Marine Engineering faces certain challenges in recent times due to the prevalence of ambient conditions caused by imbalance in the ecosystem. Underwater ambient noise is primarily a background noise, which is a function of time, location and depth. It is of prime importance to detect the signals such as the sound of a submarine or an echo from a target, surpassing and surmounting this ambient noise. In the absence of the sound from ships and marine life, underwater ambient noise levels are dependent mainly on wind speeds at frequencies between 500 Hz and 50 KHz (Urick, 1984). Since there is a possibility of signal and noise present in the same frequency, it becomes indispensable to find out a suitable algorithm to perform denoising. In this paper the functioning of different denoising methods: wavelet, Empirical Mode Decomposition (EMD) in time domain, Ensemble Empirical Mode Decomposition (EEMD) and frequency domain based EMD are studied and the results are compared. The proposed frequency domain algorithm produced better results in the frequency ranging from 50 Hz to 25 KHz, with less signal error - an encouraging result. This work is calibrated through a comparison made with the existing methods and the outcomes obtained are found to be better than the existing algorithms like wavelet, EMD in time domain, etc.

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