Title: Tightly Coupled GNSS/INS Integration based on Robust M-Estimators
Author(s): Omar Garcia Crespillo, Daniel Medina, Jan Skaloud, Michael Meurer
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 1554 - 1561
Cite this article: Crespillo, Omar Garcia, Medina, Daniel, Skaloud, Jan, Meurer, Michael, "Tightly Coupled GNSS/INS Integration based on Robust M-Estimators," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 1554-1561.
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Abstract: The combination of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS) has become the baseline of many vehicular applications. However, in challenging GNSS scenarios, classical GNSS/INS integration estimators are very sensitive to multiple measurement faults (e.g., due to multipath). In this work, we design a tightly-coupled integration between GNSS and INS where we modify the update step of a classical Extended Kalman Filter (EKF) to consider more robust estimators, like M-estimators. We consider different faulty scenarios where the pseudoranges contain one or several non-modeled biases and ramps. The tightly-coupled GNSS/INS robust Kalman filter performance in the presence of faults 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 faults effect thanks to the direct redundancy of the inertial sensor within the robust estimator.