Globally optimal real-time distributed fusion of multi-channel observation systems

A globally optimal real-time distributed fusion algorithm is discussed for multi-channel observation systems. The performance of the fusion is equal to that of centralised Kalman filtering. Different from the existing one based on information filters, the algorithm uses the projection theorem in Hilbert space according to First-Come-First-Serve principle. Local estimates are instantly fused with arrival of local information at fusion centre. Meantime, a real-time strategy is presented to balance the performance and the speed of fusion. Therefore the algorithm is flexible and has the practical benefits.