Consensus-based distributed linear filtering

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 provide 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. We continue with presenting a connection between the consensusbased distributed linear filter and the optimal linear filter of a Markovian jump linear system, appropriately defined. More specifically, we show th...

• Type: Journal
• Year: 2010
• Where: CDC
• Authors: Ion Matei, John S. Baras
• Keywords: CDC 2010, Control Systems, Linear, Linear Filter, Markovian Jump Linear