Distributed moving horizon estimation for linear constrained systems

This paper presents a novel distributed estimation
algorithm based on the concept of moving horizon estimation.
Under weak observability conditions we prove convergence of
the state estimates computed by any sensors to the correct state
even when constraints on noise and state variables are taken
into account in the estimation process. Simulation examples are
provided in order to show the main features of the proposed
method.