Multi-sensor information fusion suboptimal Kalman filter for time-delay systems

Based on the optimal weighted fusion estimation algorithm in the linear minimum variance sense, a distributed weighted fusion optimal Kalman filter is given for discrete linear time-delay stochastic systems with multiple sensors by using the state augmented approach, which requires the high-dimension computation. To reduce the computational burden, a distributed weighted fusion suboptimal Kalman filter is given. It avoids the high-dimension computation by state augmentation, and has the reduced computation and is convenient to apply in real time. A simulation example shows its effectiveness.