3D-RABLC:a novel refinement algorithm based on LQI confidence for three-dimensional localization

A novel refinement algorithm based on LQI confidence for three-dimensional localization (3D-RABLC)was proposed.LQI confidence was obtained in terms of the relationships between RSSI and one hop distance,LQI and packet error rate(PER),which derived from experimental data.The measured RSSI was filtere...

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Main Authors: Jian SHU, Lin-lan LIU, Yu-bin CHEN, Jia-jie GONG
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2012-07-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)07-0125-10/
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author Jian SHU
Lin-lan LIU
Yu-bin CHEN
Jia-jie GONG
author_facet Jian SHU
Lin-lan LIU
Yu-bin CHEN
Jia-jie GONG
author_sort Jian SHU
collection DOAJ
description A novel refinement algorithm based on LQI confidence for three-dimensional localization (3D-RABLC)was proposed.LQI confidence was obtained in terms of the relationships between RSSI and one hop distance,LQI and packet error rate(PER),which derived from experimental data.The measured RSSI was filtered by LQI confidence.Moreover,the RSSI with lower confidence was modified by a three-dimensional multi-hop model or a compensating refinement method.The experiment results show that the algorithm reduces the RSSI range error,and improves the accuracy of three-dimensional localization significantly.
format Article
id doaj-art-29fbcd1e91cb414d92b4208129ac2886
institution Kabale University
issn 1000-436X
language zho
publishDate 2012-07-01
publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-29fbcd1e91cb414d92b4208129ac28862025-01-14T06:32:25ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2012-07-0133125134596636203D-RABLC:a novel refinement algorithm based on LQI confidence for three-dimensional localizationJian SHULin-lan LIUYu-bin CHENJia-jie GONGA novel refinement algorithm based on LQI confidence for three-dimensional localization (3D-RABLC)was proposed.LQI confidence was obtained in terms of the relationships between RSSI and one hop distance,LQI and packet error rate(PER),which derived from experimental data.The measured RSSI was filtered by LQI confidence.Moreover,the RSSI with lower confidence was modified by a three-dimensional multi-hop model or a compensating refinement method.The experiment results show that the algorithm reduces the RSSI range error,and improves the accuracy of three-dimensional localization significantly.http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)07-0125-10/wireless sensor networkthree-dimensional localizationLQI confidenceRSSIlocation refinement
spellingShingle Jian SHU
Lin-lan LIU
Yu-bin CHEN
Jia-jie GONG
3D-RABLC:a novel refinement algorithm based on LQI confidence for three-dimensional localization
Tongxin xuebao
wireless sensor network
three-dimensional localization
LQI confidence
RSSI
location refinement
title 3D-RABLC:a novel refinement algorithm based on LQI confidence for three-dimensional localization
title_full 3D-RABLC:a novel refinement algorithm based on LQI confidence for three-dimensional localization
title_fullStr 3D-RABLC:a novel refinement algorithm based on LQI confidence for three-dimensional localization
title_full_unstemmed 3D-RABLC:a novel refinement algorithm based on LQI confidence for three-dimensional localization
title_short 3D-RABLC:a novel refinement algorithm based on LQI confidence for three-dimensional localization
title_sort 3d rablc a novel refinement algorithm based on lqi confidence for three dimensional localization
topic wireless sensor network
three-dimensional localization
LQI confidence
RSSI
location refinement
url http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)07-0125-10/
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AT linlanliu 3drablcanovelrefinementalgorithmbasedonlqiconfidenceforthreedimensionallocalization
AT yubinchen 3drablcanovelrefinementalgorithmbasedonlqiconfidenceforthreedimensionallocalization
AT jiajiegong 3drablcanovelrefinementalgorithmbasedonlqiconfidenceforthreedimensionallocalization