An approach for distributed Kalman filtering

In this article we propose a parallel and distributed state estimation structure developed from an hierarchical estimation structure, optimal in the sense of Kalman filtering and that is based on the multiple projections method. We explore a duality that exists between two state space representations, derived from the application of an approach based on the coupling and noise terms of the original system. The algebraic structure developed is suboptimal, due to the fact that it does not take into account the corrections of the state predictions based on the multiple innovations. This approach contributes to the design of distributed Kalman filtering algorithms.