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.
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Abstract
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.
Item Type: | Conference or Workshop Item (Full Paper) |
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Additional Information: | 5960/15025 |
Uncontrolled Keywords: | Particle filter, IEEE 802.11 Signals, Indoor user location, Mobile user, Location-Aware Computing. |
Subjects: | T Technology > T Technology (General) |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System |
Depositing User: | Media Ayu |
Date Deposited: | 09 Jan 2012 08:50 |
Last Modified: | 09 Jan 2012 11:52 |
URI: | http://irep.iium.edu.my/id/eprint/15025 |
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