Abstract
Indoor localization based on ubiquitous WLAN has exhibited the capability of being a cheap and relatively precise technology and has been verified by many successful examples. Its performance is subject to change due to multipath propagation and changes in the environment (people, building layouts, antenna characteristics, etc.) which cannot be eliminated easily. An indoor localization and tracking algorithm is described which is based on the creation of a database of WLAN signal strengths at pre-chosen calibration points (CPs). The need for fewer CPs than in standard methods is due to use of a novel interpolation algorithm, based on the specification of robust, range and angle-dependent likelihood functions that describe the probability of a user being in the vicinity of each CP. The actual location of the user is estimated by solving a system of two non-linear equations with two unknowns derived for a pair of CPs. Different pairs of CPs can be chosen to make several estimates which then can be combined to increase the accuracy of the estimate. A variety of results are presented using challenging data collected in a typical office environment which demonstrate the accuracy that can be achieved with a reduced number of CPs.)) The method is compared to several competing localization methods and is shown to give superior results.
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