Signal Detection in Underwater Sound Using the Empirical Mode Decomposition

In this article, the empirical mode decomposition (EMD) is introduced to the problem of signal detection in underwater sound. EMD is a new method pioneered by Huang et al. for non-linear and non-stationary signal analysis. Based on the EMD, any input data can be decomposed into a small number of intrinsic mode functions (IMFs) which can serve as the basis of non-stationary data for they are complete, almost orthogonal, local and adaptive. Another useful tool for processing transient signals is discrete wavelet transform (DWT). In this paper, these IMFs are applied to determine when the particular signals appear. From the computer simulation, based on the receiver operating characteristics (ROC), a performance comparison shows that this proposed EMD-based detector is better than the DWT-based method.

[1]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[2]  Shun-Hsyung Chang,et al.  Signal Detection in Underwater Sound by Dual-Tree Discrete Wavelet Transform , 2007, OCEANS 2007 - Europe.

[3]  Theofanis Sapatinas,et al.  Signal Detection in Underwater Sound using Wavelets , 1998 .

[4]  Frederick Mosteller,et al.  Data Analysis and Regression , 1978 .

[5]  Stanisław Ryszard Massel,et al.  Wavelet analysis for processing of ocean surface wave records , 2001 .

[6]  P. Abry,et al.  Multiresolution transient detection , 1994, Proceedings of IEEE-SP International Symposium on Time- Frequency and Time-Scale Analysis.

[7]  A. M. Gross.  Confidence Interval Robustness with Long-Tailed Symmetric Distributions , 1976 .

[8]  S. S. Shen,et al.  A confidence limit for the empirical mode decomposition and Hilbert spectral analysis , 2003, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[9]  C. Guedes Soares,et al.  Identification of the components of wave spectra by the Hilbert Huang transform method , 2004 .

[10]  Gabriel Rilling,et al.  Empirical mode decomposition as a filter bank , 2004, IEEE Signal Processing Letters.

[11]  C. D. Kemp,et al.  Density Estimation for Statistics and Data Analysis , 1987 .

[12]  Alan V. Oppenheim,et al.  Digital Signal Processing , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[13]  Shun-Hsyung Chang,et al.  Application of the robust discrete wavelet transform to signal detection in underwater sound , 2003 .

[14]  José M. F. Moura,et al.  On Translation Invariant Subspaces and Critically Sampled Wavelet Transforms , 1997, Multidimens. Syst. Signal Process..