Wavelet-based signal recovery and denoising of underwater acoustic signals

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. Since the unwanted backscatter typically concentrates in the low frequencies, high pass filters are often applied but with limited effectiveness. It turns out that some of the backscattering actually appears across several frequencies, and so a more flexible filtering approach is needed. The filtering approach presented applies wavelet transforms for signal recovery and denoising of high frequency acoustic signals. Wavelet transforms are applied since they perform a multiresolution decomposition in time and frequency and therefore are well suited for removing specific unwanted signal components that may vary spectrally. It is shown that by computing a wavelet transform of the returned signals, applying a denoising technique, and then reconstructing the signals, additional unwanted backscatter can be removed.