JOURNAL ARTICLE

Gsm Position Tracking Using A Kalman Filter

Jean‐Pierre DuboisJihad DabaManfred NaderC. El Ferkh

Year: 2012 Journal:   Zenodo (CERN European Organization for Nuclear Research) Vol: 6 (8)Pages: 867-876   Publisher: European Organization for Nuclear Research

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.

Keywords:
Kalman filter Position (finance) Tracking (education) Computer science GSM Extended Kalman filter Computer vision Artificial intelligence Telecommunications Psychology Business

Metrics

8
Cited By
1.15
FWCI (Field Weighted Citation Impact)
0
Refs
0.86
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Inertial Sensor and Navigation
Physical Sciences →  Engineering →  Aerospace Engineering
Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Wireless Sensor Networks for Data Analysis
Physical Sciences →  Computer Science →  Computer Networks and Communications

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