John S. Baras


Consensus-Based Linear Distributed Filtering

I. Matei and J.S. Baras

AutomaticaVolume 48, Issue 8Pages 1776-1782, August 2012

Full Text Paper (.Pdf)


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.

Key words: distributed filtering, consensus, sensor networks

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