Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient

Being applicable for almost every scenario, mobile localization based on cellular network has gained increasing interest in recent years. Since received signal strength indication (RSSI) information is available in all mobile phones, RSSI-based techniques have become the preferred method for GSM loc...

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Main Authors: Huiyu Liu, Yunzhou Zhang, Xiaolin Su, Xintong Li, Ning Xu
Format: Article
Language:English
Published: SAGE Publishing 2015-08-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2015/157046
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spelling doaj-a78d2237b1f344c79da9ba5d0718afb42020-11-25T02:22:15ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-08-011110.1155/2015/157046157046Mobile Localization Based on Received Signal Strength and Pearson's Correlation CoefficientHuiyu LiuYunzhou ZhangXiaolin SuXintong LiNing XuBeing applicable for almost every scenario, mobile localization based on cellular network has gained increasing interest in recent years. Since received signal strength indication (RSSI) information is available in all mobile phones, RSSI-based techniques have become the preferred method for GSM localization. Although the GSM standard allows for a mobile phone to receive signal strength information from up to seven base stations (BSs), most of mobile phones only use the information of the associated cell as its estimated position. Therefore, the accuracy of GSM localization is seriously limited. In this paper, an algorithm for GSM localization is proposed with RSSI and Pearson's correlation coefficient (PCC). The information of seven cells, including the serving cell and six neighboring cells, is used to accurately estimate the mobile location. With redundant information, the proposed algorithm restrains the error of Cell-ID and shows good robustness against environmental change. Without any additional device or prior statistical knowledge, the proposed algorithm is implementable on common mobile devices. Furthermore, in the practical test, its maximum error is below 550 m, which is 100 m better than that of Cell-ID, and the mean error is below 150 m, which is 250 m better than Cell-ID.https://doi.org/10.1155/2015/157046
collection DOAJ
language English
format Article
sources DOAJ
author Huiyu Liu
Yunzhou Zhang
Xiaolin Su
Xintong Li
Ning Xu
spellingShingle Huiyu Liu
Yunzhou Zhang
Xiaolin Su
Xintong Li
Ning Xu
Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient
International Journal of Distributed Sensor Networks
author_facet Huiyu Liu
Yunzhou Zhang
Xiaolin Su
Xintong Li
Ning Xu
author_sort Huiyu Liu
title Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient
title_short Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient
title_full Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient
title_fullStr Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient
title_full_unstemmed Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient
title_sort mobile localization based on received signal strength and pearson's correlation coefficient
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2015-08-01
description Being applicable for almost every scenario, mobile localization based on cellular network has gained increasing interest in recent years. Since received signal strength indication (RSSI) information is available in all mobile phones, RSSI-based techniques have become the preferred method for GSM localization. Although the GSM standard allows for a mobile phone to receive signal strength information from up to seven base stations (BSs), most of mobile phones only use the information of the associated cell as its estimated position. Therefore, the accuracy of GSM localization is seriously limited. In this paper, an algorithm for GSM localization is proposed with RSSI and Pearson's correlation coefficient (PCC). The information of seven cells, including the serving cell and six neighboring cells, is used to accurately estimate the mobile location. With redundant information, the proposed algorithm restrains the error of Cell-ID and shows good robustness against environmental change. Without any additional device or prior statistical knowledge, the proposed algorithm is implementable on common mobile devices. Furthermore, in the practical test, its maximum error is below 550 m, which is 100 m better than that of Cell-ID, and the mean error is below 150 m, which is 250 m better than Cell-ID.
url https://doi.org/10.1155/2015/157046
work_keys_str_mv AT huiyuliu mobilelocalizationbasedonreceivedsignalstrengthandpearsonscorrelationcoefficient
AT yunzhouzhang mobilelocalizationbasedonreceivedsignalstrengthandpearsonscorrelationcoefficient
AT xiaolinsu mobilelocalizationbasedonreceivedsignalstrengthandpearsonscorrelationcoefficient
AT xintongli mobilelocalizationbasedonreceivedsignalstrengthandpearsonscorrelationcoefficient
AT ningxu mobilelocalizationbasedonreceivedsignalstrengthandpearsonscorrelationcoefficient
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