1 Wireless Sensor Networks Akyildiz/Vuran Chapter 17: Underground Sensor Networks.
Localization in Zigbee based Sensor Networks · Sensor Networks, PIK - Praxis der...
Transcript of Localization in Zigbee based Sensor Networks · Sensor Networks, PIK - Praxis der...
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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
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Overview
Introduction Coarse-grained localisation
Centroid localisationWeighted centroid localisation
Realisation with CC2420Measurements Algorithm improvement
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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
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Location-based services
A moving user gets location-dependant services using an indoor location system
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Localization
Localization = determining where a given node is physically located in the network
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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
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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“
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Example 1
X = (0 + 50 + 0 + 50) / 4X = 25
Y = (0 + 0 + 50 + 50) / 4Y = 25
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Example 2
X = (50 + 100 + 100) / 3X = 83
Y = (100 + 100 + 50) / 3Y = 83
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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“
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– Weighted Centroid Localization –
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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:
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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
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1A
4A
2A
3A2d
d
d
4B
1B
3B
2BReal Position
Estimated Position
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1A
4A
2A
3A2d
d
d
4B
1B
3B
2BReal Position
Estimated Position
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1A
4A
2A
3A2d
d
d
4B
1B
3B
2BReal Position
Estimated Position
-Weight influences the position
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– Weighted Centroid Localization –& ZigBee
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CC2420 Development Boards for realising localisation -WCLBoards are equipped with an ATmega128L and CC2420Z-Stack provided by Chipcon installed on every Board
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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
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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
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Location 1 with PCB antenna
0
20
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60
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120
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0 5 10 15 20 25 30 35 40 45d/m
LQI/byte Location 1 with PCB antennaindoor, 40m long floor
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0
30
60
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120
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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
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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
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Real Position vs. Estimated Position
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– Improvements –
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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
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Outview
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Fusion of localization systems
Integrating technology DPWS*web services for device www.ws4d.org *Devices profile for Web services
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Summary
Weighted coarse-grained localisationusable for ZigBee nodes
Precision reasonable but to be improved
Transmission range important to improve precision
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Thank you
Contact information ? Dr. Frank Golatowski
Center for Life Science Automation
Friedrich-Barnewitz-Str. 8
18119 Rostock-WarnemuendeGermany
Tel.: +49 381 498 7274
Fax: +49 381 498 7251