  We propose a partition-based state estimator for linear discrete-time systems
composed by coupled subsystems affected by bounded disturbances. The
architecture is distributed in the sense that each subsystem is equipped with a
local state estimator that exploits suitable pieces of information from parent
subsystems. Moreover, differently from methods based on moving horizon
estimation, our approach does not require the on-line solution to optimization
problems. Our state-estimation scheme, that is based on the notion of practical
robust positive invariance developed in Rakovic 2011, also guarantees
satisfaction of constraints on local estimation errors and it can be updated
with a limited computational effort when subsystems are added or removed.
