Wavelet-based denoising of underwater acoustic signals

Underwater environmental measurements of the ocean require signals that are free from unwanted backscatter and clutter. Removing these unwanted signal components usually amounts to applying some form of filtering technique such as a high pass filter, a bandpass filter, a Wiener filter, etc. These approaches however are limited in their abilities to remove acoustic returns that vary spectrally. This paper presents a multiresolution approach to removing unwanted backscatter from high-frequency underwater acoustic signals and compares it to high pass filtering of the same signals. The filtering approach presented applies wavelet transforms for signal recovery and denoising of high-frequency acoustic signals. It is shown that by computing a wavelet transform of the returned signals, applying a denoising technique, and then reconstructing the signal, additional unwanted backscatter can be removed.