Adaptive window-length detection of underwater transients using wavelets

摘要

This paper describes a detection method that adapts to unknown characteristics of the underlying transient signal, such as location, length, and time-frequency content. It applies a set of embedded detectors tuned to a number of signal partitions. The detectors are based on the wavelet theory, whereby two different techniques are examined, one using local Fourier transform and the other using discrete wavelet transform. The detection statistics are computed so as to enable prewhitening of unknown colored noise and to allow for a constant false-alarm rate detection. An adapted segmentation of the signal is next obtained with a goal of finding the largest detection statistics within each segment of the partition. The detectors are tested using several underwater acoustic transient signals buried in ambient sea noise. © 2005 Acoustical Society, of America.