Application of an Approximately Shift-invariant Wavelet Transform to Signal Detection via Empirical Model of Noise

This article proposes a use of the dual-tree discrete wavelet transform (DT DWT) to the problem of signal detection in underwater sound. This approximately shift invariant DT DWT can generate multi-resolution subspaces that keep more of their coefficient energy in each of these subspaces than discre...

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Bibliographic Details
Main Authors: Fu-Tai Wang, Lee, J.C.-Y., Shun-Hsyung Chang, Chin-Pin Chou, Sheng-Yun Hou, Hsin-Hung Chang, Yi-Han Wang
Format: Conference Proceeding
Language:English
Subjects:
Acoustic noise
Band pass filters
Detectors
Discrete wavelet transforms
Filter bank
Frequency
Marine
Signal analysis
Signal detection
Wavelet analysis
Wavelet transforms
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Summary:This article proposes a use of the dual-tree discrete wavelet transform (DT DWT) to the problem of signal detection in underwater sound. This approximately shift invariant DT DWT can generate multi-resolution subspaces that keep more of their coefficient energy in each of these subspaces than discrete wavelet transform's (DWT). The detection performance comparison, under the same value of the false alarm probability P F , of this proposed DT DWT-based empirical model and DWT- based method is presented. A performance comparison has shown that this proposed DT DWT-based empirical model of noise is better than the DWT-based detector.
DOI:10.1109/OCEANSKOBE.2008.4531075