Open AccessA Kalman‐filter‐based fusion method for accurate urban localisation
Author(s) -
Alfakih Marwan,
Keche Mokhtar,
Benoudnine Hadjira
Publication year - 2021
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/cmu2.12096
Subject(s) - gnss applications , computer science , kalman filter , multipath propagation , global positioning system , fusion , sensor fusion , satellite system , real time computing , satellite , positioning technology , computer vision , position (finance) , artificial intelligence , telecommunications , engineering , channel (broadcasting) , linguistics , philosophy , finance , economics , aerospace engineering
Abstract The outage and degradation of the global navigation satellite system (GNSS) signals caused by the multipath phenomena reduce the location accuracy of these systems in urban environment. Hence, integrating an additional localisation technology with the GNSS, so that each technology complements the weakness of the other one, is an efficient solution to improve this accuracy. The widespread availability of the Wi‐Fi technology makes it the most appropriate additional technology. In this work, a fusion algorithm based on a Kalman filter is used to integrate the GPS localisation with Wi‐Fi fingerprinting localisation in urban environment. The fusion algorithm uses the positions delivered by these two systems to achieve an accurate estimation of the mobile position. The experimental results show that the performance of the proposed fusion method is more accurate than those of the individual methods and other fusion methods from the literature.