Hellmers, Hendrik ; Norrdine, Abdelmoumen ; Blankenbach, Jörg ; Eichhorn, Andreas (2013)
An IMU/magnetometer-based Indoor positioning system using Kalman filtering.
2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN). Montbéliard, France (28-31.10.2013)
doi: 10.1109/IPIN.2013.6817887
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Many infrastructure-based indoor positioning technologies such as UWB, WLAN, ultrasonic or infrared are limited by disturbances and errors caused by building objects (e.g. walls, ceiling and furniture). Magnetic fields, however, are able to penetrate various obstacles - in this case commonly used (building) materials - without attenuation, fading, multipath or signal delay. Thus, in the past years a DC Magnetic signal based Indoor Local Positioning System (MILPS), which consists of multiple electrical coils as reference stations and tri-axial magnetic sensors as mobile stations was developed. By observing magnetic field intensities of at least three different magnetic coils, position estimation of the magnetic sensors can be carried out even in severe indoor environments. However, the positioning algorithm currently used is designed for stop-and-go localization. This contribution focuses on the integration of a low cost Inertial Measurement Unit (IMU) in order to improve the system's positioning update rate and therefore provide complete 2D localization estimates for kinematic applications and probably afford position solutions even outside the coverage area of MILPS. Therefore an Extended Kalman-Filter (EKF) is adapted for position estimation. The filtering process is accomplished in two steps. The first step leads to position prediction caused by inertial data, which could be updated at the second step by using the MILPS-measurements. In this context simulations combining MILPS and IMU have been performed. Testing of the filter with real IMU-data and simulated MILPS positioning data delivered promising results for indoor positioning purposes.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2013 |
| Autor(en): | Hellmers, Hendrik ; Norrdine, Abdelmoumen ; Blankenbach, Jörg ; Eichhorn, Andreas |
| Art des Eintrags: | Bibliographie |
| Titel: | An IMU/magnetometer-based Indoor positioning system using Kalman filtering |
| Sprache: | Englisch |
| Publikationsjahr: | Oktober 2013 |
| Ort: | Montbéliard, France |
| Veranstaltungstitel: | 2013 International Conference on Indoor Positioning and Indoor Navigation (IPIN) |
| Veranstaltungsort: | Montbéliard, France |
| Veranstaltungsdatum: | 28-31.10.2013 |
| DOI: | 10.1109/IPIN.2013.6817887 |
| URL / URN: | http://ieeexplore.ieee.org/document/6817887/ |
| Kurzbeschreibung (Abstract): | Many infrastructure-based indoor positioning technologies such as UWB, WLAN, ultrasonic or infrared are limited by disturbances and errors caused by building objects (e.g. walls, ceiling and furniture). Magnetic fields, however, are able to penetrate various obstacles - in this case commonly used (building) materials - without attenuation, fading, multipath or signal delay. Thus, in the past years a DC Magnetic signal based Indoor Local Positioning System (MILPS), which consists of multiple electrical coils as reference stations and tri-axial magnetic sensors as mobile stations was developed. By observing magnetic field intensities of at least three different magnetic coils, position estimation of the magnetic sensors can be carried out even in severe indoor environments. However, the positioning algorithm currently used is designed for stop-and-go localization. This contribution focuses on the integration of a low cost Inertial Measurement Unit (IMU) in order to improve the system's positioning update rate and therefore provide complete 2D localization estimates for kinematic applications and probably afford position solutions even outside the coverage area of MILPS. Therefore an Extended Kalman-Filter (EKF) is adapted for position estimation. The filtering process is accomplished in two steps. The first step leads to position prediction caused by inertial data, which could be updated at the second step by using the MILPS-measurements. In this context simulations combining MILPS and IMU have been performed. Testing of the filter with real IMU-data and simulated MILPS positioning data delivered promising results for indoor positioning purposes. |
| Freie Schlagworte: | 2D localization estimation, dc magnetic signal based indoor local positioning system, EKF, extended Kalman-filter, Global Positioning System, IMU, Indoor-Positioning, inertial measurement unit, Inertial Navigation, infrared, infrastructure-based indoor positioning technologies, Kalm, Kalman filters, kinematic applications, magnetic coils, magnetic field intensities, Magnetic field measurement, magnetic fields, magnetic sensors, Magnetic separation, magnetometer, magnetometers, mobile stations, multiple electrical coils, nonlinear filters, positioning update rate, probably afford position solutions, reference stations, Robots, simulated MILPS positioning data, stop-and-go localization, Trajectory, tri-axial magnetic sensors, ultrasonic, UWB, WLAN |
| Zusätzliche Informationen: | Peer Reviewed |
| Fachbereich(e)/-gebiet(e): | 13 Fachbereich Bau- und Umweltingenieurwissenschaften 13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Geodäsie 13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Geodäsie > Geodetic Measuring Systems and Sensor Technology 13 Fachbereich Bau- und Umweltingenieurwissenschaften > Institut für Baubetrieb |
| Hinterlegungsdatum: | 31 Okt 2016 07:38 |
| Letzte Änderung: | 07 Jan 2021 19:30 |
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