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Improving RFID-Based Indoor Positioning Accuracy Using Gaussian Processes

AutorSeco Granja, Fernando ; Plagemann, C.; Jiménez Ruiz, Antonio R. ; Burgard, W.
Fecha de publicación2010
EditorInstitute of Electrical and Electronics Engineers
Citación2010 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
ResumenThe received signal strength (RSS) of radiofrequency signals emitted from beacons placed at known locations in an environment, can be used by a local positioning system (LPS) to estimate the location of a person or a mobile object. In indoor environments, interference, multipath propagation of RF signals, and the presence of obstacles and people, lead to a complex spatial distribution of the RSS, which is inaccurately described by simple parametric models. In this work, we present a Bayesian method for an indoor RFID location system which uses an observation model based in Gaussian processes (GPs) nonparametric regression to represent the environment-specific RSS distributions for the individual RFID tags. The experimental results in an indoor environment demonstrate the effectiveness of GPs in order to increase positioning accuracy.
Versión del editorhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5637226
URI10261/32113
DOI10.1109/IPIN.2010.5647095
Aparece en las colecciones: (CAR) Comunicaciones congresos
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