Junseok Kim

Wireless Networking Lab (WINLAB)

Konkuk University, South Korea

http://usn.konkuk.ac.kr/~jskim

1

Why Localization is important

Where should I go to Gate 20?

Location-based applications

Personal navigation

Tracking shipments

Monitoring patients

Location-based network protocols

Geographical Routing

Topology Control

s

d

Which node is closest to destination?

Which node is closest to destination?

Which node is closest to destination?

Without location information With location information2

Path loss vs. Distance Path loss is the reduction in power of an

electromagnetic wave as it propagates through space

Distance can be estimated by path loss model

0

10

20

30

40

50

60

70

80

90

100

1 10 20 30 40 50 60 70 80 90 100

Pa

th L

oss

(d

B)

Distance (m)

3

Log distance Path loss Model

n: path loss exponent which indicates the rate at which the path loss increases with distance n is about 1.5~2.8 in indoor

d0: close-in reference distance which is determined from measurements close the transmitter

d: distance between sender and receiver PL(d0): path loss at distance d0

PL(d0) is about 38~42dB in indoor

0

0 log10)(d

dndPLPL

n

dPLPL

dd 10

)(

0

0

10

4

Trilateration Somehow complicated calculating

Not precise because of variation of Path loss

a b

c

α

β γ

(x2,y2)

(x3,y3)(x1,y1)

2

1

2

1

2 )()( yyxx

2

2

2

2

2 )()( yyxx

2

3

2

3

2 )()( yyxx

13121312

12

222

13

222

22

xxyyyyxx

yyb

yya

x

13121312

13

222

12

222

22

xxyyyyxx

xxa

xxb

y

(x, y)

5

RSSI vs. Time RSSI value fluctuates due to environmental changes

RSSI: Receive Signal Strength Indicator

-90

-85

-80

-75

-70

1 6 11 16 21 26 31 36 41 46

RS

SI

(dB

m)

Time (min)

6

Maximum Likelihood Estimation (MLE) Use probability to improve accuracy

50m

45 46 47 48 49 50 51 52 53 54 55

x

y

z

7

MLE (Cont.) Divide region into many cells and find the cell with the

highest probability of blind node being located

50m

45 46 47 48 49 50 51 52 53 54 55

2

2

2 2

)(exp

2

1)|(

xsp ji

Gaussian distribution

Estimated RSSI value at

distance of sender to a cell

n

dPLPL

dd 10

)(

0

0

10

Measured RSSI value

at receiverreference

node i

blind node

variance of RSSI

measurements

probability of blind node being located at j-th cell

in a view of reference node i8

MLE (Cont.) Divide region into many cells and find the cell with the

highest probability of a node being located

x

y

m

i

jij spL1

)|()(

probability of blind node

being located at j-th cell

probability of blind node being located at j-th cell

in a view of reference node i

the number of reference node

9

Min-Max Bounding Box Very easy and simple but less accurate than MLE

10

11