FDI and Navigation integration algorithm design for skew redundant strapdown inertial measurement unit

Skew Redundant Inertial Measurement Unit (SRIMU) is used to ensure that flight vehicle can achieve high reliability and accuracy. There are two essential discussions for SRIMU, one is Fault Detection and Isolation (FDI), and the other is how to get more accurate navigation parameters. Currently, two parts are investigated separately. This paper presents a FDI and navigation algorithm for SRIMU in an integrated solution framework. Considering various error sources, a more precise output model is established firstly. Unitary transformation is applied to project redundant information into data estimation space and null space for fault monitor. Kalman filter is used not only to compensate stochastic error for inertial sensors, but also in GNSS / INS integrated navigation system. Simulation is performed to show the performance of the suggested method. It is proofed that proposed frame has a sensitive capability of fault detection and high accuracy of the navigation solution.