron. Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2013
fDate :
14-16 April 2013
Firstpage :
1
Lastpage :
4
Abstract :
The extraction of radar emitter identification is very important to distinct the correct target. Up to now, many corresponding methods are proposed. But most of it has the problems of low recognition rate and not adapting to low SNR environment. In the paper, a novel method is proposed. The approach utilizes time-frequency analysis methods and singular value distribution(SVD) to extract the singular values of signal, making it be the feature vector., and neural network based classifiers were designed to identify radar emitter signals automatically. The experimental results show that it can achieve a satisfying accurate recognition rate when signal-to-noise rate varies in a large range. It is proved to be valid and practical approach.
Keywords :
radar signal processing; time-frequency analysis; neural network based classifiers; radar emitter identification; radar emitter signal recognition; radar emitter signals; signal-to-noise rate; singular value distribution; time-frequency analysis methods; LVQ neural networks; Radar emitter identification; SVD; WVD; time-frequency analysis;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Radar Conference 2013, IET International
Conference_Location :
Xi´an
Electronic_ISBN :
978-1-84919-603-1
Type :
conf
DOI :
10.1049/cp.2013.0335
Filename :
6624499
Link To Document :
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