Group 5

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1896
1920
1987
2006
Survey on indoor positioning
systems (IPS)
Zhou Haihang 0150332004
Huan Yang 0140339011
Bai Xuanyu 115033910088
Jin Yan 015033910010
Zheng Shengan 0140339027
Brian A. Ignacio Reyes 115030990049
Tian Tan 0150332007
Ivan M. Peñaranda Soria 115030990048
Outline
Business background
•Trend
•Applications
IPS approaches
•Technical approaches
•Positioning approaches
•Fingerprinting
•Triangulation
•Trilateration
•Connection based positioning
1
Business Background
Business background
The indoor location market is growing
rapidly
•At least 130 companies are working on indoor
maps, tracking and navigation technologies and
services.
•Indoor location market is expected to grow fast
and potential benefits are seen in every level
(consumer, service provider, operator and
supplier).
•There are individual players like Google and
also group of players like Nokia lead In-location
alliance (including at&t, intel, CISCO, microsoft)
•http://www.in-location-alliance.com/
Market expectations: Example on
Advertising
ABI Research proposes
that by 2017 up to 4$
billion would be spent on
indoor positioning based
advertising.
This is just one service
example but indicates the
expected potential of IPS
technology.
Applications
Airports
Universities
Stadiums
IDTechEx: The addressable market is around $10B with
healthcare expected to be the first to expand.
Navigation
•Finding places in large office buildings, university buildings,malls,
museums, hospitals
•Emergency situations: navigation of rescue personality and
localization of people
People and property tracking – patients, kids, visitors, travellers
•Example: Baggage tracking in airports
•Logistic – cargo and container tracking in warehouses, harbours,
airports etc.
•Device (Factories, Offices & Hospitals) and items tracking (keys,
wallets, bag, laptops etc.)
User applications
•Social applications: Finding people.
•Shopping, indoor parking assistance
Advertising
•Advertising based on where you are.
Unlimited applications
•Take advantage of position with cellphones,
tablets, Smart watches, etc.
•Display specific menus and options depending of the
location of user.
•Focused advertising
•Better maps for specific places, ability to save
places for reference or directions.
•Statistics of interest for the application owner.
Some companies working with IPS
2
IPS approaches
Problem definition
Wirelessly locate objects or people inside a building in real time.
Indoor Positioning Systems (IPS)
Real-time Locating Systems (RTLS)
Criteria
Accuracy
Coverage
Availability
Update rate
Costs and System Complexity
Technical IPS approaches
Terminal based IPS:
•Most commercial products use terminal based IPS
since it can be easily implemented without
permission/support from network.
Infrastructure based IPS:
•Current infrastructure based IPS products use either
dedicated IPS infrastructure or existing WiFi
networks.
Hybrid IPS (terminal and infrastructure based):
•Combine all available IPS information (WiFi, BT,
geomagnetic information, intertia sensor
•information)
Positioning approaches
Connection based positioning
In simple methods called as Cell of Origin or Cell
Identity terminal simply uses the location of the
serving wireless node.
To run this positioning system just a database of
station IDs and locations is needed.
The position is determined by measuring the signal
strengths from different stations.
•It is assumed that the closest station is the station from
which the strongest incoming signal on the device is
received.
•Terminal just send the ID of the serving station to the IPS
database. Then the database will send the location of the
station to the terminal.
Connection based positioning
Connection based positioning
Advantages
•No complicated algorithms
•Easy to implement
•Low cost
Disadvantages
•Low accuracy – room level
•Identification problem
Trilateration/multilateration
These methods assume that signal strength and/or time delay is
directly proportional to the distance between the user terminal
and the base station.
•When this assumption holds it is a simple geometrical
exercise to compute the location of the user terminal provided
that signals from at least three separate base stations can be
reliably received.
The challenge for a trilateration method is in the determination
of the distance between the base station and the user terminal.
•Methods that are based on time measurements assume accurate
synchronization between the base stations and the user
terminal.
•Methods that are based on the signal strength have problems
with interference and multipath propagation effects.
•Well‚Äźknown methods for distance estimation are
Time of arrive (ToA)
Time difference of arrive (TdoA)
Using relative Arrival time
measurements at each receiving
sensor
l
Example:
TDoAc-a= Txc – Txa = 10^-8s
TDoAb-a = Txb – Txa = 10^-7s
Received Signal Strength
Indicator
•
•
•
•
•
PR: Received signal strength at the receiver
PT: Transmitted power strength at the emitter
GT GR: Antenna gains of transmitter and receiver
d: Distance
P: The path loss factor
The path loss factor (P) is related to the environmental conditions
P = 2 for free space
P > 2 for environments with multipath
P ≈ (4 - 6) for typical indoor environments
Example
•The RSSI pattern is shown below.
• 3 WiFi routers
• 9 references points
•Q: Where is M(1.2, 2.6, 4.5) in this pattern?
1
5
2
5
1
2
1
3
1
2
4
1
1
3
1
3
3
1
1
2
2
1
2
3
4
3
3
2
3
5
Example (Continuation)
•Q: Where is M(1.2, 2.6, 4.5) in this pattern?
A: Measured RSSI of Wifi one is 1.2.
• Red zone (referenced RSSI of Wifi one is 1) are possible locations.
1
5
2
5
1
2
1
3
1
2
4
1
1
3
1
3
3
1
1
2
2
1
2
3
4
3
3
2
3
5
Example (Continuation)
•Q: Where is M(1.2, 2.6, 4.5) in this pattern?
•A: Measured RSSI of Wifi two is 2.6.
• Green zone (referenced RSSI of Wifi two is 3) are possible locations.
1
5
2
5
1
2
1
3
1
2
4
1
1
3
1
3
3
1
1
2
2
1
2
3
4
3
3
2
3
5
Example (Continuation)
•Q: Where is M(1.2, 2.6, 4.5) in this pattern?
•A: Measured RSSI of Wifi three is 4.5.
• Blue zone (referenced RSSI of Wifi two is 5) are possible locations.
• The intersection of three zones is the location of M.
•1
1
5
2
5
1
2
1
3
1
2
4
1
1
3
1
3
3
1
1
2
2
1
2
3
4
3
3
2
3
5
Triangulation
Base stations measure the angle of
arrival(AoA) for the received signal from
user terminal.
Location of the terminal is computed
using the known locations of the base
stations and AoA measurements.
Needs directive antennas and thus,
challenging to implement
•Special infrastructures needed.
Triangulation
Angle of Arrival / Direction of
Arrival
AoA/DoA
More sensors = Higher accuracy
Fingerprint based approach
Based on spatial differences in the radio
environment.
Fingerprint based methods include two phases.
•Off-line Phase
•A fingerprint database is build by collecting signal
strengths from all identified base stations at pre-defined
locations.
•Several measurements are collected at each location
and e.g. the median signal strength values are calculated.
•The values are inserted into a radio environment map.
•On-line Phase
•User terminal that desire to define location measure the
signal strengths from surrounding base stations and
compared result with the radio environment radio map.
•Usually many measurements are needed to define the
location from the radio environment map.
Example of fingerprinting
3
Example: google
The big player: Google
Due to Google business approach the user
reach in general is of great importance.
Google provides IPS map database and
location functions through Android
•http://maps.google.com/help/maps/indoormaps/
Did you know that Google uses your
Android to collect location based
information?
Automated multiradio
fingerprinting
Automated fingerprinting
Android Location Services check periodically
user location using GPS, 3GPP Cell-ID, and Wi-Fi
to locate your device.
When location is defined, user’s Android phone
will send back Wi-Fi access points' Service set
identifier (SSID) and Media Access Control (MAC)
data.
As a result Google can aggregate radio
fingerprinting information taking advantage of
users that employ Android based location services.
Not only Google does this. It's common
practice for location database vendors.
Limitations
The bottleneck in the Google approach is that
accurate user location is needed before measured
radio fingerprinting information is useful
Usually best reference location is obtained through
GPS
•automated indoor fingerprinting is difficult due to lack of
GPS
•either manual fingerprinting or other location reference
information is needed indoors
•manual fingerprinting is not possible without access to
indoor premises (then, of course, access to indoor maps can
be limited)
•Some development attempts have been done to use inertia
sensors to provide reference location: location known when
entering the building and inertia sensors used to update
location. Accuracy of this method decreases with
distance that user moves
References
[1] Z. Zhang Indoor Localization
CSI Wireless Networks
and Mobile Computing,
University of Ottawa.
[2] S. Sullivan Indoor Localization
Primer Local Social. Place London
(2014).
Thank you for your attention.
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