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Anjali singh1, Selva balan2 and
Prof Dr.R S kawitkar 3

M.E. Student, Dept. of Electronics, Sinhgad
College of Engineering, Pune, India1

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Professor, Dept. of Electronics, Sinhgad College
of Engineering, Pune, India3

Abstract

Underwater acoustics signal is the study of the
propagation of sound in water and the interaction of the
mechanical waves that constitute sound with
the water and its
boundaries. The water may
be in the dam, ocean, a lake or a tank. There are some frequencies affiliated with underwater acoustics are between
10 Hz and 1 MHz .There are some major steps for underwater signal de-noising. The first
step deals with signal pre-processing which including amplifying, filtering,
and take use of analogy / digital (AD) technique to save signals as digital
file. The underwater acoustic signal is affected by ocean interference
and ambient noise disturbance during its propagation in ocean. Acoustic waves
are the most important characteristic to convey data in underwater domain as a
practical method. But the oceans are increasingly exposed to sounds from human
activities, such as shipping and the building of foundations for offshore
construction projects and other different noise.

 

Keyword: under water acoustic signal,
wavelet transform, signal processing, denoising, noise reduction

1       Introduction

Because of the activities of people in the ocean
are expanded, the field of underwater acoustics has been extensively developed
in a variety of applications including acoustic communication, the detection
and location of surface and subsurface objects, depth sounders, and sub-bottom
profiling for seismic explorationl.underwater acoustic signals that received from ocean are the signal
of ships radiated when it sails on the ocean. The aim
of this paper is to develop a de-noising system and evaluate the effect of
wavelet de-noising processing for underwater acoustic signals. Noise hampers
sonar data collection and related processing of the data to extract information
since many of the signals of interest are of short duration and of relatively
low energy. Underwater signal transmission is a challenging task since the
usable frequency range is limited to low frequency and the transmission of
electromagnetic waves is impossible due to its high attenuation nature.

The types of attenuation
that affects the sound signal are transmission loss, Spreading Loss,
Attenuation Loss, Background noise like Self-Noise, Machinery Noise, Flow
Noise, etc. 

1.1     
Motivation

Human interaction
is the study in under water acoustic signal, which is the rapidly growing topic
everywhere, 

·        
Communication
purpose

·        
Commercial

·        
Warship

Acoustic communications form an active field of
research with significant challenges to overcome, especially in horizontal,
shallow-water channels.

1.2     
Objective

 Reduce noise in under
water for acoustic signal.

•         
Sound propagation
losses

•         
Self-noise and ambient
noise, SNR

•         
Mixed Gaussian noise

 

2. Literature review

A noise removal algorithm based on short-time Wiener filtering
is described. An analysis of the performance of the filter in terms of
processing gain, mean square error, and signal distortion is presented. Noise hampers sonar data collection and related
processing of the data to extract information since many of the signals of interest
are of short duration and of relatively low energy 1.

The evaluation is performed on a representative real data set
of underwater acoustic records. Rationales used to process the proposed
evaluation are mean squared error, global signal-to noise ratio (SNR),
segmental SNR and mean squared spectral error. These filters are generally
designed 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 remain
in the time-frequency representation after processing with spectral subtraction
algorithm 2.

The authors S.S.Murugan, et al 3 studied the real time data
collected from the Bay of Bengal at Chennai by implementing Welch, Barlett and
Blackman estimation methods and improved the maximum Signal to Noise Ratio to
42-51 dB.

The authors Yen-Hsiang Chen et al 4 implemented a real time
adaptive wiener filter with two micro phones is implemented to reduce noisy
speech when noise signals and desired speech are incoming simultaneously.

Sound travels rapidly through water – four times faster than
the 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, and
volume decreases with increasing distance from source. Sound pressure is most
commonly 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 and
seismic surveys • Continuous: Lower-level constant noises , such as those
generated by shipping and wind turbines These two types of MSFD-related noise
have different   impacts on marine life.
In addition, mid-frequency naval sonar may be harmful to marine mammals. The
frequency or pitch of the noise is also important, as animals are sensitive to
different frequencies 5.

The underwater acoustic signal is affected by ocean interference
and ambient noise disturbance during its propagation in ocean. Therefore the
signal reveal random process and time varying characteristics. The procedure
consists of three parts: First, wavelet transformation of the underwater
acoustic signals. Secondly, threshold of wavelet coefficients. Thirdly, inverse
wavelet transformation of reconstructing modified signals 6

Because of the activities of people in the ocean are
expanded, the field of underwater acoustics has been extensively developed in a
variety of applications including acoustic communication, the detection and
location of surface and subsurface objects, depth sounders, and sub-bottom profiling
for seismic exploration7.

The Ultrasonic signal is most commonly used for the depth
estimation. This signal is affected by various underwater noises which results
in inaccurate depth estimation. The objective of this paper is to provide noise
reduction methods for underwater acoustic signal. In present work, the signal
processing is done on the data collected using TC2122 dual frequency transducer
along with the Navy sound 415 echo sounder. There are two signal processing
techniques which are used: The first method is denoising algorithm based on
Stationary wavelet transform (SWT) and second method is Savitzky-Golay filter.
The results are evaluated based on the criteria of peak signal to noise ratio
and 3D Surfer plots of the dam reservoir whose depth estimation has to be done
8.

 

3. Proposed Work

Minimize or remove the background noise signals
from the corrupted acoustic signal in underwater communication.

 

4. References

1. C. W. Therrien,
K. L. Frack, Jr., N. Ruiz pontes” a
short-time wiener filter for noise removal in underwater acoustic data”,IEEE
1997

2. Fabien Chaillan, Jean-Rémi Mesquida UgoMoreaud,
PhilippeCourmontagne” Performance
Assessment of Noise Reduction Methods Applied to Underwater Acoustic Signals”,
IEEE 2016

3.S.Sakthivel Murugan, V.Natarajan, S.Kiruba Veni,
K.Balagayathri,”Analysis of Adaptive algorithms to Improve the SNR of the
Acoustic Signal affected due to wind Driven Ambient Noise in Shallow water”,
IEEE 2011.

4. Yen-Hsiang
chen, Shanq-Jang Ruan, Tom Qi, “An Automotive Application of real time adaptive
wiener filter for noise cancellation in a car environment,” IEEE,2012.

5. T. Tejaswi, V Vamsi Sudheera, Sri
K. V. R. Chowdary” Removal of
Different Noises in Underwater Communication”, IJERT 2015

6. CHU-KUEI Tu,
YAN-YAO JIANG “Development of Noise Reduction Algorithm for Underwater Signals”,
IEEE 2004

7. Burdic, William S, Underwater acoustic system analysig, 2nd,
Prentice Hall, 1991

 

8. Selva Balan,Arti Khaparde,Vanita Tank,Tejashri Rade and Kirti
Takalkar” under water noise reduction using
wavelet and savitzky-golay”,CSIT 2014

 

 

5. Conclusion

We are studied about filters. From these filter
technique we can remove noise in under water acoustic signal. These are some
most useful techniques for noise reduction. I referred so many papers related
to this topic. An algorithm for noise removal based on optimal filtering of
short segments of the data has been developed. The algorithm was developed for
improved pro- cessing of underwater acoustic data.

 

 

 

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