@article {
	title = {Consensus-Based Linear Distributed Filtering},
	author = {Matei, Ion., Baras, John S.},
	year = {2012},
	month = {08/2012},
	abstract = {We address the consensus-based distributed linear filtering problem, where a discrete time, linear stochastic process is observed by a network of sensors. We assume that the consensus weights are known and we first provide sufficient conditions under which the stochastic process is detectable, i.e. for a specific choice of consensus weights there exists a set of filtering gains such that the dynamics of the estimation errors (without noise) is asymptotically stable. Next, we develop a distributed, sub-optimal filtering scheme based on minimizing an upper bound on a quadratic filtering cost. In the stationary case, we provide sufficient conditions under which this scheme converges; conditions expressed in terms of the convergence properties of a set of coupled Riccati equations.},
	pages = {Pages 1776-1782},
	volume = {Volume 48},
	number = {Issue 8},
	journal = {Automatica}
}
