ANCHOR POSITION ESTIMATION FOR USE IN AD HOC WIRELESS

73 Pages·2007·1.41 MB·English

ANCHOR POSITION ESTIMATION FOR USE IN AD HOC
WIRELESS SENSOR LOCALISATION
A dissertation submitted in part fulfilment of the requirements for the
Open University’s Master of Science Degree in Computing for Commerce
and Industry

Rory Galvin
(U8689009)
Open University
11th March 2007

word count: 13695
Preface
The research presented in this dissertation was performed at the Faculty of
Mathematics & Computing, Open University, Milton Keynes, between February 2006
and March 2007. The experimentation took place in Bristol, a city with a rich history
of research in wireless localisation.
The greatest challenge to the realisation of ad hoc localisation solutions is the lack of
deployed and accessible infrastructure. Is it any surprise that telecommunications
companies, who charge us so much for our wireless data transfer, will not make GSM
beacon data freely available for ad hoc localisation? This dissertation was conceived
in the spirit of War Driving, as a community response to this restriction of data. My
ultimate goal is to take the ideas herein and build something practical for free and
public use.
Acknowledgments
I would like to thank everyone who supported me during this project. First and
foremost, I thank Rob Walker, who has hauled me into the world of scientific thinking
and rigor, and provided the technical edge and steady hand of experience. Thanks also
to Blaine Price for his initial encouragement to take the topic. It has proved a good
choice. I am wholly indebted to Angus Benjafield for providing equipment, software,
continual interest in the project, and genuine pearls of insight at just the right time.
Thanks too, to John Honniball for useful sources of information and informal advice
on methods and tools, and to Matt Bowers for his understanding towards the end.
Thanks must go to my father Roddy, for critical analysis at the critical time, and to my
mother Maureen for all things. Finally, and most of all, I thank Faye, Jessica, Abigail,
Conor, and Lilly-Moo, without whom all of this would be pointless.
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Table of Contents
LIST OF FIGURES...........................................................................................................5
LIST OF TABLES.............................................................................................................6
ABSTRACT.......................................................................................................................7
CHAPTER 1. INTRODUCTION AND PROBLEM OVERVIEW..............................8
1.1 AIM OF PROPOSED RESEARCH..................................................................................11
CHAPTER 2. LITERATURE REVIEW.......................................................................13
2.1 WHY GPS IS NOT ENOUGH.......................................................................................16
2.2 WHAT IS ‘ACCURATE ENOUGH’?...............................................................................18
2.3 PRIVACY CONCERNS AND THE IMPLICATIONS FOR LOCALISATION............................20
2.3.1 Self Localisation...............................................................................................21
2.3.2 Single or Multihop............................................................................................22
2.4 INFRASTRUCTURE AND THE PROBLEM OF MAPPING BEACONS IN THE WILD...............24
CHAPTER 3. RESEARCH METHODOLOGY..........................................................29
3.1 CHOOSING A RESEARCH METHOD............................................................................29
3.2 THE METHOD............................................................................................................33
3.2.1 Devising a fixed-beacon localisation scheme...................................................34
3.2.2 Scope of experimentation..................................................................................36
3.2.3 Data Collection.................................................................................................37
3.3 RESULTS AND ERROR...............................................................................................37
3.3.1 Systematic Bias.................................................................................................38
3.3.2 Effect of Distance on Triangulation.................................................................38
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CHAPTER 4. EXPERIMENTAL SETUP....................................................................40
4.1 TESTBED...................................................................................................................40
4.2 DATA COLLECTION: GATHERING NARROW-BEAM SIGHTINGS...................................42
5.2 TECHNICAL CONSIDERATIONS ..................................................................................45
CHAPTER 5. RESULTS................................................................................................46
5.1 TWO MEASURES OF ACCURACY.................................................................................46
5.1 ERROR EFFECTS OF OBSTRUCTION BEACON LOCALISATION.....................................47
5.2 BEACON LOCALISATION OVER DISTANCE.................................................................48
5.3 TESTING THE LIMITS OF BEACON LOCALISATION.....................................................49
CHAPTER 6. ANALYSIS..............................................................................................51
6.1 ESTIMATING BEACON POSITION...............................................................................51
6.2 USING THE METHOD TO MAINTAIN BEACON DATA....................................................54
6.3 EVALUATION OF THE METHOD AND EXECUTION......................................................55
6.4 RELATING BEACON ERROR TO AD HOC ERROR..........................................................56
CHAPTER 7. CONCLUSIONS.....................................................................................58
CHAPTER 8. IMPROVEMENTS AND FUTURE WORK........................................60
8.1 EXPLORING VARIATION IN ANCHOR POSITION ESTIMATION.......................................60
8.2 PRACTICAL IMPROVEMENTS.....................................................................................61
8.3 FUTURE WORK..........................................................................................................63
REFERENCES................................................................................................................65
APPENDIX A. SAMPLE POSITIONAL ESTIMATE CALCULATION.................73
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List of Figures
FIG 2.1: SAMPLE NETWORK IN THE TIM-BASED POSITIONING SCHEME..........................21
FIG 2.2: POSITION ESTIMATION IN HIRLOC USING CHANGES IN ANGLE OF ARRIVAL......22
FIG 2.3: POSITION ESTIMATION IN HIRLOC USING CHANGES IN RSSI RANGE.................23
FIG 3.1: VARIANCE IN BEACON LOCALISATION ERROR WITH DISTANCE..........................39
FIG 4.1: HYPERLINK H2424G REFLECTOR GRID FOR WI-FI SCANNING.........................40
FIG 4.2: HG2424G ANTENNA GAIN PATTERNS..............................................................41
FIG 4.3: GEOGRAPHIC AREA OF INTEREST FOR THE FIELD TEST......................................42
FIG 4.4: APVIEWER’S CATALOGUE OF VISIBLE WI-FI BEACONS......................................43
FIG 4.5: RANGE OF A BEACON’S SIGNAL IN A SCANNING SWEEP......................................44
FIG 6.1: LINE OF SIGHT FROM K2 TO THE BEACON CLUSTER...........................................52
FIG 6.2: LINE OF SIGHT FROM K3 TO THE BEACON CLUSTER...........................................52
FIG 6.3: ESTIMATION ERROR IN RELATION TO DISTANCE FROM BASE STATION...............53

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List of Tables
TABLE 2.1: CONTEXT-AWARE APPLICATIONS AND THEIR REQUIRED ACCURACY............19
TABLE 5.1: BEACON LOCATION ESTIMATION USING TRIANGULATION FROM K1 & K2...47
TABLE 5.2: BEACON LOCATION ESTIMATION USING TRIANGULATION FROM K1 & K3...47
TABLE 5.3: BEACON LOCATION ESTIMATION USING TRIANGULATION FROM K1 & K4...48

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Abstract
The ability to locate mobile nodes in a wireless sensor network is important for
context-aware applications and the emerging field of location based services. While
GPS is the leading commercial method for localisation, there are advantages to using a
device’s inherent networking capability to enable positioning. These include a
reduction in form factor, power drain, and cost. Because of its pervasive nature Wi-Fi
is a natural candidate for ‘built-in’ positioning capability. It has particular relevance in
an urban setting because of the high density of private access points that could be used
as positioning beacons. However, self-positioning of wireless sensor nodes depends
on the availability of a map of these reference nodes, or anchors. The effort required
to create and maintain such a map is a major challenge. We present a scheme for
locating Wi-Fi beacons in the wild in a defined area using triangulated signals from
directional Wi-Fi antennae. Under good conditions and a clear line of sight to target,
this method achieves a median accuracy of 4.5% of the average distance between the
anchor and its two detecting antennae. When base stations are 200m from the target
beacons, this equates to an average error in beacon estimation of 9m. With an
obstructed line of sight between base station and beacon, the average weighted error
rises to 8.1%. We have also located beacons to within 8% accuracy up to 1.4Km from
the base station pair.
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Chapter 1. Introduction and Problem Overview
Low cost ubiquitous computing has become a popular research domain, and holds a
particular relevance for wireless networks and applications. Localisation, a term
borrowed from the field of Robotics, refers to the ability of a wireless sensor network
to identify physical position of nodes in its network. This facility is necessary for the
provision of Location Based Services (LBS).
A valuable example of such an application is the FCC’s E911 service in the US
(Federal Communications Commission, 2006), which enables emergency services to
establish the caller’s approximate position from cell-phone signal alone.
SmartRestaurant (Lukkari at al., 2004) is a mobile order and payments facility. The
system aims to entice users passing close to the restaurant with relevant ‘push-type
mobile advertising’ onto mobile devices. There is a growing consensus that LBS and
context-aware applications represent a rapidly expanding area for wireless networks.
There are many ways of determining the position of unknown sensor nodes in a
wireless network. Ultimately, all of these require reference to nodes of known position
to operate effectively. Simple proximity based schemes (Bulusu et al., 2000), offer a
low accuracy solution using just one anchor node. Schemes employing triangulation
derive position from the direction of signals from at least two references points.
Schemes relying on multilateration (e.g. Savvides et al, 2001), or trilateration require
at least three. These are examples of range or angle-based schemes.
The Placelab scheme (LaMarca et al, 2005) uses profiling (or fingerprinting) based on
signals from Global System for Mobile communications (GSM), Wi-Fi or Bluetooth
beacons at certain locations. A probabilistic method is then used to estimate the
location of an unknown sensor node. Haeberlen et al. (2004) give a good example of a
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similar approach on large scale indoor network in which a great deal of training is
required to map-out beacon signatures which unknown sensor nodes can later use to
estimate their most likely position.
Common to all of these techniques is their dependency on beacons of known location,
or ‘anchors’, as positional reference points. This dissertation examines the role
wireless network anchors play in localisation and on how the accuracy of their
recorded position affects the localisation problem.
The Global Positioning System (GPS) has become an important means of localisation
to support LBS. Good examples are car navigation and consignment tracking systems
and researchers are looking for new ways to use existing deployed infrastructure to
achieve the same goal. GPS sets have shrunk in size dramatically in the last five years
but the technology has not yet achieved cheap and seamless integration with laptops,
PDAs, watches, and other personal devices. The extra power drain GPS chipsets
impose on the mobility of hardware is a significant factor. According to ABI Research
(2004) the cost of integrating GPS chips acts as an inhibitor to its adoption in the
manufacture of GSM handsets. Crucially, GPS suffers from some insurmountable
coverage limitations, most obviously when nodes are underground or inside a building
complex. The disruptive effects of a city’s ‘urban canyons’ are also cited (Borriello
and Hightower, 2005).
GPS-less localisation, in particular utilizing wireless LAN technology (802.11 or Wi-
Fi), is an attractive solution. The ubiquitous nature of GSM and Code Division
Multiple Access (CDMA) in the developed world and 802.11 beacons in most cities
provides an existing deployed infrastructure. The technology that provides positioning
capability is already integrated with the applications that use it. Several challenges
remain, particularly with regard to accuracy and coverage. During the past six years
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there has been keen research interest in the accuracy and predictability of positioning
in ad hoc networks.
A major difficulty with modelling ad hoc positioning systems is that many factors can
cause inaccuracy in real world localisation. How the assumptions that researchers
make about their localisation models hold up when applied ‘in the wild’ is a significant
question (Kotz, 2004). The scope of the localisation exercise – indoor, outdoor, lab,
urban, suburban, rural - introduces its own particular set of constraints. Environmental
factors such as weather, time of day, Radio Frequency (RF) noise, variations in urban
terrain inducing RF propagation, shadowing and urban canyons can all degrade the
system’s accuracy. Of particular importance factor is the saturation of anchor points,
or more precisely the distance between them (Cheng et al., 2005).
Perhaps the most important environmental factor is how the scheme manages the
relationship between the mobile sensors and the system of coordinates and landmarks
that defines their locale. However, an area that has received relatively little attention
to date relates to how the accuracy of anchor nodes used in various localisation
schemes affects the performance of those schemes.
The general problem of establishing reference information in a system is one of
calibration. In a Wireless Sensor Network (WSN) dependant on geographic reference
points for resolution, calibration refers to the fixing of position of the anchor nodes.
Whitehouse and Culler (2005) in their work on sensor network calibration highlight
the reliance on infrastructure and the fact that ad hoc networks do not have established
anchors for positioning is a challenge.
The problem of beacon node calibration in an ad hoc WSN raises two questions. How
is this information collected and how is it maintained? Researchers studying
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