par S. M. Monfared, Shaghayegh ;Delépaut, Anaïs ULB;Van Eeckhaute, Mathieu ;De Doncker, Philippe ;Horlin, François
Référence (28 April-01 May, 2019: Kuala Lumpur, Malaysia), Proc. of the IEEE 89th Vehicular Technology Conference, VTC-Spring
Publication Publié, 2019-05
Publication dans des actes
Résumé : Internet of Things (IoT) integrates numerous technologies to obtain the location information of the sensors in various ways. The most common localization methods are based on measuring a location dependent parameter such as Received Signal Strength (RSS) or Angle of Arrival (AoA). Then the measured parameters are used to estimate the sensor location by using a multilateration algorithm. AoA estimation can provide good localization accuracy for narrowband array-based systems. The research has drawn considerable attention in the literature and numerous methods have been proposed to improve the localization accuracy. The two-step method suffers from information loss from the received signals when the estimation of the parameters is communicated to the multilateration step. In this paper, we propose a new localization algorithm which iterates between AoA estimation and multilateration steps to refine the position estimate. We develop a localization scenario for the assessment and validation of the algorithm in Bluetooth Low Energy (BLE) sensor networks. Simulation results show that the proposed solution achieves a better localization accuracy when compared to the common two-step and achieving this after only a few iterations. Additionally, our method comes very close to the performance of the position estimation relying directly on the received signal, known as Direct Position Estimation (DPE), while reducing its complexity.