Measuring accurate Angle of Arrival of weak LoRa signals for Indoor Positionning
In: 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN) ; 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022) ; https://hal.science/hal-03932846 ; 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022), Sep 2022, Beijing, China. ⟨10.1109/IPIN54987.2022.9918114⟩ ; https://ipin-conference.org/2022/, 2022
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Zugriff:
International audience ; In this paper, we propose an Autocorrelation method for measuring the angle of arrival (AoA) of a weak LoRa signal. A weak LoRa signal has a negative SNR down to −20 dB. The objective is to detect a LoRa signal that operates at low transmission power (TX). Operating at low transmission power (TX) reduces power consumption and extends the battery life of LoRa devices. Besides, the transmission of weak signals strengthens the radio communication protocol, preventing an enemy device from accessing the location coordinates. The detecting algorithm consists of finding Autocorrelation peaks of the LoRa signal. We show that Autocorrelation peaks decrease when the signal is buried in the noise. However, using a large number of Fast Fourier Transform (FFT) will increase the Autocorrelation peaks and the signal-to-noise ratio (SNR). Once the peak of the LoRa signal is detected under the noise, the algorithm will calculate the AoA. All of the proposed algorithms are implemented using a Universal Software Radio Peripheral (USRP), Software Defined Radio (SDR) receiver with the help of GNU Radio software. We, therefore, believe that our Autocorrelation method can detect the LoRa signal accurately and measure the AoA at very low SNR in real_ time being usable for indoor positionning.
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Measuring accurate Angle of Arrival of weak LoRa signals for Indoor Positionning
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Autor/in / Beteiligte Person: | Zeaiter, Hussein ; Spies, François ; Baala, Oumaya ; Val, Thierry ; Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST) ; Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC) ; Université Bourgogne Franche-Comté COMUE (UBFC)-Université Bourgogne Franche-Comté COMUE (UBFC) ; Réseaux, Mobiles, Embarqués, Sans fil, Satellites (IRIT-RMESS) ; Institut de recherche en informatique de Toulouse (IRIT) ; Université Toulouse Capitole (UT Capitole) ; Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J) ; Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3) ; Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP) ; Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI) ; Université Toulouse - Jean Jaurès (UT2J) ; Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3) ; Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole) ; Université de Toulouse (UT) ; SYLOIN FEDER BPI Project |
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Zeitschrift: | 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN) ; 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022) ; https://hal.science/hal-03932846 ; 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2022), Sep 2022, Beijing, China. ⟨10.1109/IPIN54987.2022.9918114⟩ ; https://ipin-conference.org/2022/, 2022 |
Veröffentlichung: | HAL CCSD, 2022 |
Medientyp: | Konferenz |
ISBN: | 978-1-7281-6218-8 (print) ; 1-7281-6218-1 (print) |
DOI: | 10.1109/IPIN54987.2022.9918114 |
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