Optimal fusion Kalman filter for systems with colored measurement noises

The optimality of the optimal fusion criterion in the linear minimum variance sense is further stated. Based on this optimal fusion criterion, an optimal fusion Kalman filter is presented for discrete time-varying linear stochastic control systems measured by multiple sensors with colored measurement noises, which is equivalent to an optimal fusion Kalman predictor for systems measured by multiple sensors with correlated noises. It has a two-layer fusion structure with a fault tolerant property. Further, it has higher precision than any local filter does. Compared with the centralized filter, it has better reliability and robustness. Applying it into a radar tracking system with three sensors shows its effectiveness.