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Kalman filter-based localization for Internet of Things LoRaWAN™ end points

Abstract : This paper addresses the problem of estimating the location of Internet of Things (IoT) Long Range Wide Area Networks (LoRaWAN) devices from time of arrival differences measured at gateways. An Extended Kalman Filter (EKF) based approach is considered to aggregate the measurements obtained at different time instants. Particular attention is paid to the processing of outliers. Based on experimental data obtained from field measurements conducted on a real LoRaWAN™ network an insight into the realistic localization accuracy of the considered localization approach is provided.
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https://hal.archives-ouvertes.fr/hal-01734856
Contributor : Wafae Bakkali <>
Submitted on : Thursday, March 15, 2018 - 10:30:01 AM
Last modification on : Wednesday, April 8, 2020 - 3:44:37 PM

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Wafae Bakkali, Michel Kieffer, Massinissa Lalam, Thierry Lestable. Kalman filter-based localization for Internet of Things LoRaWAN™ end points. 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Oct 2017, Montréal, Canada. ⟨10.1109/PIMRC.2017.8292242⟩. ⟨hal-01734856⟩

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