Automatic Intra-Pulse modulation recognition using support vector machines and genetic algorithm

被引：0
|
作者：
Li, Jie [1 ]
Zhang, Ge [1 ]
Sun, Yang [1 ]
Yang, Erlei [1 ]
Qiu, Lede [2 ]
Ma, Wei [1 ]
机构：
[1] China Acad Space Technol Xian, Xian 710000, Shaanxi, Peoples R China
[2] CAST, Inst Telecommun Satellite, Beijing 100094, Peoples R China
来源：
2017 IEEE 3RD INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC) | 2017年
关键词：
Intra-Pulse modulation recogniton; support vector machines; genetic algorithm; time-frequency; Wigner Ville Distribution (WVD);
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new method, based on support vector machines (SVMs) and genetic algorithm (GA), is proposed for automatic Intra-Pulse modulation recognition (AIMR). In particular, the best feature subset from the combined pulse descriptor word (PDW) feature set and time-frequency feature set is optimized using genetic algorithm. Compared to the conventional decision-theoretic method, the method proposed avoids the frequency ambiguity caused by signal noise. Simulation results show that this method is more robust and effective than other existing approaches, particularly at a low signal noise ratio (SNR).
引用
收藏
页码：309 / 312
页数：4
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