Fault detection combining interacting multiple model and multiple solution separation for aviation satellite navigation system

In civil aviation applications, satellite failures yield unacceptable positioning errors when using the Global Positioning System (GPS). To ensure the user security, the navigation system has to fulfill stringent performance requirements. Thus, detecting and excluding the faulty GPS measurements is necessary prior to estimating the mobile location. Classical fault detection algorithms based on Kalman filters (KF) are sensitive to the choice of an appropriate motion model for the mobile. To overcome this difficulty, we propose in this paper a new fault detection algorithm wherein the KF are replaced by multiple model algorithms. In this way, both the false alarm rate and the position mean square error are shown to be decreased.