J4 ›› 2013, Vol. 40 ›› Issue (2): 164-171.doi: 10.3969/j.issn.1001-2400.2013.02.027

• 研究论文 • 上一篇    下一篇

基于多集典型相关分析的雷达辐射源指纹识别

王磊;史亚;姬红兵   

  1. (西安电子科技大学 电子工程学院,陕西 西安  710071)
  • 收稿日期:2012-09-19 出版日期:2013-04-20 发布日期:2013-05-22
  • 通讯作者: 王磊
  • 作者简介:王磊(1979-),男,讲师,博士,E-mail: leiwang@mail.xidian.edu.cn.
  • 基金资助:

    国家自然科学基金资助项目(61203137);高等学校博士学科点专项科研基金资助项目(20120203120010);中央高校基本科研业务费专项资金资助项目(K5051302011,K5051302039)

Specific radar emitter identification using multiset canonical correlation analysis

WANG Lei;SHI Ya;JI Hongbing   

  1. (School of Electronic Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2012-09-19 Online:2013-04-20 Published:2013-05-22
  • Contact: WANG Lei

摘要:

为了提升雷达辐射源指纹识别系统的性能,提出了一种基于多集典型相关分析的辐射源指纹识别新策略.首先抽取辐射源信号的模糊函数多普勒切片作为初始特征,继而利用多集典型相关分析实现了表征能力不同的各切片间的特征融合与冗余消除,而进一步推广得到的多集判别典型相关分析在保持较低典型向量阶数的同时还可获得更优的识别性能.由于采用多集策略进行切片特征的直接融合,模糊函数加多集典型相关分析法不仅避免了代表性切片法中切片寻优的不确定性,而且克服了传统典型相关分析只适用于两集特征的局限性.实测雷达辐射源数据上的实验表明所提方法有效地优化了雷达指纹特征.

关键词: 辐射源指纹识别, 模糊函数, 多集典型相关分析, 多集判别典型相关分析, 特征融合

Abstract:

In order to improve the performance of a specific radar emitter recognition system, a novel framework based on Multiset Canonical Correlation Analysis (MCCA) is proposed. It extracts the Doppler cuts of the ambiguity function (AF) of each radar signal as the initial feature set and employs MCCA to perform feature fusion and redundancy reduction in such a set. By using label information, the further developed Multiset Discriminant Canonical Correlation Analysis (MDCCA) achieves competitive performance while retaining the low order of canonical vectors. Thanks to the direct fusion strategy, the proposed scheme not only avoids the uncertainty in determining the optimal cut of AF in previous methods, but also extends the conventional CCA, which can only deal with two sets of feature vectors, to the multiset version. Experiments on real radar emitter data demonstrate the effectiveness of the proposed methods.

Key words: specific emitter identification, ambiguity function, multiset canonical correlation analysis, multiset discriminant canonical correlation analysis, feature fusion

中图分类号: 

  • TN974