Real-time Kalman filtering based on distributed measurements

A kind of real-time Kalman filtering problem is discussed for systems with distributed multichannel measurements. Recursive filters are presented for two cases with correlated and uncorrelated measurement noises. An optimal algorithm is constructed using projection theory in Hilbert space according to a first-come-first-served scheme. An update is generated whenever a new measurement arrives at a central unit. Therefore, the algorithm has the practical advantages of flexibility and the easiness for real-time implementation. Copyright (c) 2012 John Wiley & Sons, Ltd.