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We designed a tightly-coupled integration between GNSS and inertial navigation systems (INS) where we modify the update step of a classical Extended Kalman Filter (EKF) to consider different robust estimators (such as M-estimators). We consider different faulty scenarios where the pseudoranges contain one or several non-modeled biases. The tightly-coupled GNSS/INS robust Kalman filter performance in the presence of biases is compared with the classical EKF and with a loosely-coupled Robust-GNSS/INS approach. The robust tightly-coupled version is able to minimize more efficiently the biases effect thanks to the direct redundancy of the inertial sensor within the robust estimator.
Michael Christoph Gastpar, Marco Bondaschi
Giancarlo Ferrari Trecate, Florian Dörfler, Jean-Sébastien Hubert Brouillon