Evaluation of Multi-Sensor Fusion Methods for Ultrasonic Indoor Positioning

被引:10
|
作者
Mannay, Khaoula [1 ,2 ]
Urena, Jesus [2 ]
Hernandez, Alvaro [2 ]
Villadangos, Jose M. [2 ]
Machhout, Mohsen [3 ]
Aguili, Taoufik [4 ]
机构
[1] Univ Tunis EI Manar, Fac Sci Monastir, Natl Engineer Sch Tunis, E E Lab, BP 37, Tunis 1002, Tunisia
[2] Univ Alcala, Elect Dept, E-28805 Alcala De Henares, Spain
[3] Univ Monastir, Fac Sci Monastir, E E Lab, Monastir 5019, Tunisia
[4] Univ Tunis EI Manar, Natl Engineer Sch Tunis, SysCom Lab, BP 37, Tunis 1002, Tunisia
来源
APPLIED SCIENCES-BASEL | 2021年 / 11卷 / 15期
关键词
3D positioning; ultrasonic local positioning systems; loosely coupled fusion; tightly coupled fusion; KALMAN-FILTER;
D O I
10.3390/app11156805
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页数:24
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