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In the paper, state filtration in a LQG problem formulated for a multisensor system is considered. Control is determined by a central node as a linear form of a state estimate. It is assumed that control values are not available to local nodes. Because of the drawbacks of centralized filtration an optimal fusion of decentralized local Kalman filters is proposed. When control values are not available to local nodes, then control should be treated as a random variable in the synthesis of local state estimates. This leads to a non-classical estimation. It is shown that the proposed filter is equivalent to the centralized one. [ABSTRACT FROM AUTHOR]

In the paper nonconventional linear equations of state filtration are derived. They are useful for some two-level hierarchical control system structure with coordinator and local controllers having different information. It is assumed that the system considered is described by a linear output equation and a linear state equation with control being a random variable for the coordinator generated by decision rules of the local controllers. The approach to state filtration is based on modified innovations and orthogonality principle. A simple numerical example is presented. [ABSTRACT FROM AUTHOR]