Anjali are some major steps for underwater signal de-noising.

Anjali singh1, Selva balan2 andProf Dr.R S kawitkar 3M.

E. Student, Dept. of Electronics, SinhgadCollege of Engineering, Pune, India1Professor, Dept.

of Electronics, Sinhgad Collegeof Engineering, Pune, India3AbstractUnderwater acoustics signal is the study of thepropagation of sound in water and the interaction of themechanical waves that constitute sound withthe water and itsboundaries. The water maybe in the dam, ocean, a lake or a tank. There are some frequencies affiliated with underwater acoustics are between10 Hz and 1 MHz .There are some major steps for underwater signal de-noising. The firststep deals with signal pre-processing which including amplifying, filtering,and take use of analogy / digital (AD) technique to save signals as digitalfile. The underwater acoustic signal is affected by ocean interferenceand ambient noise disturbance during its propagation in ocean. Acoustic wavesare the most important characteristic to convey data in underwater domain as apractical method.

But the oceans are increasingly exposed to sounds from humanactivities, such as shipping and the building of foundations for offshoreconstruction projects and other different noise. Keyword: under water acoustic signal,wavelet transform, signal processing, denoising, noise reduction 1       IntroductionBecause of the activities of people in the oceanare expanded, the field of underwater acoustics has been extensively developedin a variety of applications including acoustic communication, the detectionand location of surface and subsurface objects, depth sounders, and sub-bottomprofiling for seismic explorationl.underwater acoustic signals that received from ocean are the signalof ships radiated when it sails on the ocean. The aimof this paper is to develop a de-noising system and evaluate the effect ofwavelet de-noising processing for underwater acoustic signals. Noise hamperssonar data collection and related processing of the data to extract informationsince many of the signals of interest are of short duration and of relativelylow energy. Underwater signal transmission is a challenging task since theusable frequency range is limited to low frequency and the transmission ofelectromagnetic waves is impossible due to its high attenuation nature.The types of attenuationthat affects the sound signal are transmission loss, Spreading Loss,Attenuation Loss, Background noise like Self-Noise, Machinery Noise, FlowNoise, etc.

  1.1     MotivationHuman interactionis the study in under water acoustic signal, which is the rapidly growing topiceverywhere,  ·        Communicationpurpose·        Commercial·        WarshipAcoustic communications form an active field ofresearch with significant challenges to overcome, especially in horizontal,shallow-water channels.1.2     Objective Reduce noise in underwater for acoustic signal.

•         Sound propagationlosses•         Self-noise and ambientnoise, SNR•         Mixed Gaussian noise 2. Literature reviewA noise removal algorithm based on short-time Wiener filteringis described. An analysis of the performance of the filter in terms ofprocessing gain, mean square error, and signal distortion is presented. Noise hampers sonar data collection and relatedprocessing of the data to extract information since many of the signals of interestare of short duration and of relatively low energy 1.The evaluation is performed on a representative real data setof underwater acoustic records.

Rationales used to process the proposedevaluation are mean squared error, global signal-to noise ratio (SNR),segmental SNR and mean squared spectral error. These filters are generallydesigned by a calculation which involves the signal autocorrelation estimation,a difficult task in case of low SNR or presence of non-stationary components.Musical noise is a perceptual phenomenon that occurs when isolated peaks remainin the time-frequency representation after processing with spectral subtractionalgorithm 2.

The authors S.S.Murugan, et al 3 studied the real time datacollected from the Bay of Bengal at Chennai by implementing Welch, Barlett andBlackman estimation methods and improved the maximum Signal to Noise Ratio to42-51 dB.The authors Yen-Hsiang Chen et al 4 implemented a real timeadaptive wiener filter with two micro phones is implemented to reduce noisyspeech when noise signals and desired speech are incoming simultaneously.Sound travels rapidly through water – four times faster thanthe air. As in open air, sounds are transmitted in water as a pressure wave.They can be loud or soft, high- or low pitched, constant or intermittent, andvolume decreases with increasing distance from source.

Sound pressure is mostcommonly measured in decibels (dB). Underwater noise has been divided into two main types: • Impulsive: Loud,intermittent or infrequent noises, such as those generated by piling andseismic surveys • Continuous: Lower-level constant noises , such as thosegenerated by shipping and wind turbines These two types of MSFD-related noisehave different   impacts on marine life.In addition, mid-frequency naval sonar may be harmful to marine mammals. Thefrequency or pitch of the noise is also important, as animals are sensitive todifferent frequencies 5.The underwater acoustic signal is affected by ocean interferenceand ambient noise disturbance during its propagation in ocean.

Therefore thesignal reveal random process and time varying characteristics. The procedureconsists of three parts: First, wavelet transformation of the underwateracoustic signals. Secondly, threshold of wavelet coefficients. Thirdly, inversewavelet transformation of reconstructing modified signals 6Because of the activities of people in the ocean areexpanded, the field of underwater acoustics has been extensively developed in avariety of applications including acoustic communication, the detection andlocation of surface and subsurface objects, depth sounders, and sub-bottom profilingfor seismic exploration7.The Ultrasonic signal is most commonly used for the depthestimation. This signal is affected by various underwater noises which resultsin inaccurate depth estimation.

The objective of this paper is to provide noisereduction methods for underwater acoustic signal. In present work, the signalprocessing is done on the data collected using TC2122 dual frequency transduceralong with the Navy sound 415 echo sounder. There are two signal processingtechniques which are used: The first method is denoising algorithm based onStationary wavelet transform (SWT) and second method is Savitzky-Golay filter.The results are evaluated based on the criteria of peak signal to noise ratioand 3D Surfer plots of the dam reservoir whose depth estimation has to be done8. 3. Proposed WorkMinimize or remove the background noise signalsfrom the corrupted acoustic signal in underwater communication.

 4. References 1. C. W.

Therrien,K. L. Frack, Jr., N. Ruiz pontes” ashort-time wiener filter for noise removal in underwater acoustic data”,IEEE19972. Fabien Chaillan, Jean-Rémi Mesquida UgoMoreaud,PhilippeCourmontagne” PerformanceAssessment of Noise Reduction Methods Applied to Underwater Acoustic Signals”,IEEE 20163.

S.Sakthivel Murugan, V.Natarajan, S.

Kiruba Veni,K.Balagayathri,”Analysis of Adaptive algorithms to Improve the SNR of theAcoustic Signal affected due to wind Driven Ambient Noise in Shallow water”,IEEE 2011.4. Yen-Hsiangchen, Shanq-Jang Ruan, Tom Qi, “An Automotive Application of real time adaptivewiener filter for noise cancellation in a car environment,” IEEE,2012.5.

T. Tejaswi, V Vamsi Sudheera, SriK. V. R.

Chowdary” Removal ofDifferent Noises in Underwater Communication”, IJERT 20156. CHU-KUEI Tu,YAN-YAO JIANG “Development of Noise Reduction Algorithm for Underwater Signals”,IEEE 20047. Burdic, William S, Underwater acoustic system analysig, 2nd,Prentice Hall, 1991 8. Selva Balan,Arti Khaparde,Vanita Tank,Tejashri Rade and KirtiTakalkar” under water noise reduction usingwavelet and savitzky-golay”,CSIT 2014  5. ConclusionWe are studied about filters.

From these filtertechnique we can remove noise in under water acoustic signal. These are somemost useful techniques for noise reduction. I referred so many papers relatedto this topic. An algorithm for noise removal based on optimal filtering ofshort segments of the data has been developed. The algorithm was developed forimproved pro- cessing of underwater acoustic data.