Fast SCI fusion steady-state Kalman filters for multiple time-delayed systems with colored measurement noises

This paper is concerned with the fusion estimation problem for multi-sensor discrete time-invariant linear systems with multiple time delays and colored measurement noise. A fast sequential covariance intersection (SCI) fusion Kalman filter is given based on the augmented Kalman filter in the linear minimum variance sense, which avoids the calculation of the cross covariance matrices between local sensors. It is proved that the presented fused steady-state Kalman filter has higher accuracy than those local filters. The simulation result reveals that the actual accuracy of the SCI fusion steady-state Kalman filter approximates to the SCI fused optimal Kalman filter, and based on the covariance ellipse, the geometric interpretation with respect to accuracy relation of the local and the fused Kalman filter is shown.