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Improving Wi-Fi based Indoor Positioning using Particle Filter based on Signal Strength

Sakib, Md. Sabbir Rahman; Quyum, Md Abdul; Andersson, Karl; Synnes, Kare and Körner, Ulf LU (2014) 9th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) In 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) p.1-6
Abstract
Indoor positioning is recognized as one of the upcoming major applications which can be used in wide variety of applications such as indoor navigation and enterprise asset tracking. The significance of localization in indoor environments have made the use of Wi-Fi based indoor positioning so that it can utilize available current wireless infrastructure and perform positioning very easily. In this paper we introduced a user friendly prototype for Wi-Fi based indoor positioning system where a user can identify its own position in indoor. Wi-Fi received signal strength (RSS) fluctuations over time introduce incorrect positioning To minimize the fluctuation of RSS, we developed Particle Filters with the prototype. A comparison between with and... (More)
Indoor positioning is recognized as one of the upcoming major applications which can be used in wide variety of applications such as indoor navigation and enterprise asset tracking. The significance of localization in indoor environments have made the use of Wi-Fi based indoor positioning so that it can utilize available current wireless infrastructure and perform positioning very easily. In this paper we introduced a user friendly prototype for Wi-Fi based indoor positioning system where a user can identify its own position in indoor. Wi-Fi received signal strength (RSS) fluctuations over time introduce incorrect positioning To minimize the fluctuation of RSS, we developed Particle Filters with the prototype. A comparison between with and without Particle Filter for error performance is presented and at the same time it is also noticed that variation in number of particles could change the positioning accuracy. Moreover comparison between calibration data in all directions and in one direction while constructing a radio map is presented. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
positioning, rss fingerprinting, particle filters, radio map, calibration data
in
2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)
pages
1 - 6
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
9th IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)
external identifiers
  • WOS:000356411200011
  • Scopus:84903724241
ISBN
978-1-4799-2842-2
DOI
10.1109/ISSNIP.2014.6827597
language
English
LU publication?
yes
id
6f3285f9-bdc1-473f-8e87-82a88ba9c3ec (old id 7596501)
date added to LUP
2015-07-23 09:58:35
date last changed
2016-10-13 04:51:00
@misc{6f3285f9-bdc1-473f-8e87-82a88ba9c3ec,
  abstract     = {Indoor positioning is recognized as one of the upcoming major applications which can be used in wide variety of applications such as indoor navigation and enterprise asset tracking. The significance of localization in indoor environments have made the use of Wi-Fi based indoor positioning so that it can utilize available current wireless infrastructure and perform positioning very easily. In this paper we introduced a user friendly prototype for Wi-Fi based indoor positioning system where a user can identify its own position in indoor. Wi-Fi received signal strength (RSS) fluctuations over time introduce incorrect positioning To minimize the fluctuation of RSS, we developed Particle Filters with the prototype. A comparison between with and without Particle Filter for error performance is presented and at the same time it is also noticed that variation in number of particles could change the positioning accuracy. Moreover comparison between calibration data in all directions and in one direction while constructing a radio map is presented.},
  author       = {Sakib, Md. Sabbir Rahman and Quyum, Md Abdul and Andersson, Karl and Synnes, Kare and Körner, Ulf},
  isbn         = {978-1-4799-2842-2},
  keyword      = {positioning,rss fingerprinting,particle filters,radio map,calibration data},
  language     = {eng},
  pages        = {1--6},
  publisher    = {ARRAY(0xb15b288)},
  series       = {2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)},
  title        = {Improving Wi-Fi based Indoor Positioning using Particle Filter based on Signal Strength},
  url          = {http://dx.doi.org/10.1109/ISSNIP.2014.6827597},
  year         = {2014},
}