EMD-FB Based Denoising Algorithm For Under Water Acoustic Signal

Purpose of this paper is to introduce a new technique for denoising underwater acoustic signal affected by ambient noise. Ambient noise is nonstationary and unwanted background noise caused due to manmade or natural causes. In practical application it is essential to denoise underwater acoustic signal, which is received by a hydrophone in order to get actual information. Having considered wind driven noise as a source of ambient noise, which is added to the input signal in turn makes it a noisy signal. An algorithm based on Empirical Mode Decomposition (EMD) and Fourier Bessel expansion is used to separate the input signal from the noisy signal. EMD is a time-frequency analysis method, which is suitable for analyzing nonstationary signals. It is able to decompose multicomponent signal in to finite number of Intrinsic Mode Functions (IMFs) [9]. The Mean Frequency for all the IMFs has been calculated using Fourier Bessel which is used to reconstruct the input signal.