Kalman filter-based multialternative method for fault detection and estimation

Proposed was a computationally efficient multialternative method for detection and estimation of faults additively involved in the right-hand sides of the linear equations of the state and measurement vectors. In distinction to the classical approach using a Kalman filter bank for each fault, the paper suggested an extended Kalman filter estimating a set of possible faults. The a posteriori probabilities and estimates of individual faults were shown to be readily calculable from the estimates and covariance matrices generated by the extended Kalman filter. Efficiency of the method is corroborated by modeling of a navigation complex with two inertial systems.