Generalized Rayleigh quotient based sensor/actuator fault detection

A new approach based on the generalized Rayleigh quotient for testing the innovation covariance of the Kalman filter is proposed. The optimization process of testing quality is reduced to the classical problem of maximization of the generalized Rayleigh quotient. The proposed fault detection algorithm is reduced to the comparison of the generalized Rayleigh quotient, which is calculated using representative sample and found quotient's bounds, and making a decision on the basis of the presented decision rule. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model are considered, and the detection procedure of sensor/actuator faults, which affect the innovation covariance, is examined.