WLAN indoor positioning algorithm based on skewness-kurtosis testing

Focused on the issues that large positioning errors produced by the inconsistency of received signal strength (RSS)sample population distributions under indoor wireless local area network (WLAN),an indoor positioning algorithm based on skewness-kurtosis testing was proposed.By using the testing meth...

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Main Authors: Zhen-long SONG, Gang-yi JIANG, Chao HUANG, Mei YU, Jia-le ZHANG
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2012-05-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)05-0099-07/
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author Zhen-long SONG
Gang-yi JIANG
Chao HUANG
Mei YU
Jia-le ZHANG
author_facet Zhen-long SONG
Gang-yi JIANG
Chao HUANG
Mei YU
Jia-le ZHANG
author_sort Zhen-long SONG
collection DOAJ
description Focused on the issues that large positioning errors produced by the inconsistency of received signal strength (RSS)sample population distributions under indoor wireless local area network (WLAN),an indoor positioning algorithm based on skewness-kurtosis testing was proposed.By using the testing method of skewness and kurtosis,whether the RSS samples come from the normal population or not was checked.The distribution functions of the samples accepting null hypothesis were approximated with normal distribution,and the probability density functions of the samples refusing null hypothesis were estimated by kernel function.Experimental results show that the proposed algorithm leads to a 15 percent improvement over the previous methods.Moreover,the proposed algorithm can significantly reduce the workload of the off-line phase at the same positioning accuracy.
format Article
id doaj-art-3d3c98d17c5f4e30b39cd1d2eff32647
institution Kabale University
issn 1000-436X
language zho
publishDate 2012-05-01
publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-3d3c98d17c5f4e30b39cd1d2eff326472025-01-14T06:31:55ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2012-05-01339910559662222WLAN indoor positioning algorithm based on skewness-kurtosis testingZhen-long SONGGang-yi JIANGChao HUANGMei YUJia-le ZHANGFocused on the issues that large positioning errors produced by the inconsistency of received signal strength (RSS)sample population distributions under indoor wireless local area network (WLAN),an indoor positioning algorithm based on skewness-kurtosis testing was proposed.By using the testing method of skewness and kurtosis,whether the RSS samples come from the normal population or not was checked.The distribution functions of the samples accepting null hypothesis were approximated with normal distribution,and the probability density functions of the samples refusing null hypothesis were estimated by kernel function.Experimental results show that the proposed algorithm leads to a 15 percent improvement over the previous methods.Moreover,the proposed algorithm can significantly reduce the workload of the off-line phase at the same positioning accuracy.http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)05-0099-07/indoor positioningskewness-kurtosis testingkernel functionWLAN
spellingShingle Zhen-long SONG
Gang-yi JIANG
Chao HUANG
Mei YU
Jia-le ZHANG
WLAN indoor positioning algorithm based on skewness-kurtosis testing
Tongxin xuebao
indoor positioning
skewness-kurtosis testing
kernel function
WLAN
title WLAN indoor positioning algorithm based on skewness-kurtosis testing
title_full WLAN indoor positioning algorithm based on skewness-kurtosis testing
title_fullStr WLAN indoor positioning algorithm based on skewness-kurtosis testing
title_full_unstemmed WLAN indoor positioning algorithm based on skewness-kurtosis testing
title_short WLAN indoor positioning algorithm based on skewness-kurtosis testing
title_sort wlan indoor positioning algorithm based on skewness kurtosis testing
topic indoor positioning
skewness-kurtosis testing
kernel function
WLAN
url http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)05-0099-07/
work_keys_str_mv AT zhenlongsong wlanindoorpositioningalgorithmbasedonskewnesskurtosistesting
AT gangyijiang wlanindoorpositioningalgorithmbasedonskewnesskurtosistesting
AT chaohuang wlanindoorpositioningalgorithmbasedonskewnesskurtosistesting
AT meiyu wlanindoorpositioningalgorithmbasedonskewnesskurtosistesting
AT jialezhang wlanindoorpositioningalgorithmbasedonskewnesskurtosistesting