1. Murat Demirbas SUNY Buffalo
Localization
Murat Demirbas
SUNY Buffalo

2. Localization
Localization of a node refers to the problem of identifying its spatial co-ordinates in some co-ordinate system
How do nodes discover their geographic positions in 2D or 3D space?
Model: static wireless sensor networks

3. Location Matters Sensor Net Applications Geographic routing protocols
Environment monitoring
Event tracking
Smart environment
Geographic routing protocols
GeoCast, GPSR, LAR, GAF, GEAR

4. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

5. Range-based localization
Distances between nodes to nodes/anchors measured wirelessly
TOA (Time of Arrival )
GPS
TDOA (Time Difference of Arrival)
Cricket
AOA (Angle of Arrive )
APS
RSSI (Receive Signal Strength Indicator)
RADAR

6. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

7. Time of arrival (TOA) Example: GPS
Uses a satellite constellation of at least 24 satellites with atomic clocks
Satellites broadcast precise time
Estimate distance to satellite using signal TOA
Trilateration
does not work indoors or under dense vegetation
high power consumption
high cost
big antenna does not fit in small (unobtrusive) node
B. H. Wellenhoff, H. Lichtenegger and J. Collins, Global Positioning System: Theory and Practice. Fourth Edition, Springer Verlag, 1997

8. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

9. Sound based ToF approach
Because the speed of sound is much slower (approximately 331.4m/s) than radio, it is easier to be applied in sensor network.
Some hurdles are:
Line of sight path must exist between sender and receiver.
Mono-direction.
Short range.

10. Cricket Intended for indoors use where GPS don't work
It can provide distance ranging and positioning precision of between 1 and 3 cm
Active beacons and passive listeners

11. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

12. Angle of arrival (AOA)
Idea: Use antenna array to measure direction of neighbors
Special landmarks have compass + GPS, broadcast location and bearing
Flood beacons, update bearing along the way
Once bearing of three landmarks is known, calculate position
"Medusa" mote
Dragos Niculescu and Badri Nath. Ad Hoc Positioning System (APS) Using AoA, IEEE InfoCom 2003

13. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

14. RADAR Bahl: MS research Offline calibration:
Tabulate <location, RSSI> to construct radio map
Real-time location & tracking:
Extract RSSI from base station beacons
Find table entry best matching the measurement

15. Problems with RSSI
Sensors have wireless transceivers anyway, so why not just use the RSSI to estimate distances?
Problem: Irregular signal propagation characteristics (fading, interference, multi-path etc.)
Graph from Bahl, Padmadabhan: RADAR: An In-Building RF-Based User Location and Tracking System

16. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

17. Range-free localization
Range-based localization:
Required Expensive hardware
Limited working range ( Dense anchor requirement)
Range-free localization:
Simple hardware
Less accuracy

18. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

19. Range-free: Centroid
Idea: Do not use any ranging at all, simply deploy enough beacons
Anchors periodically broadcast their location
Localization:
Listen for beacons
Average locations of all anchors in range
Result is location estimate
Good anchor placement is crucial!
Anchors
Nirupama Bulusu, John Heidemann and Deborah Estrin. Density Adaptive Beacon Placement, Proceedings of the 21st IEEE ICDCS, 2001

20. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

21. Hop-Count Techniques r DV-HOP [Niculescu & Nath, 2003]4
DV-HOP [Niculescu & Nath, 2003]
Amorphous [Nagpal et. al, 2003] 1 2 7 3 1 4 3 5 2 4 8 3 3 6 4 4 5
Works well with a few, well-located seeds and regular, static node distribution. Works poorly if nodes move or are unevenly distributed.

22. Outline Range-based localization Range-free localization GPS Cricket
APS
RADAR
Range-free localization
Centroid
DV-HOP
APIT

23. Overview of APIT
APIT employs a novel area-based approach. Anchors divide terrain into triangular regions
A node’s presence inside or outside of these triangular regions allows a node to narrow the area in which it can potentially reside.
The method to do so is called Approximate Point In Triangle Test (APIT).

24. Algorithm Anchor Beaconing Individual APIT Test Triangle Aggregation
Center of Gravity Estimation
Pseudo Code:
Receive beacons (Xi,Yi)
from N anchors
N anchors form triangles.
For ( each triangle Ti Є ){
InsideSet  Point-In-Triangle-Test (Ti) }
Position = COG ( ∩Ti InsideSet);

25. Perfect PIT
If there exists a direction in which M is departure from points A, B, and C simultaneously, then M is outside of ∆ABC. Otherwise, M is inside ∆ABC.
Require approximation for practical use
Nodes can’t move, how to recognize direction of departure
Exhaustive test on all directions is impractical

26. Departure test
Recognize directions of departure via neighbor exchange RSSI
Problems with the assumption!!!

27. APIT approximation Test only directions towards neighbors
Error in individual test exists, may be masked by APIT aggregation.

28. APIT: Approximate PIT Distances unknown for most adjacent points
Use neighbor nodes only
How to compare distances to beacons?
Stronger RSS
Distributed algorithm:
Beacon nodes broadcast their location
Each node builds a table of beacons it receives and the corresponding RSS
Each node broadcasts this table once (1 hop only)
3mv 56 23 C
2mv 31 45 B
1mv 20 A
MySS
(X,Y)
7mv
1mv
3mv
6mv
2mv
SSn
....
SS1
Node M

29. Error Case PIT = IN while APIT = OUT PIT = OUT while APIT = IN
Since the number of neighbors is limited, an exhaustive test on every direction is impossible.
InToOut Error can happen when M is near the edge of the triangle
OutToIn Error can happen with irregular placement of neighbors
PIT = IN while APIT = OUT PIT = OUT while APIT = IN

30. APIT Aggregation
High Possibility area
Grid-Based Aggregation
With a density 10 nodes/circle, Average 92% A.P.I.T Test is correct
Average 8% A.P.I.T Test is wrong
Low possibility area
Localization Simulation example

31. Evaluation DOI =0 DOI = 0.05 DOI = 0.2
Radio Model: Continuous Radio Variation Model.
Degree of Irregularity (DOI ) is defined as maximum radio range variation per unit degree change in the direction of radio propagation α
DOI = DOI = DOI = 0.2

32. Simulation Setup Setup Metrics 1000 by 1000m area
2000 ~ 4000 nodes ( random or uniform placement )
10 to 30 anchors ( random or uniform placement )
Node density: 6 ~ 20 node/ radio range
Anchor percentage 0.5~2%
90% confidence intervals are within in 5~10% of the mean
Metrics
Localization Estimation Error ( normalized to units of radio range)
Communication Overhead in terms of #message

33. Error Reduction by Increasing #Anchors
AH=10~28,ND = 8, ANR = 10, DOI = 0
Placement = Uniform
Placement = Random

34. Error Reduction by Increasing Node Density
AH=16, Uniform, AP = 0.6%~2%, ANR = 10
DOI=0.1
DOI=0.2

35. Error Under Varying DOI
ND = 8, AH=16, AP = 2%, ANR = 10
Placement = Uniform
Placement = Random

36. Communication Overhead
Centroid and APIT
Long beacons
DV-Hop and Amorphous
Short beacons
Assume: 1 long beacon = Range2  short beacons = 100 short beacons
APIT > Centroid
Neighborhood information exchange
DV-Hop > Amorphous
Online HopSize estimation
ANR=10, AH = 16, DOI = 0.1, Uniform

37. Performance Summary Centroid DV-Hop Amorphous APIT Accuracy Fair Good
Node Density
>0
>8
>6
Anchor
>10
ANR
>3
DOI
GPSError
Overhead
Smallest
Largest
Large
Small