Indoor localization techniques for wireless sensor networks
Intérieur Techniques de localisation pour les réseaux de capteurs sans fil
Résumé
In this thesis, the author focused on RSSI based
localization algorithms for indoor applications in
wireless sensor networks. Firstly, from the observation
of RSSI behavior based on an experimental
localization system, an experimental RSSI channel
model is deduced, which is consistent to the popular
lognormal shadowing path loss model. Secondly, this
thesis proposes three indoor localization algorithms
based on multilateration and averaged RSSI. In these
algorithms, the measured distances are weighted
according to their assumed accuracy. Lastly, a RSSI
based parameter tracking strategy for constrained
position localization is proposed. To estimate channel
model parameters, least mean squares method (LMS)
is associated with the trilateration method.
Quantitative criteria are provided to guarantee the
efficiency of the proposed tracking strategy by
providing a tradeoff between the constraint resolution
and parameter variation. The simulation results show
a good behavior of the proposed tracking strategy in
presence of space-time variation of the propagation
channel. Compared with the existing RSSI based
algorithms, the proposed tracking strategy exhibits
better localization accuracy but consumes more
calculation time. In addition, experimental tracking test
is performed to validate the effectiveness of the
proposed tracking strategy.
Domaines
Electronique
Origine : Fichiers produits par l'(les) auteur(s)
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