Correlation Analysis for Fault Detection Statistics in Integrated GNSS/INS Systems

Global Satellite Navigation Systems (GNSS) have been widely used for positioning, navigation and timing (PNT). Therefore, the integrity of the satellite based navigation systems has been a major concern for many liability critical applications, such as civil aviation, and location-based services (LBS). Over the past two decades, GNSS Receiver Autonomous Integrity Monitoring (RAIM) procedures have been developed, but the efficiency of such procedures is highly dependent on measurement redundancy and geometric strength within the GNSS positioning solutions. Reliability of a PNT system can be measured by, not only the wellknown Minimal Detectable Biases (MDBs), but also the recently derived Minimal Separable Biases (MSBs) for the measurements. While the previous research has shown that the MSBs are directly related to the correlations between the faulty measurement detection statistics, a comprehensive analysis for such correlations between fault (or outlier) detection statistics is still lacking, even for commonly used GNSS/INS integration scenarios. In this research, we have demonstrated that with the aid of inertial sensors, even with low-cost MEMS sensors, the MDBs and correlation coefficients between the measurement fault detection statistics can be significantly reduced, thus improving the separability of faults in GNSS measurements.