Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning
| Autor: | Mohsen Machhout, Khaoula Mannay, Taoufik Aguili, Jesús Ureña, J.M. Villadangos, Alvaro Hernandez |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Technology
Computer science QH301-705.5 QC1-999 Real-time computing Local positioning system Context (language use) 02 engineering and technology Workspace Extended Kalman filter ultrasonic local positioning systems 0202 electrical engineering electronic engineering information engineering General Materials Science Biology (General) Instrumentation QD1-999 Fluid Flow and Transfer Processes 3D positioning Process Chemistry and Technology Physics 020208 electrical & electronic engineering General Engineering 020206 networking & telecommunications Kalman filter Multilateration Engineering (General). Civil engineering (General) Computer Science Applications Beacon Chemistry Ultrasonic sensor tightly coupled fusion TA1-2040 loosely coupled fusion |
| Zdroj: | Applied Sciences Volume 11 Issue 15 Applied Sciences, Vol 11, Iss 6805, p 6805 (2021) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app11156805 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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