• DocumentCode
    3156105
  • Title

    Analysis and SNR comparision of various adaptive algorithms to denoise the wind driven ambient noise in shallow water

  • Author

    Murugan, S. Sakthivel ; Natarajan, V. ; Kumar, R. Rajesh ; Balagayathri, K.

  • Author_Institution
    Dept. of ECE, SSN Coll. of Eng., Chennai, India
  • fYear
    2011
  • fDate
    16-18 Dec. 2011
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Underwater signal transmission is a challenging task since the usable frequency range is limited to low frequency and the transmission of electromagnetic waves was 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 Goa are studied in detail using Welch estimation method and the results shows the effect of wind over 100 to 8 kHz range. Different adaptive filter algorithms are analyzed in detail to eliminate the effect due to wind on the signal transmitted and signal to noise ratio is calculated. The SNR obtained for 24 types of adaptive algorithms are analyzed and tabulated for different wind speed. The results shows that RLS algorithm works better when compared to others. The maximum SNR of about 80 dB is achieved.
  • Keywords
    acoustic noise; acoustic signal processing; acoustic wave transmission; adaptive filters; underwater sound; Welch estimation method; adaptive filter algorithms; electromagnetic wave transmission; low frequency acoustic signal; shallow water; signal-to-noise ratio; underwater signal transmission; wind driven ambient noise; Adaptive filters; Finite impulse response filter; Noise measurement; Signal to noise ratio; Transversal filters; Wind speed; Ambient noise; LMS; SNR; Spectral Estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    India Conference (INDICON), 2011 Annual IEEE
  • Conference_Location
    Hyderabad
  • Print_ISBN
    978-1-4577-1110-7
  • Type

    conf

  • DOI
    10.1109/INDCON.2011.6139467
  • Filename
    6139467