Radar Emitter Signal Feature Extraction Based on Time-Frequency Atom Decomposition

被引：0
|
作者：
Li, Jungang [1 ]
Chen, Zhuyu [1 ]
Yang, Ji [1 ]
机构：
[1] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu 610031, Sichuan, Peoples R China
来源：
MANUFACTURING PROCESS AND EQUIPMENT, PTS 1-4 | 2013年 / 694-697卷
关键词：
feature extraction; classifier; radar emitter signal recognition; PULSE MODULATION RECOGNITION; CLASSIFICATION;
D O I：
10.4028/www.scientific.net/AMR.694-697.1317
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a novel approach based on time-frequency atom decomposition is presented to recognize the radar emitter signals. To decompose the signals into a linear expansion of time-frequency atoms, a fast matching pursuit (MP) algorithm, which is optimized by composite differential evolution (CoDE) algorithm, is introduced. The feature vectors of radar emitter signals are extracted based on the atoms generated in the process of decomposition. The Directed Acyclic Graph SVM (DAGSVM) is selected as the classifier to classify the feature vectors of different radar emitter signals.
引用
收藏
页码：1317 / 1320
页数：4
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