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Localization algorithms for wireless sensor networks. M.Srbinovska, C.Gavrovski Ss.Cyril and Methodius University, Skopje Faculty of Electrical Engineering and IT-Skopje, R. Macedonia. DAAD. Deutscher Akademischer Austausch Dienst German Academic Exchange Service. Projekt „ISSNBS“. OUTLINE.
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Localization algorithms for wireless sensor networks M.Srbinovska, C.Gavrovski Ss.Cyril and Methodius University, Skopje Faculty of Electrical Engineering and IT-Skopje, R. Macedonia
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ OUTLINE • Introduction • Propagation models • Measurement uncertainty for position estimation • Experimental results • Conclusion NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ Introduction • Wireless sensor networks • monitor large areas, • monitoring the environment, air, water and soil. • GPS (global positioning system) does not work indoors. • Define the coordinates during the instalation. NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS Wireless channel model • Three propagation models are used: • Free space propagation model • Two – Ray ground model • Log-distance model NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ Received Signal Strength Indicator (RSSI) • RSSI – power of the signal at the receiver • Direct path n- path loss exponent NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ Received Signal Strength Indicator (RSSI) • The RSSI can be used to characterize the channel status. • Friis’ free space transmission equation is: NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ Multilateration Minimizing the mean square error: NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ • Measured vs. calculated RSSI with different n Measured vs. calculated RSSI with different n NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ Root mean square error between theoretical and measured RSSI with different n NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ Received Signal Strength Indicator X3 X2 X1 A6 A5 A4 Sensor node • It works at the 2.4 GHz ISM Band. • Each board features : • Silicon laboratories C8051F121 microcontroller • Chipcon CC2420 2.4 GHz 802.15.4 transceiver. Position of sensor nodes NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ Measurement uncertainty for position estimation NIS, 2010
DAAD Deutscher Akademischer Austausch Dienst German Academic Exchange Service Projekt „ISSNBS“ Experimental results Distance uncertainties of the sensor nodes NIS, 2010
Conclusion Wireless sensor networks are widely applicable to many practical applications including environmental monitoring, military applications etc. in which sensors may need to know their geographical locations The relationship between RSSI and distance was determined through practical experiments. Distance uncertainties of the sensor nodes through experimental measurements were presented. NIS, 2010
Thank You for your attention! NIS, 2010