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Localization of Submerged Sensors Using a Single Mobile Beacon
by
Anisur Rahman
School of Information and Communication Technology
Griffith Sciences
Griffith University
August 2015
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Anisur Rahman 2015
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To my Mum & Dad
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Statement of Originality
This work has not previously been submitted for a degree or diploma in any university. To
the best of my knowledge and belief, the thesis contains no material previously published
or written by another person except where due reference is made in the thesis itself.
_____________________________
Anisur Rahman
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Acknowledgements
I would like to thank my supervisor Vallipuram Muthukkumarasamy and Xin-Wen Wu.
Their encouragement and support throughout the PhD candidature have been vital and
appreciated. I also thank my peer group for their valuable inputs in this endeavor.
The sacrifices and encouragement of my wife would always be remembered and
appreciated. I only wish my son Shomoy and daughter Nohor could have understood
why I cant play with them like I used to.
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List of Publications
A. Rahman, V. Muthukkumarasamy, and X. Wu, Coordinates and Bearing of
Submerged Sensors Using a Single Mobile Beacon (CSMB), Journal of Networks,
2015 (accepted)
A. Rahman, V. Muthukkumarasamy, and E. Sithirasenan, "The Effect of in-situ
Underwater Acoustic Speed on Localization of Submerged Sensors" in PhD
Forum of World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2014.
A. Rahman, V. Muthukkumarasamy, and E. Sithirasenan, "Localization of
Submerged Sensors". Book Chapter: Nova Publishing Inc. 2014.
A. Rahman, V. Muthukkumarasamy, and E. Sithirasenan, "Localization of
Submerged Sensors Using Radio and Acoustic Signals with Single Beacon," in
Ad-hoc, Mobile, and Wireless Network. LNCS. vol. 7960, J. Cicho, M. Gbala, and
M. Klonowski, Eds., ed: Springer Berlin Heidelberg, pp. 293-304, 2013.
A. Rahman, V. Muthukkumarasamy, and E. Sithirasenan, "The Analysis of
Temperature, Depth, Salinity Effect on Acoustic Speed for a Vertical Water
Column," in Distributed Computing in Sensor Systems (DCOSS), IEEE, pp. 310-312,
2013.
A. Rahman, V. Muthukkumarasamy, and E. Sithirasenan, "Coordinates
Determination of Submerged Sensors Using Cayley-Menger Determinant," in
Distributed Computing in Sensor Systems (DCOSS), IEEE, pp. 466-471, 2013.
A. Rahman, V. Muthukkumarasamy, and X. Wu, Underwater Localization: a
pragmatic Approach. IEEE Communication Magazine of Underwater Wireless
Communications and Networks: Theory and Applications, 2015. (submitted)
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Abstract
nswerving navigation and positioning are becoming imperative in more and more
underwater applications for the sustenance of flora and fauna of our marine biome.
As marine life helps determine the very nature of our planet at a fundamental level, it
becomes crucial to obtain accurate environmental data by using underwater sensors to
enable the provision of underwater sanctuary areas. In addition, an underwater wireless
sensor network (UWSN) is envisioned to enable application for offshore exploration for
the profusion of the wealth underwater world has. It is not only monetary value, it is also
deemed necessary to introduce controlled underwater vehicles for surveillance, to find lost
objects and to track pollutants. Due to all these potential factors, researchers have shown
fervent interest in exploring and exploiting underwater localization schemes to fulfill the
multitude of needs as the time demands. To achieving such, a wide range of sensors are
deployed underwater to gather data. Many a times, precise coordinates of the deployed
sensors which actuate or collect data are vital, as data without the knowledge of its actual
origin has limited value. So, a pragmatic dynamic approach is obligatory to localize
submerged sensors precisely with minimal logistics, which will require no preinstalled
infrastructure and reference points.
A plethora of techniques has been proposed to determine the coordinates of
submerged sensors, each with its own limitations. Preinstalled infrastructure, multiple
references and auxiliary nodes are commonly used; whereas a single reference point, like a
boat, should suffice to localize the sensors for any problem domain without the complexity
and tedium of installing reference points. Moreover, the multilateration technique is used
to determine the location of the sensors with respect to three or more known beacon
nodes. Furthermore, incorporated nonlinear distance equations are solved by conventional
methods whereby degree-of-freedom does not guarantee a unique solution. This thesis
investigates the problem of localizing submerged sensors and advocates a closed-form
solution to determine the coordinates and bearings of those using only a single beacon
node at the surface. The propounded method is capable of continuous localization of
submerged sensors with precision, in a dynamic fashion, without a preinstalled
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infrastructure or reference points. Moreover, the Cayley-Menger determinant and linearized
trilateration are used to determine the coordinates of the nodes where none of the nodes
have a priori knowledge about its location. Simulation results validate the mathematical
model proposed herein, by computing the coordinates of sensor nodes with bearing
information; thereby generating 10-12 to 10-14m positional error with 0.972% variation in
bearing with Euclidean distance.
Underwater distance determination between the beacon and sensor nodes is an
important factor in localization; and the use of acoustic signals has been the proven
technology so far. Usually, the bouncing technique or two-way message transfer is used to
measure the distances from beacon to sensors. In fact, the bouncing technique requires
lowering a reflector to a specific height, and the two-way message transfer method lacks
time synchronization. In both cases, measured distances and the unreliable time
synchronization are subject to a huge degree of error. Moreover, a default acoustic speed is
considered, regardless of problem domain, which also upsurge the errors in coordinate
determination. To minimize such distance determination error, a new method has been
devised here, in which in-situ acoustic speed is determined from the gathered environmental
variables (i.e. temperature, depth and salinity) from the vicinity of beacon and sensor
nodes. Therefore, due to the different nature of problem domain, the acoustic speed varies
and provides more accurate localization. It is logical to consider that with the advent of
incorporating 4th generation computing into the sensors; it is now indispensable to
reconsider the use of underwater radio to some extent. As such, the method uses radio
signals for time synchronization between the beacon and underwater sensors; and it
measures the flight time of generated acoustic signals from the beacon to the sensors.
Simulation results show in-situ determination of acoustic speed for various problem
domains with different combinations of environmental variable varies from 1499.8-
1507.6m/s and the experimental results also confirm the potential of determining flight
time of acoustic signals between two nodes.
This research could be extended to address and consider the mobility of the
submerged sensors while localizing. Voluntary or involuntary mobility can be analyzed to
find the Doppler effect, as UWSN is more susceptible than WSN. Therefore, mobility
introduces another challenge from the view point of communications overheads and
energy-efficiency, since underwater equipment is expected to be left in the ocean for
several weeks or months before it is collected and recharged for the next mission. Another
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interesting research direction could be inventing sensors and methods which can detect
lower radio signals and can be capable of better communication, so that all
communications can be replaced by radio instead of acoustic signals as done
conventionally.
To conclude, the model delineates the determination of in-situ underwater acoustic
speed; as well as the coordinates and bearings determination in a pragmatic fashion with a
single beacon. Scrupulous accuracy in simulation and experimental result shows the
potential of proposed model in coordinate determination of submerged sensors with a
single beacon.
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Contents
CHAPTER 1 INTRODUCTION ............................................................................ 1
CHAPTER 2 BACKGROUND .............................................................................. 7
2.5.1.1 Time of Arrival (ToA) Measurements ...................................... 25
2.5.1.2 Time Difference of Arrival (TDoA) Measurements ............... 26
2.5.1.3 Received Signals Strength Measurements ................................ 28
2.6.1.1 Infrastructure-based Positioning Schemes ............................... 34
2.6.1.2 Distributed Positioning Schemes .............................