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利用ASTFT谱有效抑制WVD交叉项的方法

程发斌 汤宝平 钟佑明

程发斌, 汤宝平, 钟佑明. 利用ASTFT谱有效抑制WVD交叉项的方法[J]. 电子与信息学报, 2008, 30(10): 2299-2302. doi: 10.3724/SP.J.1146.2007.00483
引用本文: 程发斌, 汤宝平, 钟佑明. 利用ASTFT谱有效抑制WVD交叉项的方法[J]. 电子与信息学报, 2008, 30(10): 2299-2302. doi: 10.3724/SP.J.1146.2007.00483
Cheng Fa-Bin, Tang Bao-Ping, Zhong You-Ming. A Method to Suppress Cross-Terms of Wigner-Ville Distribution Using ASTFT Spectrum[J]. Journal of Electronics & Information Technology, 2008, 30(10): 2299-2302. doi: 10.3724/SP.J.1146.2007.00483
Citation: Cheng Fa-Bin, Tang Bao-Ping, Zhong You-Ming. A Method to Suppress Cross-Terms of Wigner-Ville Distribution Using ASTFT Spectrum[J]. Journal of Electronics & Information Technology, 2008, 30(10): 2299-2302. doi: 10.3724/SP.J.1146.2007.00483

利用ASTFT谱有效抑制WVD交叉项的方法

doi: 10.3724/SP.J.1146.2007.00483
基金项目: 

国家自然科学基金(50405009, 50735008),霍英东教育基金会11屇青年教师基金(111057)和教育部新世纪人才支持计划(NCET- 04-0849)资助课题

A Method to Suppress Cross-Terms of Wigner-Ville Distribution Using ASTFT Spectrum

  • 摘要: 该文分析了Wigner-Ville Distribution (WVD)中自项与交叉项相互关系,提出了一种利用自适应短时傅里叶变换(ASTFT谱)有效抑制WVD交叉项的新方法。该方法首先对信号进行ASTFT得到信号的ASTFT谱图,以确定出信号分量在时频平面内的位置,然后将ASTFT谱作为窗函数对信号的WVD进行加窗处理,从而有效消除掉WVD中的交叉项,并保留WVD的高分辨率和能量聚集性等优良特性。最后通过实例验证了该方法的有效性。
  • [1] Baraniuk R G and Jones D J. A signal-dependenttime-frequency representation: Fast algorithm for optimalkernel design[J].IEEE Trans. on Signal Process.1994, 42(1):134-146 [2] Zhu Y M, Peyin F, and Goutte R. Equivalence betweentwo-dimensioned analytic and real signal Wigner distribution[J].IEEE Trans. on ASSP.1989, 37(10):1631-1634 [3] 李波, 沈福民. 一种新的抑制交叉项的时-频分布的分析. 雷达与对抗, 2003, (1): 16-18.Li B and Shen F M. Analysis of a new time-frequencydistribution for suppressing the cross terms. Radar andElectronic Counter Measures, 2003, (1): 16-18. [4] Mirela B and Isar A. The reduction of interference terms inthe time-frequency plane. Signals, Circuits and Systems, 2003,2: 461-464. [5] 郭福成, 皇甫堪. 基于滤波器组的改进型Wigner-Ville 分布.信号处理, 2001, 17(1): 1-4.Guo F C and Huang F K. The improved Wigner-VilleDistribution based on filter bank. Signal Processing, 2001,17(1): 1-4. [6] 陈洁, 沈远彤. 基于小波包变换的威格纳分布交叉项的抑制.湖北大学学报, 2006, 28(1): 4-6.Cheng J and Shen Y T. Applying wavelet packet transform tothe suppression of the Interference term of Wigner Villedistribution. Journal of Hubei University, 2006, 28(1): 4-6. [7] Khandan F and Ayatollahi A. Performance region of centeraffine Filter for liminating of interference terms of discreteWigner distribution. Image and Signal Processing andAnalysis, 2003, 2: 621-625. [8] Chen J. Time frequency-based blind source separationtechnique for elimination of cross-terms in Wignerdistribution[J].Electronics Letters.2003, 39(5):475-477 [9] Lu F S, Yang C X, and Lin P L. An improved Wignerdistribution based algorithm for signal identification. Proc.IEEE International Symposium on Underwater Technology(UT'04), Tapei, Taiwan, 2004: 39-45. [10] 徐春光, 谢维信. 一种高分辨自适应信号时频表示. 西安电子科技大学学报, 1999, 26(6): 718-723.Xu C G and Xie W X. Time-frequency representation of ahigh resolution adaptive signal. Journal of Xidian University,1999, 26(6): 718-723. [11] Ristic B and Boashash B. Kernel design for time-frequencysignal analysis using the radon transform[J].IEEE Trans. onSignal Processing.1993, 41(5):1996-2008
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出版历程
  • 收稿日期:  2007-04-02
  • 修回日期:  2007-09-17
  • 刊出日期:  2008-10-19

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