Experimental Study on Probabilistic ToA and AoA Joint Localization in Real Indoor Environments

In this paper, we study probabilistic time-of-arrival (ToA) and angle-of-arrival (AoA) joint localization in real indoor environments. To mitigate the effects of multipath propagation, the joint localization algorithm incorporates into the likelihood function Gaussian mixture models (GMM) and the Vo...

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Veröffentlicht in:IEEE International Conference on Communications (2003) S. 1 - 6
Hauptverfasser: Geng, Chunhua, Abrudan, Traian E., Kolmonen, Veli-Matti, Huang, Howard
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.06.2021
Schlagworte:
angle-of-arrival (AoA)
field tests
Indoor positioning
Location awareness
Measurement uncertainty
Meters
multipath propagation
probabilistic localization
Probabilistic logic
Production facilities
prototype
Prototypes
time-of-arrival (ToA)
Uncertainty
ISSN:1938-1883
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Zusammenfassung:In this paper, we study probabilistic time-of-arrival (ToA) and angle-of-arrival (AoA) joint localization in real indoor environments. To mitigate the effects of multipath propagation, the joint localization algorithm incorporates into the likelihood function Gaussian mixture models (GMM) and the Von Mises-Fisher distribution to model time bias errors and angular uncertainty, respectively. We evaluate the algorithm performance using a proprietary prototype deployed in an indoor factory environment with infrastructure receivers in each of the four corners at the ceiling of a 10 meter by 20 meter section. The field test results show that our joint probabilistic localization algorithm significantly outperforms baselines using only ToA or AoA measurements and achieves 2-D sub-meter accuracy at the 90%-ile. We also numerically demonstrate that the joint localization algorithm is more robust to synchronization errors than the baseline using ToA measurements only.
ISSN:1938-1883
DOI:10.1109/ICC42927.2021.9500283