期刊文献+

基于模式的自制小波在EBPSK信号检测中的应用 被引量:4

Pattern-based custom wavelet used for EBPSK signal detection
下载PDF
导出
摘要 为了改善基于小波的超窄带信号的检测率,提出了根据信号的模式构建小波的方法.以扩展二元相位键控的"1"信号为例,采用常数正交函数空间投影法构建了对应的unb1小波,并与经典的Haar,db系列、Symlet系列、Coiflet系列、Biorspline系列、逆Biorspline系列、离散美尔、高斯系列、墨西哥帽和Morlet小波进行比较.分析结果发现,所提出的unb1小波性能较好,能够检测出信号的位置和尺度,且在噪声强度大于信号强度的情况下亦可工作.因此,基于模式的自制小波用于超窄带信号检测是可行的. A novel custom wavelet based on signal patterns is proposed in order to improve the detection ratio of the UNB(ultra narrow band) signal.The "1" signal in extended binary phase shift keying(EBPSK) was taken as the example,and corresponding wavelet unb1 was constructed by orthconst method.Then,the proposed wavelet unb1 was compared with traditional wavelets including Haar,db series,Symlet series,Coiflet series,Biorsplines,reverse Biorsplines,discrete Meyer,Gaussian series,Mexican hat,and Morlet.The results indicate that the proposed unb1 is superior to traditional wavelets with respect to detecting both position and scale of the signal;besides,the method can work even if the magnitude of the noise is greater than that of the signal.In all,the pattern-based wavelet is feasible and effective in the application of UNB detection.
出处 《东南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2011年第4期691-694,共4页 Journal of Southeast University:Natural Science Edition
基金 国家自然科学基金资助项目(60872075) 高等学校科技创新工程重大项目培育基金资助项目(706028) 东南大学优秀博士学位论文基金资助项目(YBJJ0908)
关键词 自制小波 超窄带 统一的二元相位调制和解调 信号检测 custom wavelet ultra narrow band EBPSK(extended binary phase shift keying) signal detection
  • 相关文献

参考文献15

  • 1Walker H R. Ultra narrow band modulation textbook [EB/OL]. (2006) [2009-12-141. http://www, vmsk. org/. 被引量:1
  • 2吴乐南.超窄带高速通信进展[J].自然科学进展,2007,17(11):1467-1473. 被引量:76
  • 3吴乐南,吕久旭,张七凯,等.时频混叠信号的几何特征滤波方法:中国,200610088315.1[P].2009-02-25. 被引量:1
  • 4张士凯,吴乐南.EBPSK调制的波形优化[J].东南大学学报(自然科学版),2008,38(4):564-568. 被引量:13
  • 5马力,冯熳,吴乐南.EBPSK数字接收滤波器设计[J].科技创新导报,2008,5(28):28-29. 被引量:9
  • 6高鹏,冯熳,吴乐南.EBPSK调制信号的特殊滤波响应[C]//计算机技术与应用会议论文集.南宁,中国,2009:1018-1024. 被引量:3
  • 7Bobier J. Flash signal [EB/OL]. (2008-12-06) [2009-12-14 ]. http ://www. xgtechnology, corn/. 被引量:1
  • 8Zhang Y D, Wu L N. Crop classification by forward neural network with adaptive chaotic particle swarm optimization [J]. Sensors, 2011, 11 (5) : 4721 -4743. 被引量:1
  • 9Zhang Y D, Wang S H, Huo Y K, et al. Feature extraction of brain MRI by stationary wavelet transform and its applications [J]. Journal of Biological Systems, 2010, 18 (sl): 115-132. 被引量:1
  • 10Sweldens W. The lifting scheme: a custom-design construction of biorthogonal wavelets [ J ]. Applied and Computational Harmonic Analysis, 1996, 3 (2) : 186 - 200. 被引量:1

二级参考文献61

共引文献94

同被引文献39

引证文献4

二级引证文献28

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