Towards a set-based detector for GNSS integrity monitoring
Jingyao Su, Steffen Schön, Mathieu Joerger · 2023
This paper aims to evaluate the performance of the set-based fault detection. This approach differs from probabilistic residual-based (RB) or solution separation (SS) fault detection and exclusion methods utilized in the Receiver Autonomous Integrity Monitoring (RAIM) and Advanced RAIM. In the basic positioning model, measurement-level intervals are constructed based on the investigated error models and propagated in a linear manner using interval mathematics and set theory. Convex polytope solutions provide a measure of observation consistency formulated as a constraint satisfaction problem. Consistency checks performed using set operations facilitate multiple-fault detection. Choosing set-emptiness as the detection criterion can alleviate the need for multiple test statistics. In this paper, we formulate the fault detection problem in the context of measurement intervals and propose a framework of integrity monitoring for the set-based detection. Considering a probabilistic error model, we implement the set-based detection methods and assess its integrity performance using Monte Carlo simulations. These evaluations will serve as a basis for further development of efficient estimators and integrity monitors.