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Volume 2, Issue 4, April 2013
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Application of the signal processing to
understand underwater environment using
passive acoustic techniques.
Sonali R. Patil 1, R. B. Lohani2
1,2
Department of Electronics and Telecommunication Engineering,
Goa College of Engineering, Farmagudi - Ponda, Goa-403401
ABSTRACT
This paper presents how ambient noise data extract the information about the shallow water from continental shelf off India.
Ambient noise because of its masking the signals received in the underwater acoustic systems, such as the sonar, echo
sounder, etc limits their useful range. To enhance the signal to noise ratio of acoustic instruments the ambient noise field
must be detected. Knowledge of ambient noise tells how sound producing activities affect the health and safety of large and
small creatures, that live in the sea. This paper describes a simplified method of acquiring acoustic information from a
combination of three hydrophones. The experiment is conducted in shallow water off Goa at a depth at 17 m. The statistical
analysis of the ambient noise data shows depth dependence. Our detailed analyses involve the histogram, the power spectral
density (PSD), Real/imaginary coherence and correlation studies. The result presented in this work would lead to locate and
identify the ambient noise in the shallow water areas.
Keywords: Passive Acoustics, Ambient noise.
1. INTRODUCTION
Ambient noise in the ocean is generally considered to be the noise from all sources excluding those that are close
enough to be detected individually (on an omni-directional hydrophone). For example, the general background
noise from shipping is considered to be part of the ambient noise, but not the noise of an individual passing ship.
Sounds of an individual whale close by might also be considered to be not part of the ambient noise, though if many
animals are calling to the extent that their calls provide an almost continuous background noise, that might be
considered to be ambient noise. [1]
Acoustic wave is the best medium of signal transmission in the ocean, since the electromagnetic (EM) waves will be
spread due to its high frequency. Thus, identification and recognition of acoustic signals has become the primary issue
of underwater techniques. Ocean ambient noise is the background noise in the absence of individual particular sources
[2]. The sources of ambient noise in an ocean environment consist of man-made as well as natural sources. Man-made
noise is generated by a variety of activities, including commercial shipping, oil and gas exploration, development, and
production, naval operations, fishing, research and other activities such as construction, ice breaking, and recreational
boating. Natural sources of noise include processes such as earthquakes, wind-driven waves, rainfall, bio-acoustic
sound generation, and thermal agitation of the seawater [3].
This work envisages recording and signal processing of the ambient noise data from the western continental shelf off
Goa at different location to extend our understanding of the variability of noise and the cause thereof. The techniques of
recording the ambient noise under varying ocean environmental conditions can be realized through use of ‘spatial’ and
/ or ‘temporal’ signal processing using single or an array of hydrophones. Here, ambient noise measurements were
carried out using three calibrated omni-directional hydrophones mounted in a vertical array at different depth. We
present analyses and data recorded from the area where the system was deployed at 17-m depth off Goa, India on 14
January 2013.
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Volume 2, Issue 4, April 2013
ISSN 2319 - 4847
Figure 1. Ambient noise measurement requirements
1.1 Materials used
There are three major components employed to acquire ambient noise data as shown in Figure (1).they are
Hydrophones and accessories , Data Acquisition system , and Personal Computer
1. Hydrophones are electromechanical transducers that receive sound. Pressure and voltage affect the piezo electric materials. Sensitivity and frequency response must be known for quantative measurements.
2. Software-Timed Acquisitions—With a software-timed acquisition, software controls the rate of the acquisition.
Software sends a separate command to the hardware to initiate each ADC conversion. In NI-DAQmx,
software-timed acquisitions are referred to as having on-demand timing. Software-timed acquisitions are also
referred to as immediate or static acquisitions and are typically used for reading a single sample of data.
3. The CPU in the PC reads data from the DAQ device whenever the CPU receives a software signal to acquire a
single data point.
Out of these hydrophone is the heart of the system.
2. DATA AND METHODOLOGY
The hydrophone was suspended from the measurement platform using the rope and mounting arrangement at 3 m, 7
m, 15 m respectively. The hydrophone has a receiving sensitivity of -185 dB over a wide frequency range 0.1 Hz to
120 kHz. The data were acquired at a rate of 3 kHz, digitized and filtered with portable data acquisition system. During
the period of data collection all machinery on the ship were turned off and the recording system was powered by battery
[6]. The wind speed and sound velocity was simultaneously measured during each sampling. The data acquired at the
sampling rate of 10 kHz over a period of 18.5sec is used for analysis. Shallow water ambient noise database was
developed using NI-USB- 6216 acquisition software. The ambient noise data was collected at each second at each
location by suspending the hydrophones in water. So simultaneously data from 3 hydrophones get stored in the
database. Figure (3) shows recorded three hydrophone data in volt. Here, jagged lines represent voltage data at different
depth and it shows the ambient noise and how the amplitude of the data varies at different depth.
Figure 2 Data collection setup on field
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ISSN 2319 - 4847
TABLE 1: SENSOR SPECIFICATIONS
SPECIFICATION
Description
Hydrophone type
Sensitivity
Beam pattern
C55(1)
-185 dB re 1V/ µPa
Omni directional below 10
kHz ;
Very directional at high
frequencies -3 dB
0.020 to 44
20
-40 to 60 ºC
460 m
16 bits
ADC only
ADC only
Linear Frequency Range
Preamplifier Gain
Operating temperature
Range
Maximum Operating depth
Resolution
Linearity
S/N+ distortion
2.1 Equations
The sound pressure level (SPL) measured by a hydrophone can be determine from the knowledge of the hydrophone
sensitivity free field sensitivity, the gain in the measurement system and the amount of voltage measured. Let Mh be the
free field voltage sensitivity of a hydrophone in dB re 1V/µPa, and the hydrophone is connected to an amplifier of gain
G in dB, then the SPL in dB re 1 µPa is given by the equation, as in
SPL = |Mh| - G + 20log Vavg
(1)
3. ANALYSIS
The raw data from hydrophone at different depth were plotted the analysis can detect how the data is affected at
different depth due to different parameters like wind in sea and temperature. The power spectral density (PSD)
expressed in Pa2/Hz. It is sampled into a number of points centered around equally spaced times. Fig. 3 presents the
jagged lines which represent voltage data at different depth and it shows the ambient noise and how the amplitude of
the data varies at different depth. Fig. 4 shows the MATLAB implementation of Welch's method that gives the Power
Spectral Density (PSD) for different depth. Fig. 5 shows the power density function.
Coherence or normalized cross spectrum density gives the degree to which the noise pressures are invariant. It is a
significant property of noise field and forms the basis for finding the directivity of ambient noise. Also coherence study
reveals the noise field invariance with respect to space and time. In shallow water, often wind/wave generated noise
have variable spatial distributions. Figure (6 and 7) shows how the surface wave affects at 3m depth. Taking vertically
separated hydrophones, equation (4) from the
12
=
S12
(2)
S11 * S 22
Figure 3 The jagged lines represent voltage data at different depth
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Figure 4 Noise spectrum at different depth
4
4
Histogram data at 10 kHz
x 10
mean= -1.2089e-014
2
0
-1
4
x 10
4
-0.5
0
Histogram data at 10 kHz
V
0.5
mean=1.6542e-013
2
0
-0.6
-0.4
-0.2
4
4
x 10
0
0.2
0.4
V
Histogram data at 10 kHz
0.6
0.8
mean=-1.0530e-013
2
0
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
V
Figure 5
Power Density Function at different depth
real coherence at 10 kHz
1
3m depth
7m depth
17m depth
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
0
1000
2000
Figure 6
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3000
4000 5000 6000
Frequency (kHz)
7000
8000
9000 10000
Real Coherence at different depth
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Volume 2, Issue 4, April 2013
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Imaginary coherence at 10 kHz
1
3m depth
7m depth
15m depth
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
0
1000
Figure 7
2000
3000
4000 5000 6000
Frequncy (kHz)
7000
8000
9000 10000
Imaginary Coherence at different depth
4. CONCLUSION
The temporal fluctuations of the noise levels are mostly due to wind. The results illustrate that the effect of wind is
dominant at the shallower hydrophone depth of 3 m compared to other depths. The computed Power Spectral Density
also supports the fact that, the energy is the higher at 3 m depth (as shown in Fig. 4), and progressively decreases with
the depth. However, undulations towards the very low frequency end for all the three curves indicate shipping noise.
The characteristics of the Probability Density Function is also found to be changing.
References
[1] "Ocean ambient noise: its measurement and its significance to marine animals " by Douglas H. Cato Defense
Science and Technology Organisation, and University of Sydney Institute of Marine Science, Sydney, NSW 2006
Australia.
[2] Peter H. Dahl, James H. Miller, Douglas H. Cato, Rex K. Andrew, “Underwater Ambient Noise”, Acoustics Today,
January 2007.
[3] John A. Hildebrand, “Anthropogenic and natural sources of ambient noise in the ocean”, Acoustics in marine
ecology Vol. 395: 5–20, 2009.
[4] Urick R. J. 1967.Principles of underwater sound, Third edition McGraw-Hill, New York. U.S.A. 423 pp. ISBN 007-066086-7
[5] Kato Douglas H."Advances in Ocean Acoustic" Jixun Zhou, Zhenglin Li, Jeffrey Simmen , Melville, New
York, 2012, AIP Conference Proceedings, 1495.ISBN 978-0-7354-1107-4, ISSN 0094-243X.
[6] Carey William. M ; Evans Richard B."Ocean Ambient Noise”, Springer
[7] M. C. Sanjana and G. Latha , “ Midfrequency Ambient Noise Notch using Time-Series Measurement in
Bay of Bengal”, IEEE Journal of Oceanic Engineering, Vol. 37,NO. 2,April 2012.
[8] Lurton, Xavier; An Introduction to Underwater Acoustics: Principal and Application, Springer; Praxis Publ.,2002 ;
ISBN 3-540-42967-0
[9] [http://dx.doi.org/10.1121/1.4768885]
AUTHOR
R.B.Lohani received the ph .D , M.E and B.E degrees in Electronic Engineering in 1998,1992 and
1988, respectively. He is a Principal and Professor of Goa College of Engineering ,Farmagudi-Ponda
Goa. He has published about 30 papers in National International Conferences Workshop/Journals. He is
expert member of various committees AICTE and GPSC. His areas of interest are
Microelectronics,
Instrumentation, Optical communication, High speed optical device and communication.
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