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    <title language="eng">Comparison of 2.4 GHz WiFi FTM- and RSSI-Based Indoor Positioning Methods in Realistic Scenarios</title>
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    <title language="eng">Indoor localization using step and turn detection together with floor map information</title>
    <abstract language="eng">In this work we present a method to estimate an indoor position with the help of smartphone sensors and without any knowledge of absolute positioning systems like Wi-Fi signals. Our&#13;
system uses particle filtering to solve the recursive state estimation problem of finding the position of a pedestrian. We show how to integrate the information of the previous state into the weight update step and how the observation data can help within the state transition model. High positional accuracy can be achieved by only knowing that the pedestrian makes a foot step or changes her direction together with floor map information.</abstract>
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    <title language="eng">On Wi-Fi Model Optimizations for Smartphone-Based Indoor Localization</title>
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    <title language="eng">Multi Sensor 3D Indoor Localisation</title>
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    <title language="eng">Robust self-localization using Wi-Fi, step/turn-detection and recursive density estimation</title>
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    <title language="eng">Smartphone-Based Indoor Localization within a 13th Century Historic Building</title>
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    <title language="eng">Using Barometer for Floor Assignation within Statistical Indoor Localization</title>
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    <title language="eng">Recovering From Sample Impoverishment in Context of Indoor Localisation</title>
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