Oliviero Vouch
Integration of navigation sensors based on advanced Bayesian estimation methods.
Rel. Fabio Dovis, Alex Minetto, Gianluca Falco. Politecnico di Torino, Corso di laurea magistrale in Communications And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni), 2021
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Abstract
Global Navigation Satellite Systems (GNSSs) represent the leading technology for radio-navigation and their use is widespread in the framework of outdoor localization. For some applications, the strict requirements in terms of accuracy cannot be complied with a standalone GNSS solution and it is worthwhile coupling the former technology with an Inertial Navigation System (INS). A INS/GNSS integrated navigation unit leverages the complementary characteristics of the two sensors in order to enhance the accuracy and robustness of the solution to the localization problem. Among the available hybridization approaches, a Tightly-Coupled (TC) architecture is implemented, where a centralized Bayesian estimator exploits the low-rate GNSS noisy measurements to correct the INS high-rate estimates.
The state-of-art INS/GNSS fusion routine is represented by the Extended Kalman Filter (EKF), where the integrated system models are handled in a linearized fashion
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