Robust Tightly Coupled GNSS/INS Estimation for Navigation in Challenging Scenarios
Omar García Crespillo, Daniel Medina, Anja Grosch, Jan Škaloud, Michael Meurer · elib (German Aerospace Center) · 2017
The combination of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS) has become the baseline of many transportation applications. 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 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. 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.