Estimation of noise model and denoising of wind driven ambient noise in shallow water using the LMS algorithm

Signal transmission in ocean using water as a channel is a challenging process due to the effect of attenuation, spreading, reverberation, absorption etc., apart from the contribution of acoustic signals due to ambient noises. Ambient noises in sea are of two types namely manmade (shipping, aircraft over the sea, motor on boat, etc) and natural (rain, wind, marine fishes, seismic, etc). The ambient noises contribute more effect on reducing the quality of acoustic signal. In this paper we concentrate on denoising the effect due to wind on underwater acoustic signal using the LMS algorithm. The wind speed of the collected data ranges from 2.11 m/s to 6.57 m/s. The analysis is carried out for acoustic frequencies ranging from 100 Hz to 8 kHz. It is found that a linear relationship between noise spectrum and wind speed exists over the entire frequency range. The results of the empirical data are compared with the results obtained with the aid of the noise model developed. An adaptive model exploiting the Least Mean Square (LMS) algorithm to denoise wind driven ambient noise in shallow water has been proposed. The observation shows that the Signal to Noise Ratio (SNR) is enhanced two fold and the Mean Square Error (MSE) decreases exponentially with the aid of the LMS adaptive algorithm.