Multi-Sensor Multi-Floor 3D Localization With Robust Floor Detection

Li, Y.; Gao, Zhouzheng; He, Z.; Zhang, P.; Chen, R.; El-Sheimy, N.

doi:10.1109/ACCESS.2018.2883869

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Multi-Sensor Multi-Floor 3D Localization With Robust Floor Detection

Authors

Li, Y.
External Organizations (TEMPORARY!);

/persons/resource/gaozz

Gao, Zhouzheng
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

He, Z.
External Organizations (TEMPORARY!);

Zhang, P.
External Organizations (TEMPORARY!);

Chen, R.
External Organizations (TEMPORARY!);

El-Sheimy, N.
External Organizations (TEMPORARY!);

External Ressource

No external resources are shared

Fulltext (public)

3963897.pdf
(Publisher version), 3MB

Supplementary Material (public)

There is no public supplementary material available

Citation

Li, Y., Gao, Z., He, Z., Zhang, P., Chen, R., El-Sheimy, N. (2018): Multi-Sensor Multi-Floor 3D Localization With Robust Floor Detection. - IEEE Access, 6, 76689-76699.
https://doi.org/10.1109/ACCESS.2018.2883869

Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_3963897

Abstract

Location has become an essential part of the next-generation Internet of Things systems. Thispaper proposes a multi-sensor-based 3D indoor localization approach. Compared with the existing 3D local-ization methods, this paper presents a wireless received signal strength (RSS)-profile-based floor-detectionapproach to enhance RSS-based floor detection. The profile-based floor detection is further integrated withthe barometer data to gain more reliable estimations of the height and the barometer bias. Furthermore,the data from inertial sensors, magnetometers, and a barometer are integrated with the RSS data through anextend Kalman filter. The proposed multi-sensor integration algorithm provided more robust and smootherfloor detection and 3D localization solutions than the existing methods.