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Deep Learning Methodologies for UWB Ranging Error Compensation.
Rel. Marcello Chiaberge. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2020
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Abstract
Ultra-Wideband (UWB) is being extensively introduced in various kinds of both human and robot positioning systems. From industrial robotic tasks to drones used for search and rescue operations, this high-accuracy technology allows to locate a target with an error of just a few centimeters, outperforming other existing low-cost ranging methods like Bluetooth and Wi-Fi. This led Apple to equip the latest IPhone 11 with an UWB module specifically for precise localization applications. Unfortunately, this technology is proved to be very accurate only in Line-Of-Sight (LOS). Indeed, performances degrade significantly in Non-Line-Of-Sight (NLOS) scenarios, where walls, furniture or people obstruct the direct path between the antennas.
Moreover, reflections constitute an additional source of error, causing the receiver to detect multiple signals with different delays
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