indoor localisation
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2021 ◽  
Author(s):  
Francesco Potorti ◽  
Antonino Crivello ◽  
Filippo Palumbo ◽  
Michele Girolami ◽  
Paolo Barsocchi
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Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7020
Author(s):  
Carlos S. Álvarez-Merino ◽  
Hao Qiang Luo-Chen ◽  
Emil Jatib Khatib ◽  
Raquel Barco

High-precision indoor localisation is becoming a necessity with novel location-based services that are emerging around 5G. The deployment of high-precision indoor location technologies is usually costly due to the high density of reference points. In this work, we propose the opportunistic fusion of several different technologies, such as ultra-wide band (UWB) and Wi-Fi fine-time measurement (FTM), in order to improve the performance of location. We also propose the use of fusion with cellular networks, such as LTE, to complement these technologies where the number of reference points is under-determined, increasing the availability of the location service. Maximum likelihood estimation (MLE) is presented to weight the different reference points to eliminate outliers, and several searching methods are presented and evaluated for the localisation algorithm. An experimental setup is used to validate the presented system, using UWB and Wi-Fi FTM due to their incorporation in the latest flagship smartphones. It is shown that the use of multi-technology fusion in trilateration algorithm remarkably optimises the precise coverage area. In addition, it reduces the positioning error by over-determining the positioning problem. This technique reduces the costs of any network deployment oriented to location services, since a reduced number of reference points from each technology is required.


2021 ◽  
pp. 114906
Author(s):  
Noelia Hernández ◽  
Ignacio Parra ◽  
Héctor Corrales ◽  
Rubén Izquierdo ◽  
Augusto Luis Ballardini ◽  
...  
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2021 ◽  
pp. 75-89
Author(s):  
Iuliana Marin ◽  
Arthur-Jozsef Molnar

Author(s):  
Bo Wei ◽  
Weitao Xu ◽  
Chengwen Luo ◽  
Guillaume Zoppi ◽  
Dong Ma ◽  
...  

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