  In this paper, we consider the distributed robust filtering problem, where
estimator design is based on a set of coupled linear matrix inequalities
(LMIs). We separate the problem and show that the method of multipliers can be
applied to obtain a solution efficiently and in a decentralized fashion, i.e.
all local estimators can compute their filter gains locally and iteratively,
with communications restricted to their neighbours. The convergence properties
of the iterative algorithm are analyzed and interpreted.
