文章摘要
孟亮,李夕海,张万刚,刘代志.基于小波包分解和FK分析的次声信号参数估计[J].,2016,35(2):151-156
基于小波包分解和FK分析的次声信号参数估计
The parameter estimation of infrasound signals based on the wavelet packet decomposition and the frequency-wavenumber processing
投稿时间:2015-08-18  修订日期:2016-02-24
中文摘要:
      频率波数分析法是一种估计信号慢度和方位角的台阵数据处理方法,在地震波信号处理中得到广泛应用,但将频率波数分析法应用于次声信号的时候,分辨率不高,易受噪声的影响,伪峰较明显。因此,本文提出了一种基于小波包分解和FK分析的次声信号参数估计方法,该方法借助小波包分解对信号整个频带的分辨能力,有效提高了算法的分辨率,降低了噪声的影响,有效压制了伪峰,并利用高斯调制正弦信号模拟次声信号,对比分析了方位角的均值、方差和均方根误差,验证了算法的性能,最后利用IS45台站接收的实际次声数据对算法进行对比分析,进一步验证了算法的有效性。
英文摘要:
      The Frequency-wavenumber (FK) processing is often taken to estimate the slowness and azimuth for array data, and has been widely used in seismic signal. But when the FK processing is applied to infrasound signal, the resolution is not high, susceptible to noise and pseudo peak is obvious. Therefore, this paper proposes a method based on the wavelet packet decomposition and the frequency-wavenumber processing. This method uses the ability of wavelet packet decomposition for analyzing the whole frequency band signal, can effectively improve the resolution of the algorithm, reduces the effect of noise and suppresses the pseudo peak. The analog infrasound signal is Gaussian modulated sinusoidal signal. By analyzing the azimuth of the mean value, variance and the root mean square error, the algorithm is verified. Finally, the infrasound data received by the IS45 is analyzed by the two methods. The results demonstrate the effectiveness of the method proposed in this paper.
DOI:10.11684/j.issn.1000-310X.2016.02.009
中文关键词: 次声  频率波数法  小波包分解  均方根误差
英文关键词: infrasound, Frequency-Wavenumber processing, Wavelet Packet Decomposition, root means quare error
基金项目:
作者单位E-mail
孟亮 火箭军工程大学 ml7290@sohu.com 
李夕海 火箭军工程大学  
张万刚 火箭军工程大学  
刘代志 火箭军工程大学  
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