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General Information
Editor-in-chief
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2015 Vol.7(5): 354-361 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2015.V7.985

Performance Comparison of the Kalman Filter Variants for Dynamic Mobile Localization in Urban Area Using Cellular Network

N. Bouzera, N. Mezhoud, A. Khireddine, and M. Oussalah
Abstract—A state space model for mobile terminal motion is presented which has the properties observed in true terminal motion. This model is used with a Kalman filter to combine the information of location estimates made at different times into an improved location estimate. This paper also provides experimental The performance comparison of the conventional non linear Kalman Filters and their adaptive variants for mobile dynamic location in urban area.The methodology uses TEMS Investigation software to retrieve network information including signal strength and cell-identities of various base transmitter stations (BTS). The distance from the mobile station (MS) to each BTS is therefore determined using Walfish-Ikigami radio propagation model. The different distances are therefore combined in the framework of nonlinear Kalman filter variants. In this work we compare the performance of four algorithms, based on the nonlinear Kalman Filter. For the mobile terminal localization, the results show that both of EKF, AEKF, UKF and AUKF work comparably well, in spite of the superior performance of the UKF and AUKF algorithms.

Index Terms—Mobile localization, nonlinear kalman filter variants, noise covariance adaption, cellular network.

N. Bouzera, N. Mezhoud, and A. Khireddine are with the Genie Electric Laboratory (LGEB), Faculty of Technology, University of Bejaia, TargaOuzamour, 06000 Bejaia, Algeria (e-mail: n.bouzera@gmail.com, mezhoud.naima@gmail.com, abdelkrim.khired@gmail.com).
M. Oussalah is with the University of Birmingham, Electronics, Electrical and Computer Engineering Edgbaston, Birmingham B15 2TT (e-mail: m.oussalah@bham.ac.uk).

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Cite:N. Bouzera, N. Mezhoud, A. Khireddine, and M. Oussalah, "Performance Comparison of the Kalman Filter Variants for Dynamic Mobile Localization in Urban Area Using Cellular Network," International Journal of Computer Theory and Engineering vol. 7, no. 5, pp. 354-361, 2015.

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