Robust state and protection-level estimation within tightly coupled GNSS/INS navigation system

TL;DR

This paper introduces a robust GNSS/INS navigation system using an extended H_infinity filter and zonotope-based protection levels, improving accuracy and robustness in urban environments with signal disturbances.

Contribution

It presents a novel combination of an extended H_infinity filter and zonotope-based protection levels for tightly coupled GNSS/INS navigation, enhancing robustness and real-time feasibility.

Findings

EHF outperforms extended Kalman filter in accuracy and robustness

Zonotope-based protection levels are valid and computationally efficient

System demonstrates improved performance in urban environments

Abstract

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.