Journal of Electromagnetic Analysis and Applications, 2015, 7, 53-60 Published Online March 2015 in SciRes. http://www.scirp.org/journal/jemaa http://dx.doi.org/10.4236/jemaa.2015.73006 How to cite this paper: Khan, M.M., Ashique, R.H., Liya, B.N., Sajjad, Md.M., Rahman, Md.A. and Amin, M.T.H. (2015) New Wavelet Thresholding Algorithm in Dropping Ambient Noise from Underwater Acoustic Signals. Journal of Electromagnetic Analysis and Applications, 7, 53-60. http://dx.doi.org/10.4236/jemaa.2015.73006 New Wavelet Thresholding Algorithm in Dropping Ambient Noise from Underwater Acoustic Signals Mohammad Monirujjaman Khan, Ratil Hasnat Ashique, Badrun Naher Liya, Md. Mohsin Sajjad, Md. Anisur Rahman, M. T. Hasan Amin Department of EEE, Primeasia University, Dhaka, Bangladesh Email: monirkhan.qmul@gmail.com Received 9 February 2015; accepted 28 February 2015; published 3 March 2015 Copyright © 2015 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ 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 prob- lem 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. 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) 1. Introduction Compared to radio waves, acoustic waves have become the most effective way in underwater wireless commu- nication [1]. It is because radio waves are highly attenuated and spreading occurs due to high frequency. Hence they can propagate only over very short distances. On the other hand if acoustic waves are used, long distance communication can be established. However underwater wireless communication is still challenging due to fre- quency band limitation and underwater channel disturbances in the form of ambient noise. The disturbance is generated by both natural (seismic, wind marine animals, rain, breaking waves etc.) and manmade sources (shipping, other machineries etc.). We will discuss ambient noise properties in details and reducing algorithm