A new failure detection approach and its application to GPS autonomous integrity monitoring

This investigation presents a new approach for detecting failures which affect only subsets of system measurements. In addition to a main Kalman filter, which processes all the measurements to give the optimal state estimate, a bank of auxiliary Kalman filters is also used, which process subsets of the measurements to provide the state estimates which serve as failure detection references. After the statistical property of the differences between the state estimate of the main Kalman filter and those of the auxiliaries is derived with an application of the orthogonal projection theory, failure detection is undertaken by checking the consistency between the state estimate of the main Kalman filter and those of the auxiliaries by means of the chi-square statistical hypothesis test. The effectiveness of the proposed procedure is illustrated in a problem of GPS (Global Positioning System) autonomous integrity monitoring for a GPS/SDINS (Strapdown Inertial Navigation System) integrated navigation system.<>