Indoor localization using step and turn detection together with floor map information
- 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 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.
Author: | Lukas Köpping, Frank Ebner, Marcin Grzegorzek, Frank Deinzer |
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URN: | urn:nbn:de:bvb:863-opus-976 |
Parent Title (German): | FHWS science journal |
Document Type: | Article |
Language: | English |
Date of Publication (online): | 2015/01/07 |
Year of publication: | 2014 |
Publishing Institution: | Hochschule für Angewandte Wissenschaften Würzburg-Schweinfurt |
Creating Corporation: | Hochschule für angewandte Wissenschaften Würzburg-Schweinfurt |
Release Date: | 2015/01/07 |
Tag: | particle filter; step detection; turn detection |
Volume: | 2 (2014) |
Issue: | 1 |
First Page: | 40 |
Last Page: | 49 |
Institutes and faculty: | Fakultäten / Fakultät Informatik und Wirtschaftsinformatik |
Regensburger Klassifikation: | Informatik |
Licence (German): | ![]() |