Localization in Zigbee based Sensor Networks

Ralf Grossmann, Jan Blumenthal, Frank Golatowski*, Dirk Timmermann

University of RostockInstitute of Applied Microelectronics and Computer Engineering

* Center for Life Science AutomationRostock

Overview

Introduction Coarse-grained localisation

Centroid localisationWeighted centroid localisation

Realisation with CC2420Measurements Algorithm improvement

Use of WSN in Life Science Automation

Monitoring of environmental conditionsMeasuring environmentalparameters

temperature, humidity, lightH2, CO, CO2etc.

Sensing vibrationsTracking and control process parametersControl building automationTracking of service robotsSupport ambient services for life science industryOffering location based services

Location-based services

A moving user gets location-dependant services using an indoor location system

Localization

Localization = determining where a given node is physically located in the network

Coarse-Grained

Methods for localizationin WSN

Fine-Grained Scene analysis

Trilateration

Triangulation

Centroid determination

Other

static

differential

Physical contact

Monitoringat reference

Points

Overlapping of areas

Centroid localisation1

Algorithm:Beacons placed at known positionsSensor nodes are randomly distributed within ABeacons transmit their known positionSensor nodes receive messages containing position information of n different beaconsCalculation of position by centroid determination of received beacon positions

1A

4A

2A

3A2d

d

d

4B

1B

3B

2B

Pi‘ = Position of sensor node iBj = Position of beacon jr = Transmission Rangen = Number of received beacon positions

1

1'( , ) ( , )n

i jj

P x y B x yn =

= ∑

A

r

1) N. Bulusu, et. al.: „GPS-less Low Cost Outdoor Localization For Very Small Devices“

Example 1

X = (0 + 50 + 0 + 50) / 4X = 25

Y = (0 + 0 + 50 + 50) / 4Y = 25

Example 2

X = (50 + 100 + 100) / 3X = 83

Y = (100 + 100 + 50) / 3Y = 83

Algorithm: Centroid localisation1

: beacon : node

: Target area of sensor node

Advantages:• No RSSI measurement• No transmissions caused by

blindfolded nodes• Simple calculation• Small energy • Small memory footprint

HOWEVER:• Precision of centroid determination

mostly not sufficient

: transmission range of beacons

appapp ii yx ,

1) N. Bulusu, et. al.: „GPS-less Low Cost Outdoor Localization For Very Small Devices“

– Weighted Centroid Localization –

Weighted Centroid Localization WCL

Improvement of CLFind a better place of the real positionAlgorithm: Weighted Centroid Localization (WCL)

Simple & fast calculation Low memory footprint of algorithmAcceptable errorScalable

Jan Blumenthal, Frank Reichenbach, Dirk Timmermann: Precise Positioning with a Low Complexity Algorithm in Ad hoc Wireless Sensor Networks, PIK - Praxis der Informationsverarbeitung und Kommunikation, Vol.28 (2005), Journal-Edition No. 2, S.80-85, ISBN: 3-598-01252-7, Saur Verlag, Germany, June 2005

Jan Blumenthal, Frank Reichenbach, Dirk Timmermann: Position Estimation in Ad hoc Wireless Sensor Networks with Low Complexity (Slides), Joint 2nd Workshop on Positioning, Navigation and Communication 2005 (WPNC 05) & 1st Ultra-Wideband Expert Talk 2005 (05), S.41-49, ISBN: 3-8322-3746-1, Hannover, Germany, March 2005

Source:

Weighted Centroid Localization (WCL)

Approach:- Consider distance information into

position determination- Encapsulate distances in weight

functions wij()

( )1

1

( , )''( , )

b

ij jj

i b

ijj

w B x yP x y

w

=

=

⎛ ⎞⋅⎜ ⎟

⎝ ⎠=⎛ ⎞⎜ ⎟⎝ ⎠

∑

∑ wij = Weight between Bj and node ib = Number of beaconsBj(x,y)= Position of beacon j

1

1'( , ) ( , )n

i jj

P x y B x yn =

= ∑

WCL

CL''( , )iP x y

'( , )iP x y

1B 2B

3B4B

4id3id

2id1id

( , )iP x y

1A

4A

2A

3A2d

d

d

4B

1B

3B

2BReal Position

Estimated Position

1A

4A

2A

3A2d

d

d

4B

1B

3B

2BReal Position

Estimated Position

1A

4A

2A

3A2d

d

d

4B

1B

3B

2BReal Position

Estimated Position

-Weight influences the position

– Weighted Centroid Localization –& ZigBee

CC2420 Development Boards for realising localisation -WCLBoards are equipped with an ATmega128L and CC2420Z-Stack provided by Chipcon installed on every Board

LQI Link Quality IndicatorThe LQI measurement is a characterization of the strength and/or quality of a received packet.The LQI measurement shall be performed for each received packet, and the result shall be reported to the MAC sublayer as an integer ranging from 0x00 to 0xff. The minimum and maximum LQI values (0x00 and 0xff) should be associated with the lowest and highest quality Scaling the link quality to a LQI can be done using RSSI value, a signal-to-noise ratio estimation (correlation value), or a combination of these methods. The use of the LQI result by the network or application layers is not specified in this standard.IEEE 802.15.4 signals detectable by the receiver, and LQ values in between should be uniformly distributed between these two limits. At least eight unique values of LQ shall be used.

Source: IEEE Standard 802.15.4

CC2420: RSSI & LQI

CC2420 provides two useful measurements: RSSI and LQI. RSSI is the estimate of the signal power and is calculated over 8 symbol periods and stored in the RSSI VAL register.IEEE 802.15.4: The minimum and maximum LQI

values (0x00 and 0xff) should be associated with the lowest and highest quality Scaling link quality to LQI is calculated per Software

LQI = (RSSI register value + 38) * 4

Source: www.chipcon.com

Location 1 with PCB antenna

0

20

40

60

80

100

120

140

160

180

0 5 10 15 20 25 30 35 40 45d/m

LQI/byte Location 1 with PCB antennaindoor, 40m long floor

0

30

60

90

120

150

180

0 10 20 30 40d/m

LQI/byte LQI vs. distance between two Zigbee-based sensor nodes (CC2420DB)

Bradland: PORTABLE ANTENNA (Product ID: SMA (male) 2.4 gigs)

4 ZigBee Module

Location 2 with antennaempty parking place, outdoor

Scenario for testing WCLUsing LQI as a distance estimate

B1…B4 are configured as ZigBee routerP‘ acts as ZigBeecoordinatorWhile Bi transmit theirposition, P‘ only receivesdataIf all information forperforming thelocalization are available, WCL will be executed

d=10

Real Position vs. Estimated Position

– Improvements –

w=1/d 3̂w=1/d 0̂ (CL)w=1/d 2̂w=1/d 4̂w=1/d 5̂w=1/d

tropt,1=9.5trmin=7.1

Critical Range Divergent Error Graph

Loca

lizat

ion

Erro

r f [m

]

Transmission Range tr [m]

7.5 10 12.5 15 17.55. 0 202.50 25 27.5 30 32.5 3522.5 37.5 40 42.5

16

14

12

10

0

8

6

4

2

Transmission Rangedistance between beacons d=10

w=1/d

Outview

Fusion of localization systems

Integrating technology DPWS*web services for device www.ws4d.org *Devices profile for Web services

Summary

Weighted coarse-grained localisationusable for ZigBee nodes

Precision reasonable but to be improved

Transmission range important to improve precision

Thank you

Contact information ? Dr. Frank Golatowski

Frank.Golatowski@celisca.de

Center for Life Science Automation

Friedrich-Barnewitz-Str. 8

18119 Rostock-WarnemuendeGermany

Tel.: +49 381 498 7274

Fax: +49 381 498 7251