A Literature Survey on Ambient Noise Analysis For underwater Acoustic Signals

Sauda Sadaf P Yashaswini, Soumya Halagur, Fazil Khan, Dr. Shanta Rangaswamy


Transmitting data with water as the medium is called underwater communication. Electromagnetic signals are better attenuated in water than sound. Hence it is the most reliable and versatile means of communication underwater. The acoustic signals will be affected by ocean driven noise during transmission. Ambient noise is the background noise which has to be subtracted from the acoustic signal for smooth transmission. Hence the recognition and reduction of ambient noise is the essential part of underwater signal transmission. Studies and research are being carried out extensively in this area. There are many works reported and the research is still in progress. This literature survey presents the work done on the research front of ambient noise affecting acoustic signals.  


Noise Analysis;underwater Acoustic Signals

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. S. Najeem , M.C. Sanjana, G. Latha, P. Edwards Durai, 'Wind induced ambient noise modeling and comparison with field measurements in Arabian Sea', journal of Applied Acoustics, India, pp. 101–106, 2013.

. Bhagyashri Patil, Rajveer Shastri, Amab Das, „Wavelet De-noising with ICA for the Segmentation of bioacoustics sources in a Noisy Underwater Environment‟, International Conference on Communication and Signal Processing, IEEE, India, 2014.

. Ramesh D , „Denoising Algorithm using Wavelet for Underwater Signal Affected by Wind Driven Ambient Noise‟, International Journal of Electronics and Communication Engineering & Technology, Vol. 5, Issue 4, 2014.

. Aashish Sharma, “Underwater acoustic signal denoising Based upon Empirical Mode Decomposition and Discrete Wavelet Transform”, thesis, Electronics and Communication Engineering, Punjab, 2014.

. Selva Balan1, Arti Khaparde, Vanita Tank, Tejashri Rade and Kirti Takalkar, ‘Under Water Noise Reduction Using Wavelet and Savitzky – Golay’, CSIP, 2014.

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. Andrea Chang, Yu-Chen Cheng, Chi-Fang Chen, ‘Modeling of Shallow Water Ambient Noise based on Adiabatic Mode Theory’, IEEE, 2013.

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. George Tsolis and Thomas D. Xenos, ‘Signal Denoising Using Empirical Mode Decomposition and Higher Order Statistics’, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 4, No. 2, June, 2011.

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. S.Sakthivel Murugan, V.Natarajan, R.Rajesh Kumar, K.Balagayathri, ‘Analysis And SNR Comparison Of Various Adaptive Algorithms To Denoise The Wind Driven Ambient Noise In Shallow Water’, IEEE, 2011.

. F. Traverso and G. Vernazza, ‘Simulation of non-White and non-Gaussian Underwater Ambient Noise’, IEEE, 2011.

. Zhao Hong-tu, Xi Dong-mei, ‘Analysis on Algorithm of Wavelet Transform and Its Realization in C Language’, Proceedings of the Third International Symposium on Electronic Commerce and Security Workshops, China, pp.246-248, 2010.

. Yating Lin, Jianli Cai, ‘A New Threshold Function for Signal Denoising Based on Wavelet Transform’, International Conference on Measuring Technology and Mechatronics Automation, pp. 200-203, 2010.

. Tomoki Oku, Kazuma Hara, Masahiro Yoshida, Makoto Yamanaka, Haruhiko Murata, ‘Development of an underwater noise reduction technology’, Vol. 5, Japan, pp.1-4, 2009.

. Andrew C. Singer, Jill K Nelson, Suleyman S.Kozat, in their paper ‘Signal Processing for Underwater Acoustic Communications’, IEEE communications Magazine, pp 90-96, 2009.

. M. Sifuzzaman1, M.R. Islam and M.Z. Ali ‘Application of Wavelet Transform and its Advantages Compared to Fourier Transform’, IEEE, 2009.

. LIU Wen-bo, JIANG Li-bo, WANG Meng-xiao, ‘Research of Signal Denoising Algorithm Based on Wavelet Threshold’, IEEE, China, 2009.

. S. Ramji & S.Ramakrishanan, ‘Analysis of Short Term Temporal Fluctuations in Noise Power Spectrum of Shallow Water Ambient Noise’, IEEE, 2007.

Matthew W. Legg, Alec J. Duncan, Anthony Zaknich, Michael V. Greening, ‘Analysis of impulsive biological noise due to snapping shrimp as a point process in time’, IEEE, 2007.

. Nizamoddin Nezamoddini-Kachouie, Paul Fieguth, ‘A Gabor Based Technique for Image Denoising’, IEEE CCECE/CCGEI, Saskatoon, 2005.

DOI: http://dx.doi.org/10.26472/ijces.v1i7.37



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