Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)

To increase the accuracy of Location-aware personal computing application, multi-observers of IEEE 802.11 (Wi-Fi) signals can be used to track indoor user location. Even-though Wi-Fi is more and more widely available on most mobile devices, unfortunately, because of the reflection, refraction, tem...

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Main Authors:	Mantoro, Teddy, Ayu, Media Anugerah, Raman, Shakiratul Husna, Md. Latiff , Nurul Hidayati
Format:	Conference or Workshop Item
Language:	English English
Published:	2011
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/15025/ http://irep.iium.edu.my/15025/ http://irep.iium.edu.my/15025/1/Particle_filter_approach_for_estimating_indoor_mobile_user_location.pdf http://irep.iium.edu.my/15025/4/Particle_Filter_Approach_for_Tracking_Indoor_%28full_text%29.pdf

id	iium-15025
recordtype	eprints
spelling	iium-150252012-01-09T03:52:26Z http://irep.iium.edu.my/15025/ Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090) Mantoro, Teddy Ayu, Media Anugerah Raman, Shakiratul Husna Md. Latiff , Nurul Hidayati T Technology (General) To increase the accuracy of Location-aware personal computing application, multi-observers of IEEE 802.11 (Wi-Fi) signals can be used to track indoor user location. Even-though Wi-Fi is more and more widely available on most mobile devices, unfortunately, because of the reflection, refraction, temperature, humidity and the dynamic changing in the environment, the reading of Wi-Fi’s signal fluctuates greatly; the deviation can reach up to 33% from single Wi-Fi’s access point. This creates problem in tracking user location indoor. Moreover, the use of light estimation algorithms such as fingerprinting, ranking algorithm, Weighted Centroid method, k-Nearest Neighbour, did not give a good tracking result. This paper proposes the use of Particle Filter in improving user location estimation which involves the modeling of non-linear and non-Gaussian systems. The aim is to increase the accuracy of tracking user location indoor. In our experiments, the real time data of multi-observer Wi-Fi signals have been used and the loss of diversity and parameter chosen in order to reduce the ambiguity has also been observed. We improve the algorithm in reducing the computational complexity by giving target/reference points. The paper discussed the comparison between the true location and the estimated location based on two types of signals data: normal data and noise data. The location estimation is predicted based on real-time signal and then compare it to the training data set. This approach shows a promising result in tracking user location indoor using particle filter algorithm. 2011 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/15025/1/Particle_filter_approach_for_estimating_indoor_mobile_user_location.pdf application/pdf en http://irep.iium.edu.my/15025/4/Particle_Filter_Approach_for_Tracking_Indoor_%28full_text%29.pdf Mantoro, Teddy and Ayu, Media Anugerah and Raman, Shakiratul Husna and Md. Latiff , Nurul Hidayati (2011) Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090). In: The First International Conference on Engineering and Technology Innovation (ICETI 2011), 11-15 Nov 2011, Kenting, Taiwan. http://sparc.nfu.edu.tw/~iceti2011/download/ICETI2011_Proceedings.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T Technology (General)
spellingShingle	T Technology (General) Mantoro, Teddy Ayu, Media Anugerah Raman, Shakiratul Husna Md. Latiff , Nurul Hidayati Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)
description	To increase the accuracy of Location-aware personal computing application, multi-observers of IEEE 802.11 (Wi-Fi) signals can be used to track indoor user location. Even-though Wi-Fi is more and more widely available on most mobile devices, unfortunately, because of the reflection, refraction, temperature, humidity and the dynamic changing in the environment, the reading of Wi-Fi’s signal fluctuates greatly; the deviation can reach up to 33% from single Wi-Fi’s access point. This creates problem in tracking user location indoor. Moreover, the use of light estimation algorithms such as fingerprinting, ranking algorithm, Weighted Centroid method, k-Nearest Neighbour, did not give a good tracking result. This paper proposes the use of Particle Filter in improving user location estimation which involves the modeling of non-linear and non-Gaussian systems. The aim is to increase the accuracy of tracking user location indoor. In our experiments, the real time data of multi-observer Wi-Fi signals have been used and the loss of diversity and parameter chosen in order to reduce the ambiguity has also been observed. We improve the algorithm in reducing the computational complexity by giving target/reference points. The paper discussed the comparison between the true location and the estimated location based on two types of signals data: normal data and noise data. The location estimation is predicted based on real-time signal and then compare it to the training data set. This approach shows a promising result in tracking user location indoor using particle filter algorithm.
format	Conference or Workshop Item
author	Mantoro, Teddy Ayu, Media Anugerah Raman, Shakiratul Husna Md. Latiff , Nurul Hidayati
author_facet	Mantoro, Teddy Ayu, Media Anugerah Raman, Shakiratul Husna Md. Latiff , Nurul Hidayati
author_sort	Mantoro, Teddy
title	Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)
title_short	Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)
title_full	Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)
title_fullStr	Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)
title_full_unstemmed	Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)
title_sort	particle filter approach for estimating indoor mobile user location using ieee 802.11 signals (f1090)
publishDate	2011
url	http://irep.iium.edu.my/15025/ http://irep.iium.edu.my/15025/ http://irep.iium.edu.my/15025/1/Particle_filter_approach_for_estimating_indoor_mobile_user_location.pdf http://irep.iium.edu.my/15025/4/Particle_Filter_Approach_for_Tracking_Indoor_%28full_text%29.pdf
first_indexed	2023-09-18T20:24:03Z
last_indexed	2023-09-18T20:24:03Z
_version_	1777408298335600640

Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090)

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