文章基本信息

标题：The Improved Recognition Method of Radiation Signal under the Condition of Unstable SNR
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作者：Yun Lin ; Xiaochun Xu ; Jinfeng Pang 等
期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：2
页码：339-344
DOI：10.14257/ijsip.2014.7.2.31
出版社：SERSC
摘要：The existing recognition methods of radiation source signal are extremely sensitive to the change of signal-to-noise ratio (SNR). In order to solve this problem, in this paper, it proposes a radar signal recognition method based on fractal box dimension and neural network under the condition of unstable SNR. Firstly, it extracts box counting dimension features of four different radiation source signals, and then uses the characteristic values of stable box counting dimension as the inputs of the neural network. Finally, it can recognize the four different kinds of radiation source signals. Simulation results show that, taking the box counting dimension characteristics as the input of the neural network to train, test and classify, it has good recognition rate in a certain changed range of SNR, and it has more widely application in the application environment.
关键词：radiation source signal recognition; fractal box dimension; neural network; ; unstable SNR