  In autonomous applications for mobility and transport, a high-rate and highly
accurate vehicle-state estimation is achieved by fusing measurements of global
navigation satellite systems (GNSS) and inertial sensors. The state estimation
and its protection-level generation often suffer from satellite-signal
disturbances in urban environments and subsequent poor parametrization of the
satellite observables. Thus, we propose an innovative scheme involving an
extended H_infinity filter (EHF) for robust state estimation and zonotope for
the protection-level generation. This scheme is shown as part of a tightly
coupled navigation system based on an inertial navigation system and aided by
the GPS/Galileo dual-constellation satellite navigation system. Specifically,
GNSS pseudorange and deltarange observables are utilized. The experimental
results of post-processing a real-world dataset show significant advantages of
EHF against a conventional extended Kalman filter regarding the navigation
accuracy and robustness under various GNSS-measurement parametrizations and
environmental circumstances. The zonotope-based protection-level calculation is
proven valid, computationally affordable, and feasible for real-time
implementations.
