期刊文献+

基于分形理论的辐射源识别算法 被引量:2

Emitter recognition arithmetic based on fractal theory
在线阅读 下载PDF
导出
摘要 针对复杂的战场电磁环境,提出了一种新的辐射源信号识别方法,即基于分形特征的辐射源目标识别。介绍了分形的相关理论,给出了分形维数中盒维数与信息维数的计算步骤,而后采用距离函数进行判决识别。仿真结果表明提出的基于分形特征的辐射源信号识别算法能得到较高的识别率。 Signal environments become more and more complicated,a novel approach is proposed to recognize emitter signal based on fractal theory.Firstly,fractal theory is introduced.Secondly,box dimension and information dimension of fractal dimension calculation steps are listed.At last,decision-making is performed with distance function.Experimental results of fractal feature recognition of 5 typical emitter signals show that this arithmetic can get high accurate recognition rate,this also verifies the new approach is valid and effective.
出处 《航天电子对抗》 2010年第2期62-64,共3页 Aerospace Electronic Warfare
关键词 分形理论 盒维数 信息维数 辐射源识别 fractal theory box dimension information dimension emitter recognition
  • 相关文献

参考文献8

二级参考文献29

共引文献102

同被引文献22

  • 1蔡忠伟,李建东.基于双谱的通信辐射源个体识别[J].通信学报,2007,28(2):75-79. 被引量:86
  • 2Zhang Jing-jing, Li Bing-bing. A new modulation identification scheme for OFDM in muhipath rayleigh fading channel[C]//International Symposium on Computer Science and Computational Technology. Shanghai:China,IEEE,2008:793- 796.
  • 3Subasi A, Gursoy M I. EEG signal classification using PCA, ICA, LDA and support vector machines [J].Expert Systems with Applications, 2010,37 ( 12) : 8659-8666.
  • 4Xu Y, Lin C, Zhao W. Producing computationally efficient KP CA based feature extraction for classification problems[J]. Electronics Letters, 2010,46 (6) : 452-453.
  • 5任若恩 王惠文.多元统计数据分析[M].北京:国防工业出版社,1997..
  • 6THEODORIDIS S,KOUTSOUBOS K.模式识别[M].3版,北京:电子工业出版社,2006:213-229.
  • 7彭策,熊屹,陈文西,万柏坤.病态嗓声识别特征参数的优化选择[J].中国生物医学工程学报,2007,26(5):675-679. 被引量:1
  • 8D'Agostino S, Foglia G, Pistoia D. Specific Emitter Identi- fication: Analysis on real radar signal data[ C ]//Proceed- ings of 2009 IEEE Radar Conference. Rome : IEEE ,2009 : 242-245.
  • 9Sahmel P H. Eigenspace Approach to Specific Emitter Identieation of Orthogonal Frequency Division Multiple- xing Signals [ D ]. Virginia, USA: Virginia Polytechnic In- stitute and State University,2011.
  • 10Kyouwoong K, Spooner C M, Akbar I, et al. Specific E- mitter Identification for Cognitive Radio with Application to IEEE 802.11 [ C ]//Proceedings of 2008 IEEE Global Telecommunications Conference. New Orleans, LO: IEEE ,2008 : 1-5.

引证文献2

二级引证文献12

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部