基于改进EMD算法的跳频信号参数估计
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摘要
针对短时傅立叶变换时频分辨率不能同时很高,小波变换运算时间偏长,抗噪性差,Wigner-Ville变换及其改进方法受交叉项影响等问题,提出了一种基于希尔伯特-黄(HHT,Hilbert-Huang Transformation)算法的跳频信号参数估计.该方法的分解是自适应的,计算出的瞬时频率有很高的时间分辨率和较高频率分辨率.对于HHT算法中出现的虚假分量和端点效应问题,通过互相关方法来消除虚假分量,镜像闭合延拓方法去除端点效应.仿真结果表明该方法能很好解决上述两个问题.
Because short term fourier transform did not have high time-frequency differentiability,wavelet transformation had too much operation time and Wigner-Ville distribution( including its improved methods)had cross-term interference. Thusly,a method called Hilbert-Huang Transform( HHT) was put up with to estimate the parameters of frequency-hopping signals. Its decomposition was adaptive and had high time differentiability and frequency differentiability,but it had end effects and illusive components. The end effects can be resolved by using a mirror closed extending method,and illusive components can be treated by using a correlation coefficient. Simulation results showed that this improved algorithm could solve the problems effectively.
Because short term fourier transform did not have high time-frequency differentiability,wavelet transformation had too much operation time and Wigner-Ville distribution( including its improved methods)had cross-term interference. Thusly,a method called Hilbert-Huang Transform( HHT) was put up with to estimate the parameters of frequency-hopping signals. Its decomposition was adaptive and had high time differentiability and frequency differentiability,but it had end effects and illusive components. The end effects can be resolved by using a mirror closed extending method,and illusive components can be treated by using a correlation coefficient. Simulation results showed that this improved algorithm could solve the problems effectively.
引文
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[15]GABRIEL R,PATRICK F,PAULO G,et al.On Empirical Mode Decomposition and Its Algorithms[C]//IEEE-EUR-ASIP Workshop on Nonlinear Signal and Image Processing.Washington:IEEE Signal Processing Society,2003:9-11.
[16]YUAN YE,MEI WEN BO,WU SI LIANG,et al.Hop period estimation for frequency hopping signals based on Hilbert-huang transform[C]//Proc.of IEEE Congress on Image and Signal Processing,2008:452-455.
[2]曹汉.基于相关系数的经验模态分解算法的改进[J].中国新通信,2010(7):50-53.
[3]COUGHLIN K T,TUNG K K.11-Year solar cycle in the stratosphere extracted by the empirical mode decomposition method[C]//Advances in Space Research,2004,34:323-329.
[4]BALOCCHI R.Deriving the respiratory sinus arrhythmia from the heartbeat time series using empirical mode decomposition[J].Chaos,Solitons and Fractals,2004,20:171-177.
[5]MARCUS DATIG,TORSTEN SCHLURMANN.Performance and limitations of the Hilbert-Huang transformation with an application to irregular water waves[J].Ocean Engineering,2004,31:1783-1834.
[6]胡广书.数字信号处理:理论、算法与实现[M].北京:清华大学出版社,1997.
[7]钟佑明,秦树人.希尔伯特-黄变换的统一理论依据研究[J].振动与冲击,2006,25(3):40-44.
[8]杨彦利,邓甲昊.经验模态分解及其雷达信号处理[J].科技导报,2010,28(10):101-105.
[9]曹晖,曹永红.HHT变换在地震动信号分析中的应用[J].重庆大学学报,2008,31(8):922-927.
[10]胡劲松,杨世锡.基于自相关的旋转机械振动信号EMD分解方法研究[J].机械强度,2007,29(3):376-379.
[11]于德介,陈淼峰,程军圣,等.一种基于经验模式分解与支持向量机的转子故障诊断方法[J].中国电机工程学报,2006,26(16):162-167.
[12]DENG YONGIUN,WANG WEI.Boundary processing technique in EMD method and Hilbert transform[J].Chinese Science Bulletin,2001:257-263.
[13]戴桂平.基于EMD的时频分析方法研究[D].秦皇岛:燕山大学,2005
[14]余磊,刘泉.经验模态分解中端点效应的抑制[J].武汉理工大学学报,2010,32(10):151-154.
[15]GABRIEL R,PATRICK F,PAULO G,et al.On Empirical Mode Decomposition and Its Algorithms[C]//IEEE-EUR-ASIP Workshop on Nonlinear Signal and Image Processing.Washington:IEEE Signal Processing Society,2003:9-11.
[16]YUAN YE,MEI WEN BO,WU SI LIANG,et al.Hop period estimation for frequency hopping signals based on Hilbert-huang transform[C]//Proc.of IEEE Congress on Image and Signal Processing,2008:452-455.
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