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Veni, K.S., Murugan, S.S. and Natarajan, V. (2011) Modified LMS Adaptive Algorithm for Detection of Underwater Acoustic Signals Against Ambient Noise in Shallow Water of Indian Sea. IEEE International Conference on Recent Trends in Information Technology (ICRTIT), Chennai, 3-5 June 2011, 901-905.

has been cited by the following article:

• TITLE: New Wavelet Thresholding Algorithm in Dropping Ambient Noise from Underwater Acoustic Signals

  AUTHORS: Mohammad Monirujjaman Khan, Ratil Hasnat Ashique, Badrun Naher Liya, Md. Mohsin Sajjad, Md. Anisur Rahman, M. T. Hasan Amin

  KEYWORDS: Ambient Noise, Wavelet Transform, Thresholding, Signal to Noise Ratio (SNR), Root Mean Square Error (RMSE), Power Spectral Density (PSD), Percentage Root Mean Square Difference (PRD)

  JOURNAL NAME: Journal of Electromagnetic Analysis and Applications, Vol.7 No.3, March 3, 2015

  ABSTRACT: Underwater Wireless Communication, largely dependent on the acoustic communication between the machines, is largely affected by various types of noise in the shallow and deep water. However ambient noise which is due to multiple sources (e.g. shipping, wind) and no one source dominates. Ambient noise masks the acoustic signal to a large extent. Hence today it has drawn the attention of the experts to reduce its effect on the received signal. This paper discusses ambient noise problem and devises a new wavelet thresholding method to reduce its effect. Afterwards a comparative study on statistical parameters is shown to prove the efficiency of the devised method.