Localization and Tracking in Underwater Acoustic Networks via High Data-rate Multicarrier ...

117 Pages·2016·1.36 MB·English

by  Patrick E. Carroll

University of Connecticut
OpenCommons@UConn
Doctoral Dissertations University of Connecticut Graduate School
8-22-2014
Localization and Tracking in Underwater Acoustic
Networks via High Data-rate Multicarrier
Communications
Patrick E. Carroll
[email protected]
Follow this and additional works at:https://opencommons.uconn.edu/dissertations
Recommended Citation
Carroll, Patrick E., "Localization and Tracking in Underwater Acoustic Networks via High Data-rate Multicarrier Communications"
(2014).Doctoral Dissertations. 529.
https://opencommons.uconn.edu/dissertations/529
Localization and Tracking in Underwater Acoustic Networks via High
Data-rate Multicarrier Communications
Patrick Carroll, Ph.D.
University of Connecticut, 2014
Underwater sensor networks have seen huge strides within the past decade
as they approach viability both technologically and financially; though several
issues persist in their implementation. Of interest is localization, a key aspect
of sensor networks and navigation. This dissertation looks at several solutions,
corresponding to different scenarios:
• Global localization and tracking using surface anchor nodes: In a network-
ing context, supernodes deployed on the surface of a body of water can be
equipped with global positioning service (GPS) devices, and can act in a
time-synchronized fashion with certainty of their positions. We desire min-
imizing the use of messaging resources in the network by having only the
supernodes transmit information. A solution is developed for an unlimited
number of nodes which are capable of receiving the transmissions with no
more messaging than if there was one node. The various properties of the
algorithm will be tested in full deployments of networks of OFDM modems.
• Networklocalizationthroughon-demandprotocolswithasynchronousnodes
assuming only a known position: By allowing asynchronous nodes, a larger
Patrick Carroll––University of Connecticut, 2014
range of networking scenarios can be addressed. This is accomplished by
leveraging a simple reactive beaconing concept to maximize the amount of
information that can be obtained by nodes without requiring any trans-
mission from those nodes inside the network. The localization capabilities
of the algorithm will be rigorously tested using OFDM acoustic modems
deployed in realistic scenarios.
• Single-user localization for instantaneous position estimates: In the previ-
ous scenarios, localization takes place over a window of many seconds. For
a network with mobile elements, such as autonomous underwater vehicles
(AUVs), this can degrade the accuracy of the solution considerably. To
solve this, instead of anchors transmitting to a node, the node transmits
a single burst to the anchors, who then combine information to compute
the exact location of the target node at the time of transmission. This
provides a much more accurate method in localizing mobile elements. The
dissertation goes beyond a single point-estimate of the node and considers
fusing the Doppler-estimation capabilities of OFDM modems with tracking
methods to provide a high-accuracy tracking solution.
Localization and Tracking in Underwater Acoustic Networks via High
Data-rate Multicarrier Communications
Patrick Carroll
B.S., University of Connecticut, Storrs, CT, 2009
M.S., University of Connecticut, Storrs, CT, 2011
A Dissertation
Submitted in Partial Fulfillment of the
Requirements for the Degree of
Doctor of Philosophy
at the
University of Connecticut
2014
Copyright by
Patrick Carroll
2014
APPROVAL PAGE
Doctor of Philosophy Dissertation
Localization and Tracking in Underwater Acoustic Networks via High
Data-rate Multicarrier Communications
Presented by
Patrick Carroll, B.S. M.S.
Major Advisor
Shengli Zhou
Associate Advisor
Peter Willett
Associate Advisor
Jun-Hong Cui
University of Connecticut
2014
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ACKNOWLEDGEMENTS
I would like to extend my thanks and appreciation to my advising professor,
Dr. Shengli Zhou, for all he has done in helping me complete this thesis. He
created opportunities for me I did not think existed, guided me when I was sure
I was lost, and encouraged me to go beyond what I thought I was capable of. He
taught by example, and showed that with discipline, commitment, a level head,
and a methodical approach, any problem can be solved. I can only hope to follow
his teachings and achieve enough to make him proud.
I would also like to thank my advisory committee members, professor Peter
Willett and professor Jun-Hong Cui. Both have shared their wisdom and insight
as I have moved toward the completion of this thesis. Ultimately, they have
both contributed a great deal in shaping both myself and this thesis to be better
then I could have hoped to accomplish alone. I would also like to thank all the
professors at the UCONN Department of Electrical Engineering for what they
have taught me over these last few years.
I would like to thank those whom I have worked with in the lab during the
course of my degree: Hao Zhou, Janny Liao, Xiaoka Xu, Zheng (James) Peng,
Lei Wang, Kaleel Mahmood, Katherine Domrese, Yi Huang, Li Wei, and Yuzhi
Zhang. I owe almost all of my results to them for their aid in preparing and
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performing the many tests that lead to the completion of this thesis. Further,
I would like to extend my gratitude to my peers who shared their knowledge
and feedback as I worked my way towards my degree: Kevin Romeo, Marianne
LaRosa, Zhaohui Wang, David Crouse, Sora Choi, Nayeff Najjar, and Ting Yuan.
Finally, I would like to thank my family for all their support during this long
journey: my parents Sean and Diane, my loving and understanding wife Chrys,
and my adorable son Ian. Their love gave me the motivation to continuously
push forward and finally reach this goal.
Thank you all.
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TABLE OF CONTENTS
Chapter 1: Introduction 1
1.1 Motivation and Challenges . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Outline of the Dissertation . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Chapter 2: Underwater Localization and Tracking of Physical
Systems 6
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 System Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3 Timing of Messages . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.4 Localization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.4.1 Exhaustive Search . . . . . . . . . . . . . . . . . . . . . . 14
2.4.2 Least Squares Solution . . . . . . . . . . . . . . . . . . . . 15
2.5 Tracking Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.5.1 Kalman Filter . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.5.2 Probabilistic Data Association Filter . . . . . . . . . . . . 19
2.5.3 Interacting Multiple Model (IMM) Filter . . . . . . . . . . 22
2.5.4 Computational Complexity . . . . . . . . . . . . . . . . . . 25
2.6 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.7 Pool Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.7.1 Test Case 1 (Stationary test, March 2010) . . . . . . . . . 29
vi
2.7.2 Test Case 2 (Mobile test, December 2010) . . . . . . . . . 31
2.8 A Field Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Chapter 3: On-Demand Asynchronous Localization for Underwa-
ter Sensor Networks 35
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.2 Localization Protocol . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.3 Initiator Node Localization . . . . . . . . . . . . . . . . . . . . . . 43
3.4 Passive Node Localization . . . . . . . . . . . . . . . . . . . . . . 45
3.5 Cramer-Rao Lower Bound . . . . . . . . . . . . . . . . . . . . . . 46
3.5.1 The LBL solution for the initiator node . . . . . . . . . . . 47
3.5.2 The silent positioning solution for the passive node . . . . 49
3.5.3 The ODAL solution for the source node . . . . . . . . . . 50
3.6 Discussions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.6.1 Communication Failure . . . . . . . . . . . . . . . . . . . . 51
3.6.2 Potential Collisions . . . . . . . . . . . . . . . . . . . . . . 52
3.6.3 Message Length . . . . . . . . . . . . . . . . . . . . . . . . 53
3.6.4 Duration of The Localization Procedure . . . . . . . . . . 54
3.6.5 Localization Algorithms . . . . . . . . . . . . . . . . . . . 55
3.7 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.7.1 Scenario Setup . . . . . . . . . . . . . . . . . . . . . . . . 57
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