Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning
Indoor positioning systems have become a feasible solution for the current development of multiple location-based services and applications. They often consist of deploying a certain set of beacons in the environment to create a coverage volume, wherein some receivers, such as robots, drones or smar...
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| Format: | Article |
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MDPI AG
2021-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/15/6805 |
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| author | Khaoula Mannay Jesús Ureña Álvaro Hernández José M. Villadangos Mohsen Machhout Taoufik Aguili |
| author_facet | Khaoula Mannay Jesús Ureña Álvaro Hernández José M. Villadangos Mohsen Machhout Taoufik Aguili |
| author_sort | Khaoula Mannay |
| collection | DOAJ |
| description | Indoor positioning systems have become a feasible solution for the current development of multiple location-based services and applications. They often consist of deploying a certain set of beacons in the environment to create a coverage volume, wherein some receivers, such as robots, drones or smart devices, can move while estimating their own position. Their final accuracy and performance mainly depend on several factors: the workspace size and its nature, the technologies involved (Wi-Fi, ultrasound, light, RF), etc. This work evaluates a 3D ultrasonic local positioning system (3D-ULPS) based on three independent ULPSs installed at specific positions to cover almost all the workspace and position mobile ultrasonic receivers in the environment. Because the proposal deals with numerous ultrasonic emitters, it is possible to determine different time differences of arrival (TDOA) between them and the receiver. In that context, the selection of a suitable fusion method to merge all this information into a final position estimate is a key aspect of the proposal. A linear Kalman filter (LKF) and an adaptive Kalman filter (AKF) are proposed in that regard for a loosely coupled approach, where the positions obtained from each ULPS are merged together. On the other hand, as a tightly coupled method, an extended Kalman filter (EKF) is also applied to merge the raw measurements from all the ULPSs into a final position estimate. Simulations and experimental tests were carried out and validated both approaches, thus providing average errors in the centimetre range for the EKF version, in contrast to errors up to the meter range from the independent (not merged) ULPSs. |
| first_indexed | 2024-03-10T09:18:53Z |
| format | Article |
| id | doaj.art-7ac247c9e02c4867bc632dcd03b74360 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T09:18:53Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7ac247c9e02c4867bc632dcd03b743602023-11-22T05:19:51ZengMDPI AGApplied Sciences2076-34172021-07-011115680510.3390/app11156805Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor PositioningKhaoula Mannay0Jesús Ureña1Álvaro Hernández2José M. Villadangos3Mohsen Machhout4Taoufik Aguili5EμE Laboratory, Faculty of Sciences of Monastir, National Engineer School of Tunis, University of Tunis EI Manar, B.P. 37, Le Belvédère, Tunis 1002, TunisiaElectronics Department, University of Alcala, E-28805 Alcalá de Henares, SpainElectronics Department, University of Alcala, E-28805 Alcalá de Henares, SpainElectronics Department, University of Alcala, E-28805 Alcalá de Henares, SpainEμE Laboratory, Faculty of Sciences of Monastir, University of Monastir, Monastir 5019, TunisiaSysCom Laboratory, National Engineer School of Tunis, University of Tunis EI Manar, B.P. 37, Le Belvédère, Tunis 1002, TunisiaIndoor positioning systems have become a feasible solution for the current development of multiple location-based services and applications. They often consist of deploying a certain set of beacons in the environment to create a coverage volume, wherein some receivers, such as robots, drones or smart devices, can move while estimating their own position. Their final accuracy and performance mainly depend on several factors: the workspace size and its nature, the technologies involved (Wi-Fi, ultrasound, light, RF), etc. This work evaluates a 3D ultrasonic local positioning system (3D-ULPS) based on three independent ULPSs installed at specific positions to cover almost all the workspace and position mobile ultrasonic receivers in the environment. Because the proposal deals with numerous ultrasonic emitters, it is possible to determine different time differences of arrival (TDOA) between them and the receiver. In that context, the selection of a suitable fusion method to merge all this information into a final position estimate is a key aspect of the proposal. A linear Kalman filter (LKF) and an adaptive Kalman filter (AKF) are proposed in that regard for a loosely coupled approach, where the positions obtained from each ULPS are merged together. On the other hand, as a tightly coupled method, an extended Kalman filter (EKF) is also applied to merge the raw measurements from all the ULPSs into a final position estimate. Simulations and experimental tests were carried out and validated both approaches, thus providing average errors in the centimetre range for the EKF version, in contrast to errors up to the meter range from the independent (not merged) ULPSs.https://www.mdpi.com/2076-3417/11/15/68053D positioningultrasonic local positioning systemsloosely coupled fusiontightly coupled fusion |
| spellingShingle | Khaoula Mannay Jesús Ureña Álvaro Hernández José M. Villadangos Mohsen Machhout Taoufik Aguili Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning Applied Sciences 3D positioning ultrasonic local positioning systems loosely coupled fusion tightly coupled fusion |
| title | Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning |
| title_full | Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning |
| title_fullStr | Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning |
| title_full_unstemmed | Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning |
| title_short | Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning |
| title_sort | evaluation of multi sensor fusion methods for ultrasonic indoor positioning |
| topic | 3D positioning ultrasonic local positioning systems loosely coupled fusion tightly coupled fusion |
| url | https://www.mdpi.com/2076-3417/11/15/6805 |
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