Signal Detection in Underwater Sound Using the Empirical Mode Decomposition

Fu-Tai WANG  Shun-Hsyung CHANG  Jenny Chih-Yu LEE  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E89-A   No.9   pp.2415-2421
Publication Date: 2006/09/01
Online ISSN: 1745-1337
DOI: 10.1093/ietfec/e89-a.9.2415
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: General Fundamentals and Boundaries
empirical mode decomposition,  wavelet,  underwater sound,  signal detection,  

Full Text: PDF>>
Buy this Article

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.