Modulation recognition of non-cooperation underwater acoustic communication signals using principal component analysis

2018 ◽  
Vol 138 ◽  
pp. 209-215 ◽  
Author(s):  
Wei-hua Jiang ◽  
F. Tong ◽  
Yang-ze Dong ◽  
Gang-qiang Zhang
Keyword(s):  
Principal Component Analysis ◽  
Acoustic Communication ◽  
Principal Component ◽  
Component Analysis ◽  
Underwater Acoustic Communication ◽  
Modulation Recognition ◽  
Underwater Acoustic ◽  
Communication Signals

scholarly journals Blind Detection of Underwater Acoustic Communication Signals Based on Deep Learning

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 204114-204131 ◽  
Author(s):  
Yongbin Li ◽  
Bin Wang ◽  
Gaoping Shao ◽  
Shuai Shao ◽  
Xilong Pei
Keyword(s):  
Deep Learning ◽  
Acoustic Communication ◽  
Underwater Acoustic Communication ◽  
Blind Detection ◽  
Underwater Acoustic ◽  
Communication Signals

The Principal Component Analysis of Signal Characteristic Parameters

2011 ◽  
Vol 128-129 ◽  
pp. 1269-1272
Author(s):  
Guang Hui Li ◽  
Zheng Pei ◽  
Ran Chen ◽  
Da Li Hu
Keyword(s):  
Principal Component Analysis ◽  
Measurement Data ◽  
Principal Component ◽  
Component Analysis ◽  
Modulation Recognition ◽  
Characteristic Parameters ◽  
Monitoring Equipment ◽  
Multivariate Statistical ◽  
Radio Monitoring ◽  
Automatic Modulation Recognition

With the development of wireless communication, the automatic modulation recognition technology of communicational signals becomes an important theme. In this paper, based on multivariate statistical principal component analysis, we select characteristics of the signal, and use radio monitoring equipment mined measurement data to do some processing and analysis, which provided technical support to automatic modulation recognition of the radio signal.

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