RFID and Positioning
Outline
• RFID Introduction
• Indoor Localization
• RFID positioning Algorithm
– LANDMARC
– RFID-Based 3-D Positioning Schemes
• RFID application
Outline
• RFID Introduction
• Indoor Localization
• RFID positioning Algorithm
– LANDMARC
– RFID-Based 3-D Positioning Schemes
• RFID application
RFID
• Automatic identification technology
• Transponder, interigator, antennaReaderRF
Characteristics
•
•
•
•
•
•
No line-of-sight required
Multiple simultaneous reads
Long read range(active tag)
Long life span
Very low cost
No (so) orientation sensitive
RFID Localization
• An important application of RFID
– Localization (warehouse, shipping container, ……)
Outline
• RFID Introduction
• Indoor Localization
• RFID positioning Algorithm
– LANDMARC
– RFID-Based 3-D Positioning Schemes
• RFID application
Indoor Localization
• Infrared
– Active Badge
– IR emitter communicate with a network of sensors in
the building
– Line-of-sight required, transmission range is short
• IEEE 802.11
– RADAR
– Combine empirical measurement and signal strength
modeling to determine location
– NIC needed, not practical for small device
Indoor Localization
• Ultrasonic
– Cricket Location Support System & Active Bat
Location System
– Use time-of-arrival to measure distances
– High accuracy, expensive
• RFID
– LANDARC
– Use RFID tags as reference tags
– Coarse accuracy, 2-D
Outline
• RFID Introduction
• Indoor Localization
• RFID positioning Algorithm
– LANDMARC
– RFID-Based 3-D Positioning Schemes
• RFID application
LANDMARC
本圖取自”LANDMARC: Indoor Location Sensing Using Active RFID”, Wireless Networks, Vol. 10, 701-710, 2004.
LANDMARC
Define :
• Methodology
Signal Strength Vector of
Suppose :
tracking tags
n RF readers
Su  (Su1 , Su 2 ,...,Sun ) u  (1, u )
m reference tags
Signal Strength Vector of
u tracking tags
reference tags
 m  ( m1 , m2 ,..., mn ) m (1, m)
LANDMARC
Define :
Euclidean distance in signal strength between a
tracking tag and a reference tag j
Euj 
2
(


S
)
i1 ji ui
n
j  (1, m)
When there are m reference tags, a tracking tag
has its E vector as
Eu  ( Eu1 , Eu 2 ,...,Eum )
LANDMARC
•
To determine the weights assigned to
different neighbors
1
wj 

k
i 1
•
2
Ei
1
Ei
2
Tracking tag location:
( x, y )  i 1 wi ( xi , yi )
k
Outline
• RFID Introduction
• Indoor Localization
• RFID positioning Algorithm
– LANDMARC
– RFID-Based 3-D Positioning Schemes
• RFID application
Active Scheme Setup
本圖修改自“RFID-Based 3-D Positioning Schemes”, Infocom 2007.
Effective Reference Tag Set
Effective Reference Tag Set
Coordinate Calculation
Compensate Degree of Irregularity
• Problem
– Diff. antenna gains and
path loss in different
directions
– Imperfect circle
• Solution
– Low cost antenna array
with multiple radiation
elements
– Superpose responses
本圖取改自“RFID-Based 3-D Positioning Schemes”, Infocom 2007.
Passive SchemeDetails
Outline
• RFID Introduction
• Indoor Localization
• RFID positioning Algorithm
– LANDMARC
– RFID-Based 3-D Positioning Schemes
• Conclusion
Conclusion
LANDMARC Advantage:
– No need for a large number of expensive RFID
reader.
– Environmental dynamic can easily be
accommodated.
– Location information is more accurate and reliable.
Conclusion
• Although active RFID is not designed for accurate indoor
location sensing, LANDMARC approach does show that active
RFID is a viable cost-effective candidate for indoor location
sensing.
• Three problem :
– SSI & Power level
– Long latency
– Variation of the behavior of tags
Conclusion
• Proposed two 3-D positioning schemes
– Both schemes are based on nonlinear
optimization methods
本圖取改自“RFID-Based 3-D Positioning Schemes”, Infocom 2007.
Reference
• [1] LIONEL M. NI, YUNHAO LIU, YIU CHO LAU,
ABHISHEK P. PATIL, “LANDMARC: indoor
location sensing using active RFID ”, in PerCom
2003
• [2] Chong Wang, Hongyi Wu, and Nian-Feng
Tzeng, “RFID-Based 3-D Positioning Schemes”,
in INFOCOM 2007