Radio map position inference algorithm for indoor positioning systems
Indoor positioning systems (IPS) have gain significant attention in the recent years; due to their relative low cost and high accuracy. However, till today, RSSI (received signal strength indicator)-based localization method pose a major challenge to engineers. The effects of severe fading and dynam...
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sg-ntu-dr.10356-1016732020-03-07T13:24:50Z Radio map position inference algorithm for indoor positioning systems Liu, Wei Ng, Bing Qiang Liu, Bin Guan, Yong Liang Leow, Yan Hao Huang, Jun School of Electrical and Electronic Engineering IEEE International Conference on Networks (18th : 2012 : Singapore) DRNTU::Engineering::Electrical and electronic engineering Indoor positioning systems (IPS) have gain significant attention in the recent years; due to their relative low cost and high accuracy. However, till today, RSSI (received signal strength indicator)-based localization method pose a major challenge to engineers. The effects of severe fading and dynamic nature of the indoor environment greatly degrade the accuracy of the system. In this paper, a position inference algorithm using radio map is proposed to improve the accuracy of RSSI-based indoor locating systems. The radio map is first setup during the calibration phase; samples of RSSI at each point, within the area of interest, is recorded and converted into probability density function. During operation phase an inference algorithm, based on Bayesian probability and distance of the calibrated points involved, can determine the likely position of the object of interest that is between the calibrated points. The system yields an accuracy of less than 1.5 meter, which is better than the current RSSI-based localization system. 2013-10-10T06:50:46Z 2019-12-06T20:42:36Z 2013-10-10T06:50:46Z 2019-12-06T20:42:36Z 2012 2012 Conference Paper Liu, W., Ng, B. Q., Liu, B., Guan, Y. L., Leow, Y. H., & Huang, J. (2012). Radio map position inference algorithm for indoor positioning systems. 2012 18th IEEE International Conference on Networks (ICON), pp.161-166. https://hdl.handle.net/10356/101673 http://hdl.handle.net/10220/16405 10.1109/ICON.2012.6506552 en |
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DRNTU::Engineering::Electrical and electronic engineering Liu, Wei Ng, Bing Qiang Liu, Bin Guan, Yong Liang Leow, Yan Hao Huang, Jun Radio map position inference algorithm for indoor positioning systems |
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Indoor positioning systems (IPS) have gain significant attention in the recent years; due to their relative low cost and high accuracy. However, till today, RSSI (received signal strength indicator)-based localization method pose a major challenge to engineers. The effects of severe fading and dynamic nature of the indoor environment greatly degrade the accuracy of the system. In this paper, a position inference algorithm using radio map is proposed to improve the accuracy of RSSI-based indoor locating systems. The radio map is first setup during the calibration phase; samples of RSSI at each point, within the area of interest, is recorded and converted into probability density function. During operation phase an inference algorithm, based on Bayesian probability and distance of the calibrated points involved, can determine the likely position of the object of interest that is between the calibrated points. The system yields an accuracy of less than 1.5 meter, which is better than the current RSSI-based localization system. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Liu, Wei Ng, Bing Qiang Liu, Bin Guan, Yong Liang Leow, Yan Hao Huang, Jun |
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Conference or Workshop Item |
author |
Liu, Wei Ng, Bing Qiang Liu, Bin Guan, Yong Liang Leow, Yan Hao Huang, Jun |
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Liu, Wei |
title |
Radio map position inference algorithm for indoor positioning systems |
title_short |
Radio map position inference algorithm for indoor positioning systems |
title_full |
Radio map position inference algorithm for indoor positioning systems |
title_fullStr |
Radio map position inference algorithm for indoor positioning systems |
title_full_unstemmed |
Radio map position inference algorithm for indoor positioning systems |
title_sort |
radio map position inference algorithm for indoor positioning systems |
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2013 |
url |
https://hdl.handle.net/10356/101673 http://hdl.handle.net/10220/16405 |
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1681048420892016640 |