Analysis of power spectral density and development of an adaptive algorithm for filtering wind driven ambient noise in shallow water

Underwater signal transmission is a challenging task since the usable frequency range is limited to low frequency and the transmission of electromagnetic waves is impossible due to its high attenuation nature. Hence low frequency acoustic signal is more suited for transmission in underwater. Underwater transmission is highly affected by wind noise which is predominant at low frequency. The real time data collected from Indian Seas at Chennai are studied in detail using Welch, Bartlett and Blackman estimation methods and the results shows the effect of wind over 0-8 kHz range. Various adaptive algorithms are analyzed in detail and the SNR values are tabulated for different wind speeds. The results shows that RLS algorithm works better when compared to others. The maximum SNR of about 80 dB is achieved.