Underwater Acoustic Signal Denoising Based Upon Empirical Mode Decomposition and Discrete Wavelet Transform

Abstract

ABSTRACT Underwater acoustic communication is a rapidly growing field of research and engineering. The wave propagation in an underwater sound channel mainly gets affected by channel variations, multipath propagation and Doppler shift which keep lot of hurdles for achieving high data rates and transmission robustness. Furthermore, the usable bandwidth of an underwater sound channel is typically a few kHz at large distances. In addition, there is no typical underwater acoustic channel; every body of water exhibits quantifiably different properties. In order to achieve high data rates it is natural to employ bandwidth efficient modulation. The main problem with the underwater communication is addition of random noise in the signal. The noise in underwater is of various types such as ambient noise, ship noise, deep water noise, aquatic noise, shallow water noise etc. There are various techniques based upon signal processing and stochastic replay to denoise the signal. Keeping in mind the complex and random nature of underwater communication two effective methods have been presented in this thesis. One is EMD (Empirical Mode Decomposition) based upon stochastic replay method and other is DWT (Discrete wavelet Transform) based upon Short Time Fourier Transform (STFT). Based upon these two techniques various thresholding techniques have been applied on different types of synthetic underwater acoustic signals embedded with noise and considerable degradation of noise is seen and also there is considerable improvement in SNR of the signal.