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.
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.