Please use this identifier to cite or link to this item:
https://scholarhub.balamand.edu.lb/handle/uob/2055
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Daba, Jihad S. | en_US |
dc.contributor.author | Nader, Manal | en_US |
dc.contributor.author | Ferekh, C. El | en_US |
dc.date.accessioned | 2020-12-23T09:05:33Z | - |
dc.date.available | 2020-12-23T09:05:33Z | - |
dc.date.issued | 2012 | - |
dc.identifier.uri | https://scholarhub.balamand.edu.lb/handle/uob/2055 | - |
dc.description.abstract | GSM has undoubtedly become the most widespread cellular technology and has established itself as one of the most promising technology in wireless communication. The next generation of mobile telephones had also become more powerful and innovative in a way that new services related to the user-s location will arise. Other than the 911 requirements for emergency location initiated by the Federal Communication Commission (FCC) of the United States, GSM positioning can be highly integrated in cellular communication technology for commercial use. However, GSM positioning is facing many challenges. Issues like accuracy, availability, reliability and suitable cost render the development and implementation of GSM positioning a challenging task. In this paper, we investigate the optimal mobile position tracking means. We employ an innovative scheme by integrating the Kalman filter in the localization process especially that it has great tracking characteristics. When tracking in two dimensions, Kalman filter is very powerful due to its reliable performance as it supports estimation of past, present, and future states, even when performing in unknown environments. We show that enhanced position tracking results is achieved when implementing the Kalman filter for GSM tracking. | en_US |
dc.format.extent | 8 p. | en_US |
dc.language.iso | eng | en_US |
dc.subject | Cellular communication | en_US |
dc.subject | Estimation | en_US |
dc.subject | GSM | en_US |
dc.subject | Kalman Kalman | en_US |
dc.subject | Positioning | en_US |
dc.title | GSM position tracking using a kalman filter | en_US |
dc.type | Journal Article | en_US |
dc.contributor.affiliation | Department of Electrical Engineering | en_US |
dc.contributor.affiliation | Institute of Environment | en_US |
dc.description.volume | 6 | en_US |
dc.description.issue | 8 | en_US |
dc.description.startpage | 1354 | en_US |
dc.description.endpage | 1363 | en_US |
dc.date.catalogued | 2017-11-13 | - |
dc.description.status | Published | en_US |
dc.identifier.OlibID | 174906 | - |
dc.identifier.openURL | https://docs.google.com/viewerng/viewer?url=http://waset.org/publications/12100/pdf | en_US |
dc.relation.ispartoftext | Journal of world academy of science engineering and technology | en_US |
dc.provenance.recordsource | Olib | en_US |
crisitem.author.parentorg | Faculty of Engineering | - |
Appears in Collections: | Department of Electrical Engineering |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.