![]() The most essential contribution is the novel state transition based on continuous walks along a navigation mesh, modeling only the building’s walkable areas. This work provides three major contributions to the system. Instead of using time-consuming approaches like classic fingerprinting or measuring the exact positions of access points, we use an optimization scheme based on a set of reference measurements to estimate a corresponding Wi-Fi model. Absolute positioning information is given by a comparison between recent Wi-Fi measurements of nearby access points and signal strength predictions. Our recently presented approximation scheme of the kernel density estimation allows to find an exact estimation of the current position, compared to classical methods like weighted-average. ![]() The pedestrian’s position is given by means of recursive state estimation using a particle filter to incorporate different probabilistic sensor models. ![]() Within this work we present an updated version of our indoor localization system for smartphones.
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