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XNav Indoor Navigation System Using RFID Technology

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Abstract and Figures

This project attempts to demonstrate the usage of Radio Frequency Identification (RFID) technologies in indoor navigation. The proposed solution for indoor navigation concentrates on three key elements of the complete process. XMap is the mapping module which allows the internal structure of a building to be mapped onto a software form. XSim is a simulation component which utilizes the XMap and simulates navigation inside a building or structure. XNav is the algorithm which calculates the position on the XMap which allows a user to identify his/her bearings and navigate from origin to destination. XNav client is the client software which in theory is installed on a portable computer (PDA). This software in turn can download various XMaps and use the inbuilt XNav algorithm to calculate the position of the user in an XNav enabled environment. The project methodology involved creating various real-time XMaps and simulating complex routes through them and identifying the accuracy of the actual XNav algorithm in a real-world scenario. This report concludes that XNav RFID technology can be accurately used in indoor navigation provided that the XMap is accurately designed for a particular indoor environment and XSim is used to determine the strategic positioning of the RFID tags through out the labyrinth.
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6
Title : XNav Indoor Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
XNav Indoor Navigation System Using RFID Technology
Dissertation
Title : XNav Indoor Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
2
Title : XNav Indoor Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
MSc Wireless Enterprise Business Systems
School of Engineering & Design
Brunel University
XNav Indoor Navigation System Using
RFID Technology
Student’s name: Ishan Sudeera Abeywardena
Signature of student:
______________
Declaration: I have read and I understand the Department’s guidelines on
plagiarism and cheating, and I certify that this submission fully complies
with these guidelines.
3
Title : XNav Indoor Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Abstract
This project attempts to demonstrate the usage of Radio Frequency Identification (RFID) technologies
in indoor navigation. The proposed solution for indoor navigation concentrates on three key elements
of the complete process. XMap is the mapping module which allows the internal structure of a building
to be mapped onto a software form. XSim is a simulation component which utilizes the XMap and
simulates navigation inside a building or structure. XNav is the algorithm which calculates the position
on the XMap which allows a user to identify his/her bearings and navigate from origin to destination.
XNav client is the client software which in theory is installed on a portable computer (PDA). This
software in turn can download various XMaps and use the inbuilt XNav algorithm to calculate the
position of the user in an XNav enabled environment. The project methodology involved creating
various real-time XMaps and simulating complex routes through them and identifying the accuracy of
the actual XNav algorithm in a real-world scenario. This report concludes that XNav RFID technology
can be accurately used in indoor navigation provided that the XMap is accurately designed for a
particular indoor environment and XSim is used to determine the strategic positioning of the RFID
tags through out the labyrinth.
Acknowledgements
I wish to dedicate this section to the people who encouraged me, believed in me and guided me all
through my life as an MSc student at Brunel University, Uxbridge, Middlesex, UK. I thank them all for
having undying faith in me and sacrificing their lunch times and much deserved breaks to listen to my
crazy theories, appreciate my long simulations and provide invaluable input into my research.
First of all I thank my Father, Shantha Abeywardena, a great man whom without I wouldn’t have been
able to write this dissertation as an International MSc student at Brunel University, UK.
Prof. Wamadeva Balachandran, a giant in the field of telecommunications and navigation systems, for
providing me with the opportunity of working under his supervision and guidance towards achieving
my goals and objectives in the context of my research. Thank you, Sir, for believing in me, my work
and my ability.
Dr. Ali Mousavi, for providing me with the opportunity of working as a research assistant at Brunel
University. Thank you Sir. I gained a wealth of knowledge from working under your supervision.
Mr. Dissanayake (Uncle Disa), without your gesture of kindness I wouldn’t be here today. Thank you.
Mr. Ranjiv Bhalla (my present employer), for believing in me, never giving up on me, always giving
priority to my studies and for helping me financially and spiritually to complete my MSc in the UK.
Thank you Sir and I am eternally indebted to you.
Last but not least, I thank my family, my fiancée and all my friends who stood by my side in the
sunshine and in the rain.
Thank you all.
4
Title : XNav Indoor Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Contents
Chapter
Title
Page
1.0 Introduction
6
2.0 Time Plan, Milestones & Deliverables
8
3.0 Background and Rationale
9
4.0 Aims and Objectives
11
5.0 Initial Research & Literature Review
12
6.0 Project Methodology and Design
6.1 Project Methodology
18
6.2 XMap
19
6.3 XSim
23
6.3.1 “HALO” algorithm
26
6.3.2 The Directional Orientation Algorithm (DOA)
28
6.4 XNav
30
6.4.1 XNav Algorithm
31
6.4.1.1 Calculation Controller Algorithm
31
6.4.1.2 “HALO2” Algorithm
34
7.0 Results and Findings
41
7.1 Navigation inside a building structure
42
7.2 Navigation inside a Maze
46
7.3 Navigation in an outdoor environment
51
7.4 Real world testing of the XNav navigation system
55
8.0 Discussion and Analysis
8.1 Navigation inside a building structure
58
8.2 Navigation inside a Maze
59
8.3 Navigation in an outdoor environment
60
8.4 Real world test results
61
8.5 Limitations of the XNav system
61
9.0 Conclusion
64
10.0 Recommendations and future work
66
11.0 Bibliography
68
Appendix A Detailed time plan
70
Appendix B Algorithm source code
75
Appendix C Complete Sample XMap
80
5
Title : XNav Indoor Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
List of figures
Explanation
Page
Fig 2.1 Gantt chart 8
Fig 6.2.1 Map components tool box 19
Fig 6.2.2 Map component Attributes 19
Fig 6.2.3 Map component Attributes Window 20
Fig 6.2.4 Complete Sample XMap 21
Fig 6.3.1 XSim simulation tool box 23
Fig 6.3.2 No signal view 23
Fig 6.3.3 XSim functionality 24
Fig 6.3.4 Plotted path simulation coordinates 24
Fig 6.3.5 XSim plotted path 25
Fig 6.3.6 Manual simulation 25
Fig 6.3.1.1 HALO calculation example 26
Fig 6.3.1.2 HALO coordinate calculation 27
Fig 6.3.7 complete simulation arena 29
Fig 6.4.1 XNav client display 30
Fig 6.4.1.2.1 HALO2 center point calculation 34
Fig 6.4.1.1 XNav location calculation with two inputs 36
Fig 6.4.1.2 XNav location alculation with three inputs 37
Fig 6.4.1.3 XNav location calculation with x number of inputs 38
Fig 7.1.1 Ground floor of an assumed lecture center 42
Fig 7.1.2 The complete XMap of the indoor building environment 42
Fig 7.2.1 blueprint of the Maze 46
Fig 7.2.2 XMap Maze 1 (The RFID tags are spread along the edges) 46
Fig 7.2.3 XMap Maze 2 (The RFID tags are positioned at the junctions) 47
Fig 7.2.4 XMap Maze 5 (The RFID tags are positioned at the junctions, edge
ends and in between etc…)
47
Fig 7.3.1 Lamp posts and pillars available on walkways at Brunel University
(Ref.www.panoromio.com)
51
Fig 7.3.2 Aerial photo of Brunel University obtained using Google Earth
(www.googleearth.com)
51
Fig 7.3.3
XMap of Brunel University
5
2
Fig 7.4.1 proposed RFID reader 55
Fig 7.4.2 proposed RFID tags 56
Fig 7.4.5 Topology of the XNav real world test scenario 56
Fig 8.1.1 statistics of the indoor navigation scenario 58
Fig 8.2.1 statistics of the Maze navigation scenario 59
Fig 8.3.
1
statistics of the outdoor navigation scenario
60
Fig 8.5.1 Multi-path effect 62
Fig 8.5.2 HALO algorithm and the actual RFID range 63
6
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
1. Introduction
In the past man circum navigated the globe using the stars, trees, markers, special waypoints and natural
animal instinct. Today too we look to the heavens for guidance as we wait for GPS (Global Positioning
System) satellites to communicate with our handheld electronic maps. Through technological evolution,
which has outrun Darwinian evolution, man can now pinpoint his location on a map to an accuracy of a
few centimeters.
The proposed XNav Navigation System takes the concept of electronic navigation one step further. Today
the US military has ultimate control over GPS and utilizes its full power. Even though Projects such as
GALLELEO and techniques such as SISNeT and DGPS have tried to break the monopoly of the US
military by increasing the accuracy of the GPS signal, the rest of the world still uses GPS with an
accuracy of 3 meters. Although GPS can get us to the Air-Port over the winding motorways, we still get
lost in the vast labyrinth of its terminals because at present GPS cannot provide us with accurate
guidance inside buildings and structures. XNav is a system which proposes the link or the smooth
transition between the outside world and the indoors through the combination of different techniques for
location identification.
GPS, in a nutshell, is a technology which trilaterates the location of a GPS transceiver and transmits the
x,y,z coordinates of that location. By cross referencing the coordinates on a GIS (Geographic Information
Survey) map we are able to locate our position with an accuracy of 3 meters. Since GPS at the moment is
not overly helpful indoors, alternative means of identification of coordinates should be adopted for
navigation. As most modern buildings are now invisibly meshed with wireless networks, each building will
have a unique set of WiFi (Wireless Fidelity IEE 802.11) access point (AP) IDs and some rooms and
offices in the building will have their own unique AP IDs. In addition to the AP IDs XNav concentrates on
the use of RFID (Radio Frequency Identifiers), an inexpensive technology which transmits a unique
identifier over a limited radius, as a technique of marking each and every room and office in a building so
that it can be digitally identified using its RFID through an RFID reader. Due to its compatibility with many
wireless technologies the system was names “XNav” to indicate an “X” number of technologies.
XNav will consist of three major modules. The first would be a mapping or mapmaking software XMap
which will superimpose a software map over an existing plan, blueprint of a building or structure. This will
allow the mapmaker to define a software map which will for example map all the offices on the first floor of
Tower C at Brunel University, Uxbridge, Middlesex, UK. The rooms, defined on the software map, will
have general attributes such as Room-No, Occupant’s Name, Picture, Post, Department etc… and also
some special attributes such as RFID, WiFi Access Point ID, GPS Signature etc… By defining all of these
attributes the map maker is able to create an intricate map of a building, structure or a collection of
structures. Each building, structure, room, staircase, lavatory etc… will have a unique identifier (s) to
digitally identify themselves.
The second module is the navigation software XNav which allows people to navigate through a building or
structure using a hand held device such as a PDA (Personal Data Assistant), mobile computer (tablet pc)
or smart phone. Once the software is installed on a handheld device, it will be able to download XMap
data files which would have all the necessary information for automatically re-generating a software map
of a building or a collection of buildings. For example a traveler can download the XMap file of Heathrow
airport while riding the bus. The navigation software will then render the map using the XMap file on the
fly and will provide the traveler with a means of navigating through the airport.
The PDA would have hardware modules to read RFID signatures, WiFi AP IDs or GPS Coordinates and
would escalate these readings to the software to be translated in to room numbers and areas on the map.
A software algorithm will use the RFID and WiFi signatures of a particular area to pinpoint the location of
the PDA on the software map at that particular moment. Once the initial bearing is identified the user can
search for a location on the digital map and start navigating towards it. The algorithm will constantly
calculate the position of the PDA, based on the identification signatures available and would provide a
visual (audible at a later stage) guide to the user on his/her progress. The directional orientation of the
person would also be determined by the algorithm by identifying the order in which location IDs are
acquired or detected.
The third module is XSim which is a simulation software custom created to simulate different scenarios for
maps made using XMap. XSim would provide the map maker with the ability to fine tune the map by
7
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
running different simulation scenarios on the map. The information from the XSim simulation can be
directly fed into the XNav software and the hardware specifications (e.g. RFID transmit radius) for the
tagging of the actual building can be determined before any investment has to be made. The XSim
software would allow the mapmaker to change variables and test different test cases without any live
runs.
The complete software suit XMap, XSim and XNav complement each other as they form a strong and
complete solution for indoor navigation, both at the service provider’s end and at the user’s end. Due to
the truncated timetable of this project, only the scenario of RFID would be tested thoroughly. The testing
process would consist of several test phases where simulation testing and live testing would be done on
the same test cases to obtain a numerical value for the accuracy of the system.
The concept of XNav was inspired by the difficulties commuters face in the modern day rat race. Time is
of the essence and people are less inclined to navigate using paper maps or sign boards. Also the
limitations of the existing GPS technologies can be rectified and the strengths complimented by a different
location based technology which can integrate with the existing navigation systems. Conceptually XNav
could provide very accurate location coordinates and could be used to enrich other concepts and
technologies such as autonomous mobile robotic algorithms, collision avoidance algorithms, navigation
algorithms for the visually impaired, museum guide tools, airport commuter guides etc… In essence if a
person needs to find the Mona Lisa or the Venus De Milo in “La Luvre” in Paris he/she just needs to
search for it on the handheld map and the XNav algorithm would guide him/her right to it.
The future of XNav would be to combine RFID, WiFi and GPS signatures together so that the accuracy of
GPS coordinates can be optimized by the correctional effect of the other supporting signatures. Through
this dissertation project I wish to prove the concept behind the XNav system by developing the XNav
algorithm which would calculate the location and the mapping software which would enable me to define
digital software maps for test purposes. Through the use of simulation and live testing I hope to determine
the accuracy to which the XNav algorithm can calculate location coordinates and also to identify the error
of calculation for future developments and tweaking of the algorithm.
8
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
2. Time Plan, Milestones & Deliverables
Fig 2.1 Gantt chart
Stage
Time Frame
Milestones
Deliverables
01
4 weeks
1. Gain an in depth knowledge about the
background of the project, the technologies
used and the applications of the end system
1. Feasibility report of the project acknowledged by
the supervisor
2. Dissertation Interim Report
02
6 weeks
1. Test software map
2.The initial documented XNav algorithm
1.Test software map complete with all the attributes
2. Initial XNav Software package for mobile devices
03
1 week
1. Set of test scenarios or test cases
2. Documented updated algorithm
1. New hardware components needed for testing
the system
2. Accuracy of the system derived from simulation
04
2 weeks
1. Catalog of attributes from the real building
and hardware
2. Accuracy value of the system in real-time
3. The final XNav algorithm
1. Catalog of attributes from the real building and
hardware
2. Documented amended algorithm
3. Final XNav algorithm
05
3
weeks
1. Portable XMap database architecture
2. XMap mapping software
1. Complete portable database with all the
functionalities
2. Initial test map re-built using XMap and the
portable database
06
3 weeks
1. Simulation test result set with XMap
2. Amended XMap software
1. Final functional version of XMap
07
2 weeks
1. XSim version which uses XMap for
dynamic simulation generation
2. Documented test results of the complete
suit XMap, XSim and XNav integration tests
1. Complete suit of XMap, XNav and XSim
2. The effect of the complete suit on the accuracy of
the system
08
2 weeks
1. Accuracy of the system
2. Draft copy of the dissertation
1. Accuracy of the system
2. Final dissertation
9
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
3. Background and Rationale
Modern navigation systems are mostly based on GPS or the Global Positioning System. These navigation
systems are mainly outdoor systems which are used by vehicles, ships, aircrafts etc… When used with
precision GIS (Geographic Information Survey) maps, GPS provides enough accuracy for vehicles to get
from point A to point B using the “best” (e.g. shortest) possible route.
When posed with the challenge of indoor navigation, modern GPS systems fail to operate for two
fundamental reasons.
Modern GPS available to the general public is not accurate enough
Modern GPS transceivers are weak in picking up GPS signals indoors
The accuracy of the GPS coordinate using only the C/A signal is about 15 meters. This is due to the
synchronization of the signal speed and the receiver’s internal clock accuracy. Through the use of the
much faster P(Y) code the accuracy can be increased to about 30 centimeters. Also techniques such as
Augmentation, A-GPS (Assisted GPS), D-GPS (Differential GPS), Precise Monitoring, Dual Frequency
Monitoring, CGPS (Carrier-Phase Enhancement), RKP (Relative Kinematic Positioning), GPS Time, GPS
Modernization, etc… The accuracy of GPS can be improved to a matter of centimeters. Even though
these are promising accuracy levels for indoor navigation, the limitation of reception within buildings, due
to buildings acting as Faraday’s cages, restricts the use of GPS navigation in an indoor environment. New
positioning initiatives such as GALLEO and new high accuracy GPS transceiver devices such as the
SuperSence GPS module from u-blox (http://www.u-blox.com/news/TIM-LH.html [06/06/07]) promise a
future where GPS can be efficiently and accurately adopted in indoor navigation but at present alternative
positioning solutions such as RFID have to be adopted in order to achieve this objective.
In order for co-ordinates to be used in navigation they should be cross-referenced against a map which
records the location of each point. For outdoor navigation GIS maps are used and are available as
industry standard modules. These maps are high precision maps which are made by National and
International organizations dedicated to mapping geographic terrain. Many a custom mapping software
are available for customizing GIS maps of a certain area or place. These provide map makers with the
functionality of adding additional information and attributes to an existing geographic map so that the map
becomes more intricate and provides more accuracy. For navigation within a building or an indoor
environment, similar maps should be used. Since an indoor environment can change periodically, a
mechanism should be available to easily map and re-map the changes inside the structure. Thus custom
mapmaking software is needed to create intricate maps of buildings complete with the RFID and WiFi
signatures which can be used in the navigation process.
The internal structure of a building can vary greatly. Each floor can have a different floor plan and
considering modern skyscrapers, the software map of the internal structure could be extremely
complicated. Procuring equipment such as RFID tags to cover each floor can be a complicated task and a
large investment. Some portions of the building may need RFID tags with a larger coverage radius where
as others could manage with the minimum. There are cost and functionality restrictions which have to be
sorted before actual tagging of the indoor environment. For this purpose a simulation method is needed
where the software map created can be used in simulations with different test cases. Through multiple
simulations the exact numbers, ranges, and positioning of the RFID tags can be identified before the
investment is made on actual hardware. This will result in better functional accuracy and reduction of cost
of the project.
Modern day SatNav systems or Satellite Navigation Systems use two key components.
The GPS transceiver
The map display unit
The GPS transceiver receives GPS co-ordinates from the satellites and feeds them into and algorithm
present inside the map display unit software. Depending on the accuracy of the algorithm, the position,
direction, heading and speed will be visually indicated on the display. In indoor navigation the same
concept is used with specific hardware, software and algorithms. The software map will be a
downloadable file which can be downloaded on to a PDA. This file will then render a map which would be
fed with the RFID signatures captured using a portable RFID reader. A custom algorithm will interpret the
10
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
RFID signature to provide a visual indication of the direction, heading and position of that particular device
and device bearer. The PDA would act as a map display unit in indoor navigation.
Thus in my opinion, a complete solution for indoor navigation cannot be developed without combining all
the above mentioned aspects. The accuracy of the navigation algorithm and the actual user experience
will largely depend on the synergy of the mapmaking module, simulation module and the navigation
display and algorithm. Therefore I propose the bespoke XNav indoor navigation system which is a
complete suit of maps, simulation and the navigation algorithms that can be used to create accurate XNav
environments for navigation.
11
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
4. Aims and Objectives
Aim
To develop a complete end-to-end solution for indoor navigation through the use of RFID, WiFi and GPS
by combining custom map making, custom simulation and custom navigation software where portable
databases containing necessary information for rendering a dynamic map of a particular building can be
downloaded over the internet into a portable handheld device which hosts the navigation software and the
navigation algorithm that can use the RFID, WiFi, GPS signatures of a building to navigate within the
limitation of an optimum accuracy for a particular radio technology.
Objectives
1. Development of a map making software which allows the map maker the flexibility of defining
general attributes of a building such as building name, rooms numbers, occupant’s name,
occupant’s image, position etc… but also special attributes such as RFID signature, WiFi Access
point ID, GPS signature etc… that would be recorded in a portable database which can be used
to re-generate the map through a navigation software.
2. Development of a navigation software which could download a portable database over the
internet, re-generate the map using the parameters stored in the database and facilitate
navigation guidance using a hand held device such as a PDA, hardware modules specific to a
particular radio technology and a special navigation algorithm.
3. Formulation of the navigation algorithm which would be embedded in the navigation software and
would use the unique identifier signatures used to mark internal structures of buildings to provide
a visual aid to the user on his or her bearing, orientation and suitable routes to fulfill the journey
from point A to point B using predefined criterion.
4. Development of a simulation software which would simulate navigation through buildings mapped
using the mapping software and enable testing of maps using different test cases and scenarios
to identify the ideal positioning of RFID tags on the XMap for maximum accuracy of the navigation
system and the hardware specifications for the tags, readers etc… prior to the ordering of
hardware equipment.
5. Determine the numerical value which would elaborate and identify the accuracy of the system
through the use of simulation and real world testing in order to conclude whether the accuracy is
sufficient for the system to be safely and reliably adopted by users in real world scenarios.
12
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
5. Initial Research & Literature Review
GPS
The Global Positioning System, more commonly known as GPS, is a satellite-based technology with sole
proprietorship of the United States Department of Defense (DOD). The official version of GPS is called
NAVSTAR, which abbreviates Navigation Signal Timing and Ranging Global Positioning System. Even
though GPS is presently used by millions of civilians world-wide, the system was designed and controlled
by the U.S military.
At present more then 24 GPS satellites (29 as of January 2007) are in medium Earth orbit, constantly
transmitting navigation signals. This complex satellite constellation is managed by the United States Air
Force 50
th
Space Wing with an annual maintenance budget of over US$400 million including the
replacement of obsolete satellites.
The first satellite was launched in 1978 and since then GPS has become an indispensable tool in
navigation, map-making, land surveying etc. In addition to the navigation information, GPS also provides
a precise time reference which is used in many applications including the scientific study of earthquakes
and the synchronization of telecommunication networks.
The GPS satellites are constantly used by thousands of simultaneous requests from GPS receivers. In
order for a receiver to calculate its position it needs distance readings from at least three satellites.
By measuring the time delay between transmission and reception of each radio signal, and since each
reply carries location information of the satellites, the receiver can compute its position using Trilateration
(a method similar to triangulation but only uses two or more reference points and the measured distance
between the subject and each point).
An additional satellite(s) is used to correct the receiver’s clock error due to the lack of accurate inbuilt
clocks in the receivers.
System Segmentation
Space Segment: The orbiting satellites or Space Vehicles (SVs) are called the space segment. 24 SVs
are distributed equally over 6 circular orbital planes.
Control Segment: There are five known GPS Master Control and Monitoring stations located around the
world. These are located strategically in Falcon Airforce Base (Colorado Springs), Hawaii, Ascension
Island, Diego Garcia and Kwajalein. The tracking information is concentrated at the Schriever Air Force
Base at Colorado Springs and the SVs are contacted regularly and updated with the correctional
information gathered from the ground antennas. The updates synchronize the internal clocks to within a
microsecond and uses ground monitoring information, space weather information and other various inputs
to achieve this accuracy.
User Segment: The GPS receiver is the user segment of the GPS system. In general, GPS receivers are
composed of an antenna, tuned to the frequencies transmitted by the satellites, receiver-processors, and
a highly-stable clock (often a crystal oscillator). They may also include a display for providing location and
speed information to the user. A receiver is often described by its number of channels: this signifies how
many satellites it can monitor simultaneously. Originally limited to four or five, this has progressively
increased over the years such that, as of 2006, receivers typically have between twelve and twenty
channels. The recievers can readily communicate with a PC, PDA, Mobile phone or Nav System which
would manipulate the GPS data to provide a suitable output to the user. In the case of a SATNAV system
the GPS data is superimposed over a GIS map to provide the heading of a vehicle
Limitations of GPS
The accuracy of the GPS coordinate using only the C/A signal is about 15 meters. This is due to the
synchronization of the signal speed and the receiver’s internal clock accuracy. Through the use of the
much faster P(Y) code the accuracy can be increased to about 30 centimeters.
Atmospheric effects: The speed of the GPS signal may change as it passes through the earth’s
13
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
atmosphere and the ionosphere and correcting these errors is key to improving the accuracy of the GPS
signal.
Multipath Effect: The signal can succumb to delay due to multipath effect, which is the signal bouncing
and reflecting off the surrounding terrain, canyon walls, hard ground, etc. Ephemeris and clock errors
Selective availability : Selective availability is an error introduced intentionally into the GPS by the US
government. This error can range from 0 100 meters and protects against missiles being guided to
precise targets
GPS jamming: GPS is vulnerable to jamming as any other radio navigation system. These jammers can
be built intentionally or can be encountered accidentally
Relativity: According to Einstein's Theory of relativity, because of their constant movement and height
relative to the Earth Centered Inertial reference frame the clocks on the satellites are affected by their
speed as well as their gravitational potential. Earth, at 10.22999999543 MHz instead of 10.23 MHz.
Techniques of improving accuracy
Augmentation: Augmentation methods basically improve accuracy of GPS reading using external
correction or supporting data.
Assisted GPS (A-GPS): A-GPS, is a technology that uses an assistance server to cut down the time
needed to determine a location using GPS.
Differential GPS (D-GPS): D-GPS uses a network of fixed ground based reference stations to broadcast
the difference between the positions indicated by the satellite systems and the known fixed positions.
Precise Monitoring: The accuracy of a calculation can also be improved through precise monitoring and
measuring of the existing GPS signals in additional or alternate ways.
Dual Frequency Monitoring: This is a system which can compare two or more frequency signals such as
the L1 frequency and L2 frequency. Since these are two different signals and get affected in different but
predictable ways the error can be calculated and identified. Carrier-Phase
Enhancement (CPGPS): A 2 to 3 meter (6 to 10ft) error occurs due to the pulse transition of the PRN not
being instantaneous. CPGPS uses the L1 as an additional clock signal to resole uncertainty.
Relative Kinematic Positioning (RKP): Using this method the range signal can be resolved to an accuracy
of less that 10cm (4inches). This is accomplished by resolving the number of cycles in which the signal is
transmitted and received.
GPS Time: Atomic clocks on the satellites are set to "GPS time" which is not corrected to the rotation of
the Earth, ignoring leap seconds and other corrections. To correct this error a new 16 bit field is being
added to the GPS navigation message that specifies the calendar year number exactly.
GPS Modernization: Additional advances in technology and new demands on the existing system led to
the effort to "modernize" the GPS system which achieved the original design goals. This is referred to it
as GPS III.
Applications and benefits of GPS
Military : Targeting of weapons and missiles, Troop navigation on battle fields
Navigation: Automobile SATNAV systems, Aircraft navigation systems, Boat and Ship navigation systems,
Heavy equipment (construction, mining etc.) navigation, Bicycle navigation systems, Hiking, climbing,
recreational navigation systems, Visually impaired guidance systems
Surveying and mapping: Positioning of survey markers, buildings, roads etc., GIS map creation and GPS
mapping, Geophysical and geological measurements and readings
Other: Precise time reference, Mobile Satellite Communications, Emergency and Location-based
services, Location-based games, Use of GPS fro aircraft passengers, GPS compass, GPS tracking,
Weather Prediction Improvements, Photograph annotation
14
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
SatNav
Satnav systems are mainly used in automotive navigation. A satnav translates the GPS coordinate
information into a location on a map built in to the unit. Using the road database, the unit can give
directions to other locations along roads also in its database.
Honda claims to be the first company which introduced satnav in their vehicles. This was an analog
system which didn’t use GPS and was introduced in 1990. Pioneer was the first company which
developed a GPS based system also in 1990. Magellan, a GPS navigation system manufacturer claims to
have developed the first GPS based vehicle navigation system in 1995.
Limitations of Satnav
Limitations of GPS: The limitations of GPS are escalated to the satnav system. The accuracy can play a
major part in the navigation and can some times misdirect the user.
Software limitations: The Satnav depends on the software which interprets the GPS coordinates and
calculates a location on the map. The programming of the algorithm could be faulty and could misdirect
the user.
Accuracy of the map: The accuracy of the location on the map depends on the accuracy of the map itself.
A small error in the coordinates of the map can contribute to a considerable miscalculation of location on
the stanav system.
Applications and benefits
Golf carts, POI systems (Point Of Interest systems to provide information on places like restaurants, ATM
machines, gas stations etc…), Automatic dispatch of taxi cabs, Vehicle security systems and beacons,
Speed trap avoidance devices
RFID
Radio Frequency Identification is a new technology which allows the storage and retrieval of data using
wireless radio technology. These RFID tags or transponders emit radio waves with unique signatures
which can be captured and cataloged against a known piece of information. In 1946 Léon Theremin
invented an espionage tool for the Soviet Union which retransmitted incident radio waves with audio
information. This device was a passive covert listening device and not an identification tag but has been
attributed as the first known device which used RFID. In recent years RFID has invaded every day life in
is being used in many applications and solutions over a spectrum of industries and businesses.
Segments of an RFID tag
Integrated circuit: The module which modulates and demodulates RF signals, stores the RFID signature
and other custom information in specialized modules.
Antenna: The antenna is used to transmit and receive RF signals
Chipless RFID: An immerging technology which allows for discrete identification tags that can be printed
directly onto a surface
RFID tag types
Active: Active RFID tags have their own internal power source. This powers the integrated circuits and
broadcast the signal to the reader. Active tags are much more reliable, have fewer errors, can maintain
session information with a reader, can transmit at higher power levels, can be effective in "RF challenged"
environments like water (including humans/cattle, which are mostly water), metal (shipping containers,
vehicles) and can transmit at longer distances (practical range of 100m and a battery life of up to 10
years) Specialized modules can be equipped with sensors such as temperature, humidity, shock/vibration,
15
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
light, radiation etc…
Passive: Passive tags do not require a power source to transmit information. It uses a specialized
antenna which can gather enough energy from incoming signal to power up the CMOS chip and transmit
information. These tags can contain other non volatile information stored in the EEPROM. The range of a
passive tag can range form 1 cm
(ISO 14443) to a few meters (Electronic Product Code (EPC) and
ISO 18000-6) depending on the radio frequency and the tag design.
Semi-passive: Semi-passive tags have their own power source but the battery is used just to power the
microchip and not broadcast a signal. The RF energy is reflected back to the reader like a passive tag.
Applications and benefits
Passport identification, transportation payments (e.g. Oyster in UK), product tracking in supply chain
management / logistics / inventory / manufacturing assembly lines, Vehicle access control, livestock
control and identification, library tracking, human implants etc…
Indoor navigation solutions, techniques and applications
In recent years RFID navigation has become a much debated topic. Research is being done in navigation
solutions for indoor environments for both sighted and blind pedestrians. One such project is the “Robot-
Assisted indoor navigation solution” [3] developed by Logan state university, Utah, USA. This project
focuses on the deployment of RFID tags in an indoor environment and using a mobile robot to guide the
visually impaired person through the environment. The research department of University of Florida USA
has also designed a navigation system for the blind which uses RFID tags buried under carpets and foot
paths and detected and deciphered using wearable RFID readers.[9][10] Another project is the indoor
navigation solution developed by the University of Jerusalem which uses RFID and infrared information
grids mounted on the ceiling and portable receiving units[11].
Drishti: “Drishti is a wireless pedestrian navigation system. It integrates several technologies including
wearable computers, voice recognition and synthesis, wireless networks, Geographic Information System
(GIS) and Global positioning system (GPS)” [12] This was developed by the University of Florida.
Wheelesley: “This research project is aimed towards developed a usable, low-cost assistive robotic
wheelchair system for disabled people. In our initial work towards this goal, we have developed a
graphical user interface which allows the user to communicate with the wheelchair's on-board computer.
The robotic wheelchair must work with the user to accomplish the user's goals, accepting input as the
task progresses, while preventing damage to the user and the robot.” [17][18] This is a project by
Wellesley College which uses a UI for precision navigation.
OtoNav: This research project done by the University of Athens, Greece [24] concentrates on a three fold
solution for indoor navigation. Navigation Service (Nav): “It is the main interface between the user and the
system. It receives users’ requests for navigation and responds with the requested path (if any), in a form
tailored to each user’s special characteristics (perceptual, physical and other preferences)”. Geometric
Path Computation Service (GEO): “This service is responsible for the computation of all the geometrical
paths from a user’s current location to a specified destination (Point of Interest, POI)”. Semantic Path
Selection Service (SEM): This service provides the main functionality of our system and is responsible
for the selection of the best traversable navigation path among those established by the GEO service”.
“We incorporate RFID technology into a navigation system to improve the accuracy. The skeleton of the
idea is as follows: install RFID tags on roads in a certain way, store very accurate location information
along with other necessary information in the tags, add an RFID reader module to the navigation system,
and use this new location information along with GPS and a gyroscope to produce highly accurate
location information. With this scheme, the accuracy of positioning can be dramatically improved,
especially in tunnels and in downtown areas. Preliminary results show that this idea is feasible”
is the
methodology adopted by a research group of Samsung Korea to implement RFID based location
identification in an outdoor environment.[7]
16
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Mapping Software
Hybrid Indoor Navigation System: is a system designed by the
University of Saarbr¨ucken, Germany which
uses a three dimensional map of an indoor environment to guide a person through the building. [28]
Smart Classroom: “The Smart Classrooms are spread all over Clarion University’s campus and are
expanding with different configurations. A simple list of information is no more adequate to handle the
wealth of data and its varied settings. The current project develops of a GIS that visually and digitally
represent the campus as a set of smart maps for buildings floor plans. Digital maps will be created by
either the digitization of paper drawings or converted from exiting CAD files. Furthermore, all tabular
information, such as specifications, locations and quantities, will be imported into the GIS from a simple
Microsoft Access database.” [7]. This software developed by Clarion University, USA maps the features of
a classroom on to a software map for processing.
17
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
18
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
6. Project Methodology and Design
6.1 Project Methodology
Development, Testing and Analyzing
XMap mapping software development
Build XSim simulation module which would work on the XMaps created by XMap
Develop the XNav algorithm
Develop the XNav navigation software platform for portable devices
Test the accuracy of the XNav algorithm using the XSim simulation module
Tweak the XNav algorithm for further accuracy
Build an actual test platform in the University using RFID tags and XMap
Run live tests of XNav on the test bed
Run simultaneous simulation tests on the test bed
Compare results from both test and fine tune XNav algorithm further
Determine the accuracy of the system within an indoor environment
Determine whether the XNav algorithm is accurate enough to be used in an indoor
environment without compromising the safety or the confidence of the user
General
The project will be divided into steps as illustrated in the Gantt chart
Each step will be monitored and supervised by the project supervisor
Weekly progress meetings will be held with the supervisor to discuss the current state of the
project
At the end of each step a review meeting will be held to evaluate the progress of the project
and any adjustments that need to be made
Initially the project will be based on a test model
Simulation tests will take place before developing the specification for the hardware needed
After simulation testing real-time testing will take place under the supervision of the project
supervisor
After live testing and fine tuning of the algorithm the results will be documented
Then the project will be generalized to suit a variety of different scenarios
As the final stage of the project the dissertation will be compiled
Tools:
Microsoft Visual Studio.Net 2005 professional version will be used to manage source code /
versioning / releases / changes and testing of the whole project
Environmental Resources
Software
Development Environment – Microsoft Visual Studio .NET 2005 professional
Main OS – Microsoft Windows XP Professional
Portable OS – Microsoft Windows Mobile 2005
Hardware
RFID tags - Range to be specified after simulation testing
RFID tag reader - Plug and Play device for PDAs
Development computer - Server class to support simultaneous simulation
Mobile device - PDA with MS Windows Mobile 2005
19
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
6.2 XMap
XMap is the mapmaking software component which superimposes a software map on a blueprint of a
building’s internal structure.
Functionality
1. New project
a. Select project folder
A folder is selected as the project folder and given a unique project name. (e.g.
Brunel_University_Lecture_Center_Second_Floor)
b. Load map image
The load map feature loads an image file of the internal structure onto the XMap design
area.
c. Load map components
The map components box is a tool strip which contains several room
types and building components to create the software map over the
blueprint of the map. These components are marked with different
symbols identifying their purpose (e.g. Office,
Lecture Room, Fire Escape etc…). The mapmaker can drag
and drop a component onto the XMap design area, move it to the
appropriate position and resize it to fit over the relevant area on the
blueprint. The images help the mapmaker identify a map component
on the map (e.g a lecture room) much more easily. When the map is
saved as an XMap, the images are replaced with the description
attributes.
Fig 6.2.1 Map components tool box
The map component “Attributes” box is
accessed by right clickingon a particular
map component. Each map component will
have 5 attributes.
Fig 6.2.2 Map component Attributes
20
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Fig 6.2.3 Map component Attributes Window
Attributes
1. Component ID The specific
identification name given to a
room, office etc… (e.g. Prof.
Balachandran)
2. Description The description of
the map component (e.g. Office,
WiFi research lab where all the
WiFi related experiments are
conucted etc…)
3. RFID The RFID signature of the
tag which will be used to identify
this component in the real world
4. WiFi ID – The WiFi Access point
signature which would identify a
particular map component in the
real world (Optional)
5. GPS The GPS X and Y
coordinates of a given component
in the real world. (Optional)
2. Open project
Open project allows the mapmaker to open an existing project and make modifications to it such
as add new components, change attributes, resize, relocate components etc… This helps in
creating large XMaps due to the mapmaker being able to save an incomplete map and continuing
on it over a period of time. Also a map maker can modify an existing map to identify construction
work, closing of specific areas, health risks etc… Once the changes have been made to the
XMap, the XNav software, in theory, can look for any new updates and download the very latest
XMap onto the mobile computer.
3. Save – Saves the XMap on an ongoing basis
4. Save As – Saves the XMap under a different user defined name in a user defined folder.
The following figure (Fig 6.2.4) is a complete XMap of a hypothetical ground floor of a University building.
When the mouse hovers over any map component a tool tip is displayed giving all the attributes assigned
to that particular room. This allows the mapmaker to easily check the attributes attached to each map
component.
21
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Fig 6.2.4 Complete Sample XMap
5. XMap file
The XMap file is a text based file which is used to encapsulate all the information needed to
regenerate an XMap created by the mapmaker. When the mapmaker saves an XMap, an XMap
file is automatically created with the “.xmap” extension in the project folder. This file is common to
XMap, XSim and XNav components and is used to regenerate or render the software map on the
fly.
22
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
XMap Structure
Following is an abstract from the .xmap file used in the example shown in
Please refer to Appendix C for the complete .xmap.
C:\Documents and Settings\Dell\Desktop\C
Drive\BrunelAssignments\Dissertation\Xmap1\TestFloorPlan.JPGLocation of
the map / blueprint of the building
Name:0 Identification tag of the blueprint image file on the xmap
height:46 Height of the image on design pane
width:100 Width of the image on design pane
x:58 X position on the design pane
y:15 Y position on the design pane
tag:Prof. Balachandran;Office;88-1-44;324224fsdfdsf;34;43;Complete tag
information to be displayed to the mapmaker upon regeneration of the map. This is a comma
separated list of values
txt:Prof. Balachandran Component ID
ImageEnum:Prof. Balachandran Component Image ID
Name:1Component ID Number
height:44 Height on design pane
width:96 Width on design pane
x:521 X position on the design pane
y:79 Y position on the design pane
tag:Dr. Powell;Office;88-1-4;dasdasd34343;43;43;
txt:Dr. Powell
ImageEnum:Dr. Powell
Name:2
height:46
width:96
x:636
y:285
23
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
6.3 XSim
XSim is the simulation module of the XNav navigation system. XSim is designed to simulate a person
walking through an XNav enabled environment using the XNav navigation system and a RFID reader.
The XSim module incorporates three main algorithms which simulate movement, directional orientation
and the detection of RFID signatures in the building.
XSim Components and Functionality
1. XNav simulation arena
The simulation arena is similar to the XMap design area. This is the main window which would
host the simulation animations.
2. Load XMap
The “Load XMap” feature is designed to load any pre designed XMap onto the simulation arena.
This will load all the parameters of the XMap such as all the buildings, building attributes etc…
The complete XMap would be rendered in the arena using the saved XMap file.
3. Simulation (Tools)
a. XSim tools
Fig 6.3.1 XSim simulation tool box
“XSim Tools” is a control panel which facilitates and controls
the different parameters of the simulation.
The Topmost box indicates the wireless radio signatures of
the structure closest to the XNav user. The text area
underneath displays all the other RFID signals picked up
simultaneously. The XSim simulator is built to simulate the
basic functionality of an RFID reader where it reads the space
around it at given intervals to pick up available RFID signals.
A filtering software in the RFID reader normally filters out
redundant information but to study the functionality of the
system and the behavior of the RFID tags, the XSim system
does not filter redundant information. (i.e the same RFID
signature maybe repeated more than once.) and if no signal is
detected it will indicate that no signal was detected.
Fig 6.3.2 No signal view
XSim reads the RFID information around the current location
of the simulated RFID reader every 50 milliseconds (0.05
seconds) and displays the detected RFID information on the
XSim control panel. This information is then fed directly into
the XNav algorithm as input from a real live RFID reader
gathering RFID information in an XNav enabled environment.
24
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Fig 6.3.3 XSim functionality
“Clear” button
The clear button clears all the previous gathered RFID
information in the display boxes. This allows the
simulation engineer to have a fresh look at the
information gathered and the sequence in which the
information is acquired.
“Start” button
The start button starts the simulation
“Pause” button
The pause button allows the simulation to be temporarily
paused to analyze the information gathered in a
particular area. It also allows the simulation engineer to
change simulation parameters such as RFID tag range
or simulation speed, without loosing any information.
“Stop” button
The stop button stops the simulation cycle
“Tag Range(Radius)” parameter
The tag range or the radius parameter sets the range of
the RFID tags used in the XNav environment. (e.g 25 =
25 meter radius and is denoted in the simulation using
25 points or pixels. Scale 1m = 1pixel)
“Simulation Speed”
The simulation speed setting allows the simulation
engineer to slow down the simulation or to speed it up.
This in-turn is helpful to identify the exact RFID readings
acquired when the simulated RFID reader passes
through a certain area.
b. Plotted path simulation
Fig 6.3.4 Plotted path simulation
coordinates
The “Plot Path” component allows the simulation
engineer to plot different paths through the XNav
enabled environment inside the simulation arena.
The start button is clicked to start the plot and the
path is drawn on the arena buy right clicking the
mouse and dragging it over the path which needs
to be simulated. The save button save the plot for
simulation and the cancel button clears the path.
The Cartesian co-ordinates of each point on the
path is displayed in the “Co-ordinates” box for
reference and the clear button clears the box for
fresh co-ordinates.
Fig 6.3.5 illustrates a plotting of a path on the XSim
arena.
25
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Fig 6.3.5 XSim plotted path
c. Manual simulation
Fig 6.3.6 Manual simulation
Manual simulation is a method used to simulate a
path without plotting a path. Manual simulation is
activated by ticking the “Manual” tick on the
simulation control panel. When manual simulation is
activated, the simulation engineer can move the
mouse pointer over the XSim arena and the location
of the mouse pointer will be considered as the
present location of the RFID reader in the simulation
arena. This method helps identify potential faults in
the XMap design by running and re-running the
same path in the arena and also accessing difficult
locations in different ways. Using this method more
complex scenarios can be tested and the XMap can
be tweaked for optimum performance.
26
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
6.3.1 “HALO” algorithm
The “HALO” algorithm is a simple algorithm which calculates the active range of the RFID transmission
around a RFID tag in the XSim arena. The range of the RFID tag is taken from the value set in the XSim
tools control panel (Fig 6.3.3) Tag Range (Radius) value and a HALO is calculated around a building
indicating the range.
Two assumptions are made in the calculation of the HALO
1. The active range of the RFID tag can be denoted by a square (box) rather than a circle
2. The RFID tag is always placed in the center of a building component. (e.g. center of an office)
Fig 6.3.1.1 is the RFID HALO calculated around Room No LC-110.
Fig 6.3.1.1 HALO calculation example
Algorithm
Variables
Variable Name Type Description
inRange
Boolean
Check whether the building component is in range of the
simulated RFID reader
Halo Integer RFID tag range set for the simulation
Height Integer Height of the building component on the software map which
hosts the RFID signature. (This is a dimention of the software
component which was used to repesent the actual building
component. It is not a dimention of the actual building
component in the real world)
Width Integer Width of the building component on the software map which
hosts the RFID signature. (This is a dimention of the software
component which was used to repesent the actual building
component. It is not a dimention of the actual building
component in the real world)
btnX Integer Top lefthand corner X co-ordinate of the building component
on the software map which hosts the RFID signature. (This is
a dimention of the software component which was used to
repesent the actual building component. It is not a dimention
of the actual building component in the real world)
btnY Integer Top lefthand corner Y co-ordinate of the building component
on the software map which hosts the RFID signature. (This is
a dimention of the software component which was used to
repesent the actual building component. It is not a dimention
of the actual building component in the real world)
xLeftTop Integer Top lefthand corner X co-ordinate of the HALO
xRightTop Integer Top righthand corner X co-ordinate of the HALO
xLeftBottom Integer Bottom lefthand corner X co-ordinate of the HALO
xRightBottom Integer Bottom righthand corner X co-ordinate of the HALO
yLeftTop Integer Top lefthand corner Y co-ordinate of the HALO
yRightTop Integer Top righthand corner Y co-ordinate of the HALO
27
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
yLeftBottom Integer Bottom lefthand corner Y co-ordinate of the HALO
yRightBottom Integer Bottom righthand corner X co-ordinate of the HALO
Fig 6.3.1.2 HALO coordinate calculation
Steps
Start
i. Halo = RFID Tag Range from XSim tools
ii. Height = Software map component.Height
iii. Width = Software map component.Height
iv. btnX = Software map component.Location.x
v. btnY = Software map component.Location.Y
vi. xLeftTop = btnX - Halo
vii. xRightTop = btnX + Width + Halo
viii. xLeftBottom = btnX - Halo
ix. xRightBottom = btnX + Width + Halo
x. yLeftTop = btnY - Halo
xi. yRightTop = btnY - Halo
xii. yLeftBottom = btnY + Height + Halo
xiii. yRightBottom = btnY + Height + Halo
xiv. If X > xLeftTop And X < xRightTop Then
xv. If Y > yLeftTop And Y < yLeftBottom Then
xvi. inRange = True
xvii. Else
xviii. inRange = False
xix. End If
xx. End If
xxi. Return inRange
End
Please refer Appendix B for the programming code
If inRange is true then XSim component passes the RFID signature of that map component onto the
XNavv module. If false then it calculates the HALO for the next component. The only parameter passed
into the XNav componet is the RFID signature. This replicates the passing of a RFID signature using a
RFID reader. The XNav algorithm calculates the current location using only the RFID signature and no
other information.
28
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
6.3.2 The Directional Orientation Algorithm (DOA)
The Directional Orientation Algorithm is used to indicate the direction in which the RFID reader is moving.
The same algorithm is used both in the XSim component and the XNav component to identify the
directional orientation. The algorithm records the sequence of the x and y Cartesian co-ordinates on the
XMap as the simulated RFID reader pass over them. This information is then analyzed against the XMap
to determine the directional heading of the simulated RFID reader. After calculation of the direction the
algorithm indicates the heading on the XSim arena through the use of four images which indicate North,
South, East and West.
The same algorithm is used in the XNav system to calculate the directional orientation of a person
navigating through an XNav enabled environment.
Limitation - At least two co-ordinates need to be calculated before the directional orientation can be
calculated. (i.e the direction will be indicated as soon as the user starts moving through the XNav
environment. If stationary, the direction indicated on the system will be inaccurate)
Algorithm
Variables
Variable Name Type Description
PointsX
Integer
Current Cartesian X co-ordinate of the RFID reader on the
XSim arena or the XNav system (latest entry in the co-
ordinate list)
PointsY
Integer
Current Cartesian Y co-ordinate of the RFID reader on the
XSim arena or the XNav system (latest entry in the co-
ordinate list)
“0” Image Index
Image index of the “NORTH” arrow image
“1” Image Index
Image index of the “SOUTH” arrow image
“2” Image Index Image index of the “EAST” arrow image
“3” Image Index Image index of the “WEST” arrow image
Steps
Start
i. If PointsX(“present”) > PointsX(“previous”) Then
ii. ImageIndex = 3 ‘--------------------------------------------------------WEST
iii. ElseIf PointsX(“present”) < PointsX(“previous”) Then
ImageIndex = 2 ‘--------------------------------------------------------EAST
iv. End If
v. If PointsY(“present”) > PointsY(“previous”) Then
vi. ImageIndex = 1 ‘--------------------------------------------------------SOUTH
vii. ElseIf PointsY(“present”) < PointsY(“previous”) Then
viii. ImageIndex = 0 ‘--------------------------------------------------------NORTH
ix. End If
End
Please refer Appendix B for the programming code
29
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Simulation
XSim simulation setup
1. Load XMap onto XSim simulation arena
2. If using plotted path simulation, use the plot path tool to plot a path on the arena
3. Save the plot
4. Open XSim Tools control panel
5. Set the RFID Tag Range
6. Start simulation
7. If using manual simulation, tick the “Manual” option and move mouse pointer over the required
path
Fig 6.3.7 complete simulation arena
30
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
6.4 XNav
XNav is the core of the systems and is the navigation algorithm which calculates the position of the RFID
reader in an XNav enabled environment. The XNav algorithm is complimented by the “HALO Algorithm”
(Ref.6.3.1) and the “Directional Orientation Algorithm” (Ref.6.3.2) mentioned in the XSim simulation
module. XNav Client is the software which hosts the XNav algorithm and the more general functionalities.
XNav Client
XNav Client is the platform which allows a mobile computer (RFID enabled) bearing person to navigate
within an indoor environment.
Functionality
1. Download Map
Download Map feature allows a user to download an XMap file over the internet. Once the
mobile computer is connected to the internet using WiFi, GPRS or other means of internet, the
user can navigate to an XMap server and download the appropriate XMap file for a particular
venue. (e.g the XMap for Brunel University) else the XMap can be downloaded from a website of
a particular enue (e.g www.brunel.ac.uk/Xmap) Although this functionality is built into the XNav
client application, no XMap server has been defined for download of XMaps within the scope of
this project. Once an XMap server is defined or an XMap is hosted online, theoretically, this
feature would function as mentioned above.
2. Load Map
Load XMap feature literally loads a saved XMap (either from downloading or other means) on to
the XNav client arena once the user has selected the appropriate XMap for that particular venue.
This XMap is then used to visually indicate the present location of the RFID reader in the XNav
enabled environment.
The XNav Client software application receives RFID tag information directly from the RFID reader or the
XSim simulated RFID reader. This RFID tag information is then passed on to the XNav algorithm which is
used to pinpoint the location of the RFID reader in the XNav enabled environment on the XNav Client
software application.
Fig 6.4.1 XNav client display
31
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
6.4.1 XNav Algorithm
The XNav algorithm is a simple algorithm which calculates the position of the RFID reader in the XNav
enabled environment. XNav is complimented by several other smaller algorithms which are used to
calculate values for different variables for the calculation of position, directional orientation, and the
Cartesian coordinates on the XMap where the location indicator should be placed.
Algorithm Inputs : RFID signatures as a String array
Algorithm Outputs :
1. (x,y) Cartesian coordinates of the location indicator to be placed on the
XMap in the XNav arena
2. Directional orientation of the location indicator to be placed on the XMap
in the XNav arena
6.4.1.1 Calculation Controller Algorithm
This algorithm is the controller algorithm which gets the RFID information from the RFID reader as input.
This algorithm is responsible for the following tasks
I. Stores the RFID information in a stack
II. Stop the RFID reader when the information processing is being done
III. Cross-references the information against the XMap
IV. Process and identify the XMap component corresponding to a particular RFID tag
V. Store the component ID in a new stack
VI. Send the component ID to HALO2 algorithm to calculate Cartesian coordinates of HALO
VII. Send the results from HALO2 to XNav algorithm to calculate the Cartesian coordinates of the
location indicator on the XMap
VIII. Restart the RFID reader for new input
Algorithm
Variables
Variable Name Type Description
sRFID
String()
RFID signatures as a string array passed into XNav
from the RFID reader
sWiFiId
Optional String()
Optional WiFi signatures as a string array which can be
passed into XNav from a WiFi reader
sGPSX
Optional String()
Optional GPSx signatures as a string array which can
be passed into XNav from a GPS reciever
sGPSY
Optional String()
Optional GPSy signatures as a string array which can
be passed into XNav from a GPS reciever
cycleComplete
Boolean
Global flag set to stop the input of RFID information
from the RFID reader while the algorithm is processing
the previous stack of information. This elliminates
infinte loops and reduces inaacuracies in calculations.
It also make the calculations much faster. Since RFID
information is received approximately 10 times a
second, the loss of information is estimated to be a
minimum
NoSignal
Boolean
Indicates whether there are any RFID signatures
available in a particular area
arrBtnDetected
Button()
The XMap componet IDs which are identified by cross
referencing the RFID information with the XMap
32
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
roomMidX
Integer()
The detected RFID signatures are crossreferenced
against the XMap information. If there is a match then
the XMap compoent ID is passed into a different
version of the HALO algorithm called HALO2. This
inturn calculates the cartesian coordinates of the
component HALO on the XMap. The center x
coordinate of the component is recorded in this array
roomMidY
Integer()
The detected RFID signatures are crossreferenced
against the XMap information. If there is a match then
the XMap compoent ID is passed into a different
version of the HALO algorithm called HALO2. This
inturn calculates the cartesian coordinates of the
component HALO on the XMap. The center y
coordinate of the component is recorded in this array
detectedIDsIndex
Integer
This is a pointer which points to the present calculation
record in the arrBtnDetected array (Stack)
Name
String
Name of the detected XMap component
RFID
String
RFID of the detected XMap component
WiFi
String
WiFi ID of the detected XMap component
gpsX
String
GPSx of the detected XMap component
gpsY
String
GPSy of the detected XMap component
arrAtts
String()
All the attributes of an XMap component are are
compiled into a comma seperated values (csv) list
when saving. At run time this list is partitioned into the
separate attributes and temporarely places in this
arrary for processing
xx
String
A temporary variable used to store the attribute
information of an XMap component for processing
Steps
Inputs:
sRFID() As String
Optional sWiFiId As String = ""
Optional sGPSX As String = ""
Optional sGPSY As String = ""
I. If cycleComplete = True Then
II. NoSignal = True
III. Array.Clear(detectedIDsX, 0, 100)
IV. Array.Clear(detectedIDsY, 0, 100)
V. detectedIDsIndex = 0
VI. For Each btn As Button In arrBtn
VII. If Not btn Is Nothing Then
VIII. NoSignal = False
IX. Name = String.Empty
X. RFID = String.Empty
XI. WiFi = String.Empty
XII. gpsX = String.Empty
XIII. gpsY = String.Empty
XIV. If Not btn.Tag = String.Empty Then
XV. xx = btn.Attributes
XVI. arrAtts = xx.Split(";".ToCharArray())
33
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
XVII. Name = arrAtts(0)
XVIII. RFID = arrAtts(2)
XIX. WiFi = arrAtts(3)
XX. gpsX = arrAtts(4)
XXI. gpsY = arrAtts(5)
XXII. End If
XXIII. For i = 0 To sRFID.Length - 1
XXIV. If Not sRFID(i) Is Nothing Then
XXV. If sRFID(i).Trim = RFID.Trim Then
XXVI. roomMidX(detectedIDsIndex) = HALO2(btn, "x"c)
XXVII. roomMidY(detectedIDsIndex) = HALO2(btn, "y"c)
XXVIII. arrBtnDetected(detectedIDsIndex) = btn
XXIX. detectedIDsIndex = detectedIDsIndex + 1
XXX. Exit For
XXXI. End If
XXXII. End If
XXXIII. Next
XXXIV. End If
XXXV. Next
XXXVI. If detectedIDsIndex > 0 Then
XXXVII. XNav(roomMidX, roomMidY, arrBtnDetected, detectedIDsIndex)
XXXVIII. End If
XXXIX. End If
XL. End
Please refer Appendix B for the programming code
34
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
6.4.1.2 “HALO2” Algorithm
The HALO2 Algorithm is similar to the HALO algorithm mentioned in the XSim module but less complex. It
calculates the center point coordinate (xMid,yMid) of the XMap component using the information saved in
the XMap.
Algorithm Inputs :
1. XMap component ID
2. Which coordinate to calculate (x or y)
Algorithm outputs :
1. X coordinate of the center point xMid
2. Y coordinate of the center point yMid
The center point is calculated by
1. Top left hand corner X coordinate + (Component.Width / 2)
2. Top left hand corner Y coordinate + (Component.Height / 2)
Fig 6.4.1.2.1 HALO2 center point calculation
Algorithm
Variables
Variable Name Type Description
btn
Button
XMap component ID passed into the algorithm from
the Controller Algorithm
xOry
Char
Flag which indicates whether the algorithm is
calculating the x coordinate or the y coordinate of the
center point (“x” = X coordinate / “y” = Y coordinate)
Height
Integer
Height of the XMap component
Width
Integer
Width of the XMap component
btnX
Integer
Top left hand corner X coordinate of the XMap
component
btnY
Integer
Top left hand corner Y coordinate of the XMap
component
xMid
Integer
Center point X coordinate
yMid
Integer
Center point Y coordinate
35
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Steps
Inputs:
btn As Button
xOry As Char
I. Height = btn.Height
II. Width = btn.Width
III. btnX = btn.Location.X
IV. btnY = btn.Location.Y
V. If xOry = "x"c Then
VI. xMid = btnX + (Width / 2)
VII. Return xMid
VIII. Else
IX. yMid = btnY + (Height / 2)
X. Return yMid
XI. End If
XII. End
Please refer Appendix B for the programming code
36
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
XNav Algorithm contd…
The XNav algorithm calculates the Most probable position of the RFID reader in the XNav enabled
environment. It uses the center points calculated by the HALO2 algorithm to calculate lines joinnig the
centers of the XMap components.
Working Rule
Atleast two different RFID signatures should be detected for the algorithm to calculate the location. If no
RFID signatures or only one RFID signature is detected the algorithm will not execute.
Calculation steps
I. Check whether more than one RFID signature is present
II. Calculate the lines joining the centers of the components
a. [(X1,Y1) + (X2,Y2)] / 2
III. If only two RFID signatures are present
a. Calculate the center of the line joining the centers
b. Place the location indicator using the (x,y) coordinates of the most probable position
Fig 6.4.1.1 XNav location calculation with two inputs
IV. If only three RFID signatures are present
a. Calculate the lines joining the centers
b. Calculate the center points of the lines
c. If the center point is inside the component, it is disregarded
d. Place the location indicator at the first center point available
Working Rule
The distance between the two center points is assumed to be very small. It is also assumed that
the approximate position indicated would be accurate enough for the user to identify his/her
bearing in the XNav enabled environment
37
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Fig 6.4.1.2 XNav location alculation with three inputs
V. If more than three RFID signaturs are present
a. Calculate the lines joining the centers
b. Calculate the intersection points of the lines
c. If the intersection points are inside the components, they are disreegarded
d. The intersection point common to the maxmimu number of lines is identified as the most
probable location and the location ndicator is placed at that point
e. If more than one most probable points exist, the location indicator is placed on the first
point
Working Rule
The distance between the most probable points is assumed to be very small. It is also assumed
that the approximate position indicated would be accurate enough for the user to identify his/her
bearing in the XNav enabled environment
38
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Fig 6.4.1.3 XNav location calculation with x number of inputs
VI. The Directional Orientation Algorithm (DOA) (Ref.6.3.2) is used to indicate the direction of the
heading
Algorithm
Variables
Variable Name Type Description
sRoomMIdX
Integer()
Array of component center point x coordinates calculated by the
HALO2 algorithm
sRoomMIdY
Integer()
Array of component center point y coordinates calculated by the
HALO2 algorithm
arrBtnDetected
Button()
Array of detected component IDs
detectedIDsIndex
Integer
Pointer to the array of component IDs (Stack)
xReaderMid
Integer Calculated x coordinate of the location indicator which corresponds to
the location of the actula reader in the XNav enabled environment
yReaderMid
Integer
Calculated y coordinate of the location indicator which corresponds to
the location of the actula reader in the XNav enabled environment
i
Integer
Temporary calculation variable
j
Integer
Temporary calculation variable
LocationX Integer Global variable which stores the X coordinate of the calculated
location
LocationY Integer Global variable which stores the Y coordinate of the calculated
location
39
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
PreviousX Integer Global variable which stores the X coordinate of the previous
calculated location for the calculation of directional orientation
PreviousY Integer Global variable which stores the Y coordinate of the previous
calculated location for the calculation of directional orientation
Steps
Inputs:
sRoomMIdX() As Integer
sRoomMIdY() As Integer
arrBtnDetected() As Button
detectedIDsIndex As Integer
I. If detectedIDsIndex > 1 Then
II. For i = 0 To detectedIDsIndex - 2
III. xReaderMid = (sRoomMIdX(i) + sRoomMIdX(i + 1)) / 2 [center point calculation]
IV. yReaderMid = (sRoomMIdY(i) + sRoomMIdY(i + 1)) / 2
V. If CheckInsideRoom() = False Then [Check whether the calculated location falls inside a
component (i.e inside a room, office etc…)]
VI. LocationX = xReaderMid
VII. LocationY = yReaderMid
VIII. SetLocation() [Indicate the position of location of the RFID reader on the XMap using
LocationX, LocationY]
IX. setOrientation() (Ref.6.3.2)
X. PreviousX = LocationX
XI. PreviousY = LocationY
XII. Exit For
XIII. End If
XIV. Next
XV. End If
XVI. End
40
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
41
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
7. Results and Findings
The accuracy of the algorithm and the proof of concept were verified using three different simulation test
scenarios.
1. Navigation inside a building structure
2. Navigation inside a Maze
3. Navigation in an outdoor environment
Results were gathered from each test using a simple matrix of evaluation.
Matrix of evaluation
1. Overall Accuracy
The accuracy of the location indicator on the XNav system with respect to the actual location of
the RFID reader in the XNav environment
2. Overall Directional Orientation Accuracy
The directional orientation of the location indicator with respect to the actual directional orientation
of the RFID reader in the XNav environment
3. Unanticipated behavior
Abnormal location indications on the XNav system with respect to the actual location of the RFID
reader in the XNav environment (“jumps”)
Each question will be answered with a numerical value which would range from 0 to 10 where 0 being the
minimum and 10 being the maximum.
The Possibility of successful navigate in this scenario is calculated by
[(Overall Accuracy + Overall Directional Orientation Accuracy Unanticipated Behavior) /
(Maximum Overall Accuracy + Maximum Directional Orientation Accuracy Minimum
Unanticipated Behaviour)] * 100%
42
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
7.1 Navigation inside a building structure
This test was administered on an XMap created using a blueprint similar to the indoor environment found
in a lecture theater of a typical University.
Fig 7.1.1 Ground floor of an assumed lecture center
An XMap was superimposed over this blueprint using the XMap module of the application. Imaginary
names are used to identify the building structures and occupants and unique RFID signatures are
assigned to each component.
Fig 7.1.2 The complete XMap of the indoor building environment
43
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Simulation Tests
Five unique routes were plotted on the XMap using the XSim Module and were tested against the XNav
system. The range of the RFID tags was varied between 6 and 50 for each test case and the simulation
was repeated. The following screenshots compare the location of the simulated RFID reader with the
XNav calculated location of the RFID reader.
Test 1 Observation Summery
XSim
1. Overall Accuracy: 9
2. Overall Directional Orientation
Accuracy: 9
3. Unanticipated behavior: 0
4. Possibility of successful
navigate in this scenario: 90%
XNav
Test 2 Observation Summery
XSim
1. Overall Accuracy: 7
2. Overall Directional Orientation
Accuracy: 7
3. Unanticipated behavior: 0
4. Possibility of successful
navigate in this scenario: 70%
XNav
44
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Test 3 Observation Summery
XSim
1. Overall Accuracy: 7
2. Overall Directional Orientation
Accuracy: 7
3. Unanticipated behavior: 0
4. Possibility of successful
navigate in this scenario: 70%
XNav
Test 4 Observation Summery
XSim
1. Overall Accuracy: 9
2. Overall Directional Orientation
Accuracy: 9
3. Unanticipated behavior: 0
4. Possibility of successful
navigate in this scenario: 90%
XNav
45
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Test 4 Observation Summery
XSim
1. Overall Accuracy: 7
2. Overall Directional Orientation
Accuracy: 6
3. Unanticipated behavior: 0
4. Possibility of successful
navigate in this scenario: 65%
XNav
46
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
7.2 Navigation inside a Maze
In this test a blueprint of a maze is used to test the accuracy of the system. The RFID tags are placed on
the edges of the maze and given unique identification signatures. The tags are placed in cycles. E.g. In
the first cycle tags are only place in junctions. In the second cycles the tags are placed at the endpoints of
each edge etc… Five identical simulation scenarios are run in each cycle to identify the best strategic
points at which the RFID tags should be placed. Also the range of the RFID tags is varied between a
value of 6 and 50 to identify the optimal operational range.
Fig 7.2.1 blueprint of the Maze
Fig 7.2.2 XMap Maze 1 (The RFID tags are spread along the edges)
47
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Fig 7.2.3 XMap Maze 2 (The RFID tags are positioned at the junctions)
Fig 7.2.4 XMap Maze 5 (The RFID tags are positioned at the junctions, edge ends and in between etc…)
48
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Simulation Tests
Test 1 Observation Summery
XSim
1. Overall Accuracy: 6
2. Overall Directional Orientation
Accuracy: 4
3. Unanticipated behavior: 5
4. Possibility of successful
navigate in this scenario: 25%
XNav
Test 2 Observation Summery
XSim
1. Overall Accuracy: 8
2. Overall Directional Orientation
Accuracy: 6
3. Unanticipated behavior: 5
4. Possibility of successful
navigate in this scenario: 45%
XNav
49
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Test 3 Observation Summery
XSim
1. Overall Accuracy: 6
2. Overall Directional Orientation
Accuracy: 5
3. Unanticipated behavior: 6
4. Possibility of successful
navigate in this scenario: 25%
XNav
Test 4 Observation Summery
XSim
1. Overall Accuracy: 7
2. Overall Directional Orientation
Accuracy: 5
3. Unanticipated behavior: 3
4. Possibility of successful
navigate in this scenario: 45%
XNav
50
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Test 5 Observation Summery
XSim
5. Overall Accuracy: 8
6. Overall Directional Orientation
Accuracy: 5
7. Unanticipated behavior: 3
8. Possibility of successful
navigate in this scenario: 50%
XNav
51
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
7.3 Navigation in an outdoor environment
In this test an aerial map of Brunel University is used as a blueprint. The map was obtained using “Google
Earth” software package (www.googleearth.com). An XMap was superimposed on the aerial map using
the XMap mapping component and RFID tags were placed on lamp post, building pillars etc Five
probable paths were plotted on the XMap using the XSim simulation component and the simulation tests
were administered by varying the RFID tag range between 6 and 50.
Fig 7.3.1 Lamp posts and pillars available on walkways at Brunel University (Ref.www.panoromio.com)
Fig 7.3.2 Aerial photo of Brunel University obtained using Google Earth (www.googleearth.com)
52
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Fig 7.3.3 XMap of Brunel University
Test 1 Observation Summery
XSim
9. Overall Accuracy: 9
10. Overall Directional Orientation
Accuracy: 9
11. Unanticipated behavior: 0
12. Possibility of successful
navigate in this scenario: 90%
XNav
53
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Test 2 Observation Summery
XSim
13. Overall Accuracy: 8
14. Overall Directional Orientation
Accuracy: 8
15. Unanticipated behavior: 0
16. Possibility of successful
navigate in this scenario: 80%
XNav
Test 3 Observation Summery
XSim
17. Overall Accuracy: 9
18. Overall Directional Orientation
Accuracy: 9
19. Unanticipated behavior: 0
20. Possibility of successful
navigate in this scenario: 90%
XNav
54
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
Test 4 Observation Summery
XSim
21. Overall Accuracy: 9
22. Overall Directional Orientation
Accuracy: 8
23. Unanticipated behavior: 3
24. Possibility of successful
navigate in this scenario: 75%
XNav
Test 5 Observation Summery
XSim
25. Overall Accuracy: 8
26. Overall Directional Orientation
Accuracy: 7
27. Unanticipated behavior: 3
28. Possibility of successful
navigate in this scenario: 60%
Comment: In a no signal zone it’s not
accurate. As soon as a signal is acquired
the location is calculated.
XNav
55
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
7.4 Real world testing of the XNav navigation system
The real world tests on the system were to be done after the results of the simulation testing were
analyzed. The results from the real world tests would then be cross referenced against the simulation
results and the accuracy of the algorithm, the accuracy of the simulation and the error would be derived
as numerical values. Unfortunately within the time frame of the project I was unable to acquire the
necessary equipment for the testing due to financial limitations. The allocated budget for an MSc student
for the dissertation is £100.00 where as the cost of the equipment for testing the XNav system was
estimated to be around £550.00. This section will explain how the tests would have been administered if
the equipment were available.
Hardware equipment
2.4 GHz RFID SMPD
-
100 CF Active
RFID Reader
Fig 7.4.1proposed RFID reader
Ref.
www.synometrix.com
Key Features
Long range up to 20 meters
Global 2.4GHz ISM Band, Anti-collision up to 200 tags
Ultra low power RF physics layer with embedded protocol
SDK offers data interface to write own applications, open ports,
set baud rate, read tag
Supports Visual Studio .NET
Small size and light weight
Specifications
Modulation: GFSK
Data Rate: 1000kbit/s
Frequency: 2.4 - 2.4835 GHz
RF power output:-40dBm ~ 0Bm
Sensitivity:-80 dBm ~ -90BM
Bit Error Rate: 10 -6
Protocols:
Super RFID Protocol 3.1
HDLC
Frequency Hopping Protocol
Echo Commands W/R Commands
Extended Commands
Temperature: -30 to 70C (Operating) -40 to 80C (Storage)
Dimension: 64.5 mm x 42.8 mm x 11 mm
Humidity: 100% Non-condensing
EMI: 10V/m 0.1~1000 MHz AM electromagnetic wave
Shock: 1-~2000 Hz 15g 3 axial
Power Supply: 6~24V DC
Current Consumption: 50mA
56
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
SMPK
-
101 Read Only Active RFID
Tag
Fig 7.4.2 proposed RFID tags
Ref.
www.synometrix.com
Specifications
Electronic
Modulation: Uplink/Downlink GFSK
Communication Rate: Uplink/Downlink 1000kbit/s
Frequency: 2.4 - 2.4835 GHz
RF power output:-20dBm ~ -5dBm
Sensitivity: -90dBm
Bit Error Rate: 10 -6
EMI: 10V/m 0.1~1000 MHz AM electromagnetic wave
Tag transmits signal to reader every 300ms - 500 ms
Environmental
Temperature: -30 to 70C (Operating) -40 to 80C (Storage)
Humidity: 100% Non-condensing
Vibration & Shock: 10~2000 Hz 15g 3 axial
Anti-electromagnetism: 10V/m 0.1~1000 MHz
Battery Life: 3.0V lithium cell 6-8 years (10 years optional)
Free Drop: 1M Concrete floor, twice per side
Water resistant (not waterproof)
Part Numbers
Blue: SMPK-101BU
Fig 7.4.5 Topology of the XNav real world test scenario
57
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
XNav real world test
Steps
1. Acquire the blueprint of the second floor of the “Brunel University Lecture Center”
2. Build an XMap over the blueprint and add the appropriate attributes (e.g. Room numbers,
descriptions etc…)
3. Catalog the unique RFID signatures of 50 active RFID tags
4. Allocate each room an RFID tag and add the signature to the XMap attributes
5. Run XSim simulation testing on the XMap and determine whether extra RFID tags are needed at
strategic locations for the XNav algorithm to work properly
6. Finalize the RFID placement according to the simulation results
7. Physically attach the RFID tags to the corresponding structures in the building ( e.g if rooms or
offices attach to the doors etc…)
8. Check whether all the RFID tags are transmitting properly, using the RFID reader
9. Download the complete XMap of the structure on to the XNav PDA
10. Define several navigation scenarios to be tested
11. Follow the scenarios and try to navigate using the XNav navigation system
12. Allow a complete stranger to the system and the building to find a specific location with the use of
the system
13. Repeat the scenario for several different locations and test subjects
14. Gather feedback on the ease of use and the accuracy of the system form the test subjects using
a specific questionnaire
15. Conclude whether the system is accurate, user-friendly and safe enough to be used as an indoor
navigation system
58
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
8. Discussion and Analysis
8.1 Navigation inside a building structure
In the first test scenario (navigation inside a building structure) the average value for successful
navigation is approximately 77%.
Average value for successful navigation is
approximately 77%.
Accurate
Inaccurate
Overall Accuracy 78%
Accurate
Inaccurate
Overall Directional Orientation Accuracy 76%
Accurate
Inaccurate
Unanticipated behavior 0%
Accurate
Inaccurate
Fig 8.1.1 statistics of the indoor navigation scenario
The XNav navigation system is primarily designed for indoor navigation. In this scenario the system is
tested in a lecture center environment where the pathways are clearly defined by the walls on opposite
sides. This allows the prime placement of the RFID tags throughout the indoor environment. The average
value for successful navigation, overall accuracy of the system and the overall directional orientation
accuracy are above 75% indicating that ¾ of the time the subject was able to navigate through the indoor
environment solely through the use of the system. This does not mean that ¼ of the time the subject will
be unable to navigate through the indoor environment using the system, but only that the subject may
need external guidance (e.g. sign boards, direction indicators etc…) to find his/her bearing in the XNav
environment. The unanticipated behavior of the system is down to a minimum in this scenario, indicating
that the XMap was properly built, tested and the RFID placement through out the XNav environment is
almost ideal.
59
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
8.2 Navigation inside a Maze
In the second scenario (Navigation inside a Maze) the average value for successful navigation is
approximately 38%
Average value for successful navigation is
approximately 38%
Accurate
Inaccurate
Overall Accuracy 70%
Accurate
Inaccurate
Overall Directional Orientation Accuracy 50%
Accurate
Inaccurate
Unanticipated behavior 44%
Accurate
Inaccurate
Fig 8.2.1 statistics of the Maze navigation scenario
The maze was designed to demonstrate the behaviour of the system in an extreme scenario. A maze is a
hypothetical situation where the accuracy of navigation system would be put to the test.
Challenges faced
1. The winding pathways of a maze are defined using thin walls on either side. Due to this the
pathways on either side of the wall will be marked using only one RFID tag. This may lead to
incorrect calculation of location in the XNav system. In the situation of a maze, no markers or
external guidance is provided to the subject. Thus if the location indicator is placed on the
opposite side of a thin wall, the subject is misguided and the overall accuracy is reduced.
2. The pathways are very narrow in the scenario of a maze. The average range of an active RFID
tag used in the system would be around 20m. This poses a great problem when calculating the
location. The RFID reader would receive signals from RFID tags in a 20m radius and the
calculation of the location is done using the RFID signatures. Due to this the calculated location
can be inaccurate and the unanticipated behaviour is increased.
3. Strategic positioning of the RFID tags is very difficult due to the nature of the maze. The creation
of the XMap and the actual real world implementation of it inside a maze is cumbersome and
prone to error. Due to this reason and the reasons mentioned above the directional orientation of
the RFID reader cannot be accurately approximated by the “Directional Orientation” algorithm.
The average success rate of navigation inside a maze is reduced to 38% due mostly to the unanticipated
behaviour of the system inside the maze.
60
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
8.3 Navigation in an outdoor environment
In the third scenario (Navigation in an outdoor environment) the average value for successful navigation is
approximately 79%
Average value for successful navigation is
approximately 79%
Accurate
Inaccurate
Overall Accuracy 86%
Accurate
Inaccurate
Overall Directional Orientation Accuracy 82%
Accurate
Inaccurate
Unanticipated behavior 12%
Accurate
Inaccurate
Fig 8.3.1 statistics of the outdoor navigation scenario
The scenario of navigation in an outdoor environment was designed to demonstrate the flexibility of the
system. This test scenario proves that if implemented properly, the XNav system can navigate outdoors
as well as indoors of a particular vicinity.
Challenges faced
1. The XMap has to be modeled on a blueprint of an environment. An aerial view of a vicinity is hard
to obtain due to many reasons. The solution was found in the “Google Earth”
(www.googleearth.com) system where an aerial satellite image can be obtained using software.
2. The pathways have to be defined by RFID tags for the XNav system to navigate through the
environment. After examining the premises it was found that most pathways in this particular
instance were marked using lamp-posts on the edges. These would provide perfect place holders
for the RFID tags. Pathways which are defined by building walls on either side would be tagged
by attaching the tags to the walls at regular intervals. RFID tags would also be placed on
benches, trees and special markers etc… for more accurate navigation through the system.
The success rate for navigation in this scenario is approximately 79%. The overall accuracy and the
directional orientation accuracy are above 80% due to the vicinity being extensively tagged. The
unanticipated behaviour in this instance is due mostly to the loss of RFID signals. Since the algorithm
calculates the location based solely on the RFID signals, the location indicator may stop in its tracks when
the RFID tags go out of range. When a new signal is received the system immediately re-calculates the
position of the location indicator. This might seem as a “jump” on the system and is considered as
unanticipated behaviour.
61
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
8.4 Real world test results
The real world testing of the system would have provided valuable information about the accuracy, safety
and user-friendliness of the system. Using the feedback provided by the test subjects, the Overall
Accuracy, Overall Directional Orientation Accuracy, Unanticipated behavior and the Possibility of
successful navigate in this scenario would be calculated and compared with the simulation results.
By comparing the real world test results with the simulation results, the error between the real world
system and the simulation would be calculated.
8.5 Limitations of the XNav system
Since the test results of the XNav experiments are totally based on simulation, the limitations of the
system, in a real world scenario, are also theoretical. In a practical situation various different variable
could factor in to the proper functioning of the system.
a. Proper definition of the XMap
Initially it was thought that the RFID tags could be placed at any point in the XNav environment
provided it had a close proximity to its assigned structure. After rigorous simulation testing of
different scenarios and different paths, it was understood that the RFID tags should be placed at
strategic positions for the system to work with the maximum accuracy. (e.g. bigger rooms or
rooms which border two paths should be tagged with two RFID tags instead of one, identify the
blackout points where no signal is available and add a supporting RFID tag to reduce
unanticipated behaviour etc…). The proper definition of the XMap can only be achieved through
the testing of the XMap using the XSim simulation module. The map maker can switch the
simulation into “manual” mode and scout the whole XMap to find out locations where the XNav
system does not behave as anticipated. This limitation is avoided by the use of the XSim module
working in conjunction with the XMap module.
b. Limitations in the XSim simulation module
Due to the truncated timetable of an MSc dissertation, the XSim simulation module was designed
to simulate the most fundamental behaviors of the XNav system. External forces, limitations and
effects such as multi-path effect, signal attenuation etc… which are inherent with any wireless
system are not built into the XSim module. Thus any external force or effect acting upon the
system would not be reflected in the simulations. Although this may seem like a great
disadvantage of the system, the XNav algorithm is designed to work such that the effect of
external variables is a minimum in the calculation of location in the system.
62
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
c. Multi-path effect
In an indoor environment such as a building or a maze, the multi-path effect of RF signals can
cause serious issues with the validity of RFID signals within a certain area. It is not completely
understood how the multi-path effect would act upon the system in a real-world scenario but in a
theoretical perspective this poses minimum threat to the system due to the design of the
algorithm. This effect could not be tested using the XSim simulation module due to it not being
programmed into the simulation module.
Before Multi-path effect
After Multi-path effect
Fig 8.5.1 Multi-path effect
The above example proves the point that even if the RFID reader picks up a distant signal due to multi-
path effect, the XNav algorithm is not affected critically. In this instance the positioning is identical. Even if
the multi-path effect affects the system critically, the positioning, theoretically, should be accurate enough
for the user to identify his/her bearing and navigate.
d. Directional orientation (Directional Orientation Algorithm)
The “Directional orientation algorithm” algorithm was designed to provide the user a sense of
direction when navigating in an XNav enabled environment. Due to the time limitation of the
project, this algorithm was designed to approximate only four directions (i.e North, South, East
and West). Also the algorithm needs at least two location points before it can approximate the
directional orientation. (i.e. the user has to start walking before the algorithm can indicate
direction). Therefore initially when the location of the RFID reader is calculated the direction will
be set randomly. The user will have to take several steps before the system can identify his/her
direction.
e. Minimum RFID signature limit (XNav algorithm)
The XNav algorithm needs a minimum of two RFID signatures to calculate a location. If there is
an area on the XMap where only one RFID signature is present, the XMap needs to be modified
such that at least two RFID signatures are present at that specific location. This limitation can
only be identified using the XSim simulation module and new RFID tags should be placed in
strategic locations to rectify the problem. In areas where only one RFID signature is available, the
algorithm would seize to calculate and when more RFID signatures are obtained, the algorithm
would re-calculate and position the location identifier. This would result in a “jump” which would
be interpreted as unanticipated behaviour and would reduce the theoretical accuracy of the
system in the XNav enabled environment.
63
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
f. HALO algorithm
The HALO algorithm is designed to calculate the range of the RFID signature on the XMap. Since
the calculation of points contained within a circle demands a lot more processor overhead, the
HALO of the RFID tag is assumed to be a rectangle. The XNav system is designed to be hosted
on a PDA with limited processing and memory capabilities. Thus the processing overhead should
be reduced to a minimum. The limitation of the HALO being rectangular might seem significant
and could affect the calculation of the location in reality. In theory the optimal range of the RFID
tag is proven to be 25m (according to XSim simulation testing) where as most practical RFID tags
have a range of 20-80m. This would practically eliminate any theoretical limitation with the HALO
algorithm.
Fig 8.5.2 HALO algorithm and the actual RFID range
64
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
9. Conclusion
The XNav Navigation System was designed to address the limitations of GPS and other navigation
technologies with respect to indoor navigation. The project set out to understand the existing navigation
technologies and their limitations in an indoor environment and how these limitations could be addressed
by supplementing the existing technologies with new techniques. The Aim of the project was to develop a
complete end-to-end solution for indoor navigation through the use of RFID, WiFi and GPS by combining
custom map making, custom simulation and custom navigation software where portable databases
containing necessary information for rendering a dynamic map of a particular building can be downloaded
over the internet into a portable handheld device which hosts the navigation software and the navigation
algorithm that can use the RFID, WiFi, GPS signatures of a building to navigate within the limitation of an
optimum accuracy for a particular radio technology.
The project pursued five key objectives in terms of providing a feasible solution for the problem of indoor
navigation.
“The development of a map making software which allows the map maker the flexibility of defining
general attributes of a building such as building name, rooms numbers, occupant’s name, occupant’s
image, position etc… but also special attributes such as RFID signature, WiFi Access point ID, GPS
signature etc… that would be recorded in a portable database which can be used to re-generate the map
through a navigation software.”
The XMap map making module allows the mapmaker the flexibility and the capability of building a
complex software map over an existing blueprint of a structure. This software map (i.e. XMap) allows the
map maker to define attributes such as Component ID (The specific identification name given to a room,
office etc…), Description (The description of the map component (e.g. Office, WiFi research lab where all
the WiFi related experiments are conducted etc…), RFID (The RFID signature of the tag which will be
used to identify this component in the real world), WiFi ID (The WiFi Access point signature which would
identify a particular map component in the real world) and GPS (The GPS X and Y coordinates of a given
component in the real world). The complete software map is saved as a “.xmap” file which records all the
necessary attributes to dynamically recreate the software map on the XSim simulation module or the
XNav PDA.
“Development of a navigation software which could download a portable database over the internet, re-
generate the map using the parameters stored in the database and facilitate navigation guidance using a
hand held device such as a PDA, hardware modules specific to a particular radio technology and a
special navigation algorithm
The .xmap file created using the XMap module can be downloaded onto a PDA using the internet or any
other file transfer mechanism (e.g. Bluetooth, infrared etc…). The XNav navigation software system
installed on the PDA would render the textual .xmap file into a graphical dynamic XMap to be displayed
on the PDA for navigation. The XNav software system would then obtain input from any hardware
module(s) attached to the PDA (e.g. RFID reader, WiFi module, GPS transceiver etc…) and forward the
information on to the XNav algorithm which would in turn calculate the location and directional orientation
of the PDA in the XNav enabled environment.
“Formulation of the navigation algorithm which would be embedded in the navigation software and would
use the unique identifier signatures used to mark internal structures of buildings to provide a visual aid to
the user on his or her bearing, orientation and suitable routes to fulfill the journey from point A to point B
using predefined criterion”
The XNav algorithm embedded in the XNav navigation software takes the unique RFID signatures as
inputs and calculates the location of the PDA in the XNav enabled environment. The location of the PDA
in the XNav enabled environment is indicated on the PDA XMap. The calculation of the location is done
using the core XNav algorithm and the HALO” and “HALO2” algorithms which approximate the location
of the PDA in the XNav enabled environment with respect to the RFID signatures obtained. The
“Directional Orientation Algorithm” approximates the direction in which the PDA bearer is moving and
65
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
indicates it on the PDA. The PDA bearer can identify his/her bearing in the XNav enabled environment
using the location and direction indicator. Knowing the current location in the XNav enabled environment,
the PDA bearer can then plan the appropriate path which would guide him/her to the respective
destination. i.e. the PDA bearer can identify point A and then navigate onto point B using the system.
“Development of a simulation software which would simulate navigation through buildings mapped using
the mapping software and enable testing of maps using different test cases and scenarios to identify the
ideal positioning of RFID tags on the XMap for maximum accuracy of the navigation system and the
hardware specifications for the tags, readers etc… prior to the ordering of hardware equipment
XSim is the simulation module of the XNav navigation system. XSim is designed to simulate a person
walking through an XNav enabled environment using the XNav navigation system and a RFID reader.
The XSim module incorporates three main algorithms which simulate movement, directional orientation
and the detection of RFID signatures in the building. The XSim software can simulate various navigational
scenarios through the XNav enabled environment. “Pre-plotted simulation” allows the map maker to plot
complicated paths on the XMap loaded onto the simulation arena and simulate a person walking along
that path using an XNav PDA. The simulation speed and the RFID signal strength (range) can be varied
to find the optimal configuration for the scenario before tendering any hardware components. The
“manual simulation” feature allows the map maker to scout hard to reach areas and to pinpoint locations
where RFID tags may go out of range or might not be sufficient for the XNav algorithm to work.
“Determine the numerical value which would elaborate and identify the accuracy of the system through
the use of simulation and real world testing in order to conclude whether the accuracy is sufficient for the
system to be safely and reliably adopted by users in real world scenarios”
Due to the truncated timetable of the project and the limited financial budget available to an MSc student,
the real-world tests could not be administered within the course of this dissertation. Using extensive
simulation testing with countless scenarios and variations, a figure of 77% and a figure of 79% were
respectively approximated as the success rates of a person navigating from point A to point B using the
XNav system, in an indoor environment and an outdoor environment. An extreme scenario of a maze was
tested to provide valuable insight into how the system would perform under extreme conditions. The
success rate was estimated to be 38% in this extreme scenario but much information was gathered
regarding how to improve the system to be versatile enough for any extreme environment or scenario.
According to the statistics obtained through rigorous simulation testing, the XNav system has achieved a
success rate of approximately 75 - 80% indoors and outdoors. This indicates that the XNav system is
capable of guiding a person in an indoor / outdoor environment ¾ of the time without any external
guidance. The remaining ¼ of the time the PDA bearer would have to refer to external guidance such as
sign boards, direction markers etc… to support the XNav system in identifying his/her bearing in the XNav
enabled environment. It was also identified that the system has a number of fundamental limitations when
subject to extreme scenarios and environments such as a maze. With a limited timetable of approximately
90 days and a limited financial budget of GBP 100.00, the complete XNav system (XMap, XSim and
XNav client) has successfully proved that RFID technology can be used as an instrument for indoor
navigation within the limitations of the technology.
If properly implemented, the system can guide countless people through complicated labyrinths such as
airports, hospitals, museums, universities, schools, football stadiums, warehouses, factory floors etc…
Although navigation in some of these scenarios might not be a matter of life and death, boarding a plane
on time, delivering that television immediately or locating the supervisor’s office to make a 1.30
appointment could equally be critical in a fast paced world. XNav has proven to have the potential to be
the next “de facto” standard for navigation within large commercial, educational and social environments.
66
Title : XNav Indoo r Navigation System Using RFID Technology
Document : Dissertation
Student Name : Ishan Sudeera Abeywardena
Student ID : 0628399
Supervisor : Prof. Wamadeva Balachandran
Course : MSc Wireless Enterprise Business Systems (06 – 07)
10. Recommendations and future work
The XMap mapping module of the complete XNav system can be further improved to provide optimal
navigation and ideal RFID tag placement. In order for the XMap module to allow the map maker the ability
of placing the RFID tags at ideal locations, a grid feature can be incorporated into the system. This would
be a “switch on – switch off” grid which could be placed over the blueprint for placement of RFID markers.
A “snap-to-grid” feature can also be introduced so that the system calculates the optimal placement of the
RFID tags on the XMap. This would improve accuracy and would reduce time in designing an XMap.
The XMap components could be assigned unique colours to better identify or to group particular
structures. E.g. all the offices could be “blue” where as the fire escapes could be “red”. This would be
beneficial to the map maker because the structures can be identified at a glance and priorities can be
assigned when designing the XMap. The different colours would be especially beneficial to the user due
to the human brain being more sensitive to colours than textual letters. This would result in faster
identification of an XNav user’s bearing in an XNav environment.
The present XMap system only allows the mapmaker to define structures of rectangular shape. This has
no known effect on the XNav system but being able to define other shapes would improve the visual
aspect of the system. By being able to define custom shapes for structures, the map maker ensures the
PDA bearer has the optimal visual effect and support when navigating using the system.
The XSim component of the system can be further improved by providing the simulation engineer the
flexibility to perform various tests on the same scenario over an extended period of time. At present, due
to the time constraints, the XSim module cannot save any simulation paths defined in the arena. By
providing the capability of saving a simulation, a simulation engineer can define a set of complex paths
through the XNav environment and the save them onto “.xnav” files. These can be loaded onto the
simulation arena for identical simulation over an extended period of time. The XMap can be modified
according to the data gathered from the XSim simulations and the same simulation scenarios can be run
on the new XMap to verify the effect of the changes on system.
Due to the limited timetable and the knowledge on the behaviour of the system prior to rigorous simulation
testing, external effects such as multi-path effect, signal attenuation etc…were not built into the XSim
module. These effects can be built into the system to provide a much more accurate picture of how the
XNav system would behave subject to the inherent drawbacks of any wireless technology. Although the
XNav algorithm is designed to function oblivious to these effects, more insight can be obtained on how to
improve the system in complex and extreme scenarios such as a maze.
At present the “HALO” algorithm approximates the range of an RFID tag as a rectangle. The “HALO” of a
building component is used to forward RFID information form the XSim component to the XNav
component. For further accuracy of the system, the “HALO” can be designed to approximate the range of
the RFID signal to be a circle. This would prove very useful if the map components can be defined as
custom shapes instead of rectangles.
The “HALO2” algorithm which supplements the XNav algorithm,