A novel feature extraction approach for radar emitter signals

被引：0
|
作者：
Zhu Ming [1 ,2 ,3 ]
Jin Weidong [1 ]
Pu Yunwei [1 ,2 ]
Hu Laizhao [2 ]
机构：
[1] Southwest Jiaotong Univ, Sch Informat Sci & Technol, Chengdu 610031, Peoples R China
[2] Natl EW Lab, Chengdu 610036, Peoples R China
[3] Chengdu Univ Informat Technol, Chengdu 610225, Sichuan, Peoples R China
来源：
ICIEA 2007: 2ND IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-4, PROCEEDINGS | 2007年
基金：
中国国家自然科学基金;
关键词：
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Feature extraction is the crucial technology to deinterleave and recognize the new system radar emitter signals. In this paper, a novel time-frequency atom feature extraction approach is presented. Based on the over-complete multiscale dictionary of Gaussian Chirplet atoms, adopting Match Pursuit (MP) to decompose signals and the improved quantum genetic algorithm (IQGA) to reduce the search time for MP, the optimal Chirplet atoms to represent the feature information of the radar emitter signals can be obtained. The validity and feasibility of the approach was proved by using fewer Chirplet atoms to acquire more accurate feature information compared with Gabor atoms approach.
引用
收藏
页码：1785 / +
页数：2
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