Optimal fault detection in linear stochastic systems with nuisance parameters

Abstract The goal of this paper is to propose an optimal statistical tool to detect a fault in a linear stochastic (dynamical) system with uncertainties (nuisance parameters). It is supposed that the nuisance parameters are unknown but non random; practically, this means that the nuisance can be intentionally chosen to maximize its negative impact on the monitored system (for instance, to mask a fault). An example of GPS integrity monitoring illustrates the proposed method.