It is seriously interfered by ship noise when analyzing and extracting broadband spark sound source signal. In the energy concentrated domain which is below 5 kHz, the traditional scale correlation filtering algorithm...It is seriously interfered by ship noise when analyzing and extracting broadband spark sound source signal. In the energy concentrated domain which is below 5 kHz, the traditional scale correlation filtering algorithm, which is based on adjacent-scale correlation, has limited anti-interference ability due to the low signal-to-noise ratio （SNR） and similar Lipschitz exponent characteristic of each other. However, because different frequency bands of the broadband electric spark signal have different noise interferences, the filtering algorithm based on adjacent-scale correlation is adapted to high SNR and small-scale high-frequency wavelet coefficients filtering; the filtering algorithm based on cross-scale correlation is adapted to low SNR and large-scale low-frequency wavelet coefficients filtering, and the threshold coefficient selection method had been corrected in the algorithm. It is shown that the filtering algorithm has a good filtering effect and extracts the broadband spark sound source signal effectively; it is applicable to broadband underwater acoustic signM processing in the presence of narrow-band strong interference background noise.展开更多
A fast wavelet packet (WP) algorithm is presented, in which the wavelet transform (WT) and the short-time Fourier transform (STFT) are combined. As WT produces multiresolution of frequency and time, and STFT has a fas...A fast wavelet packet (WP) algorithm is presented, in which the wavelet transform (WT) and the short-time Fourier transform (STFT) are combined. As WT produces multiresolution of frequency and time, and STFT has a fast algorithm, the combining algorithm is suitable for fast signal analysis.展开更多
基金supported by the Scientific Research Foundation of Third Institute of Oceanography,SOA(NO.2010018)the Public Science and Technology Research Funds Projects of Ocean(NO.201005004,NO.201305038)
文摘It is seriously interfered by ship noise when analyzing and extracting broadband spark sound source signal. In the energy concentrated domain which is below 5 kHz, the traditional scale correlation filtering algorithm, which is based on adjacent-scale correlation, has limited anti-interference ability due to the low signal-to-noise ratio （SNR） and similar Lipschitz exponent characteristic of each other. However, because different frequency bands of the broadband electric spark signal have different noise interferences, the filtering algorithm based on adjacent-scale correlation is adapted to high SNR and small-scale high-frequency wavelet coefficients filtering; the filtering algorithm based on cross-scale correlation is adapted to low SNR and large-scale low-frequency wavelet coefficients filtering, and the threshold coefficient selection method had been corrected in the algorithm. It is shown that the filtering algorithm has a good filtering effect and extracts the broadband spark sound source signal effectively; it is applicable to broadband underwater acoustic signM processing in the presence of narrow-band strong interference background noise.
文摘A fast wavelet packet (WP) algorithm is presented, in which the wavelet transform (WT) and the short-time Fourier transform (STFT) are combined. As WT produces multiresolution of frequency and time, and STFT has a fast algorithm, the combining algorithm is suitable for fast signal analysis.
