A refinement scheme for location estimation process in indoor wireless sensor networks
Wireless Sensor Networks (WSNs) present one of the most representative and vibrant examples of networked embedded systems. With the emergence of location-based applications, location finding techniques are becoming increasingly important almost in all WSNs [1]. In this paper, we propose the improvem...
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creator | Artemenko, O Schorcht, G Tarasov, M |
description | Wireless Sensor Networks (WSNs) present one of the most representative and vibrant examples of networked embedded systems. With the emergence of location-based applications, location finding techniques are becoming increasingly important almost in all WSNs [1]. In this paper, we propose the improvement of location estimation of unknown wireless sensor nodes (a.k.a. unknowns or mobile nodes) through feeding the network with additional information about the a priori known distances between mobile nodes. We show with the simulation results that our method can enhance the accuracy of location estimation. For the localization of unknowns, we have used prepositioned anchor nodes (beacons). The proposed refinement scheme can be applied for different localization algorithms based on RSSI (Received Signal Strength Indication) [2], LQI (Link Quality Indicator) [3], ToF (Time of Flight), TDoA (Time Difference of Arrival) [4], etc. The radio channel model was determined using ZEBRA2411 modules from senTec Elektronik GmbH, based on the chipset ZRP1 developed by Freescale Semiconductor [5]. |
doi_str_mv | 10.1109/GLOCOMW.2010.5700315 |
format | Conference Proceeding |
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The proposed refinement scheme can be applied for different localization algorithms based on RSSI (Received Signal Strength Indication) [2], LQI (Link Quality Indicator) [3], ToF (Time of Flight), TDoA (Time Difference of Arrival) [4], etc. The radio channel model was determined using ZEBRA2411 modules from senTec Elektronik GmbH, based on the chipset ZRP1 developed by Freescale Semiconductor [5].</description><identifier>ISSN: 2166-0077</identifier><identifier>ISBN: 9781424488636</identifier><identifier>ISBN: 142448863X</identifier><identifier>EISSN: 2166-0077</identifier><identifier>EISBN: 9781424488650</identifier><identifier>EISBN: 1424488648</identifier><identifier>EISBN: 9781424488643</identifier><identifier>EISBN: 1424488656</identifier><identifier>DOI: 10.1109/GLOCOMW.2010.5700315</identifier><language>eng</language><publisher>IEEE</publisher><subject>Channel models ; Estimation ; Hardware ; Mathematical model ; Mobile communication ; Wireless communication ; Wireless sensor networks</subject><ispartof>2010 IEEE Globecom Workshops, 2010, p.225-229</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5700315$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5700315$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Artemenko, O</creatorcontrib><creatorcontrib>Schorcht, G</creatorcontrib><creatorcontrib>Tarasov, M</creatorcontrib><title>A refinement scheme for location estimation process in indoor wireless sensor networks</title><title>2010 IEEE Globecom Workshops</title><addtitle>GLOCOMW</addtitle><description>Wireless Sensor Networks (WSNs) present one of the most representative and vibrant examples of networked embedded systems. 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With the emergence of location-based applications, location finding techniques are becoming increasingly important almost in all WSNs [1]. In this paper, we propose the improvement of location estimation of unknown wireless sensor nodes (a.k.a. unknowns or mobile nodes) through feeding the network with additional information about the a priori known distances between mobile nodes. We show with the simulation results that our method can enhance the accuracy of location estimation. For the localization of unknowns, we have used prepositioned anchor nodes (beacons). 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subjects | Channel models Estimation Hardware Mathematical model Mobile communication Wireless communication Wireless sensor networks |
title | A refinement scheme for location estimation process in indoor wireless sensor networks |
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