This paper deals with the error analysis of the Schmidt—Kalman filter message and observation models.which contain uncertain parameters. The error quantity considered is the actual covariance which is the mean square of the difference between the nominal state and the misidentified estimate. After deriving the Schmidt—Kalman filter, the error analysis is considered due to two causes, one of which is misidentifying the coefficients of the system, the covariances of the noises and the variance of the initial state and the other of which is simplifying the coloured measurement noise by the white measurement noise. A boundedness theorem of the error equation is considered in the remaining part. Only systems governed by continuous-time linear equations are treated here.