On Distributed Estimation for Sensor Networks
Distributed estimators for sensor networks are discussed. The considered problem is on how to track a noisy time-varying signal jointly with a network of sensor nodes. The authors present a recent scheme in which each node computes its estimate as a weighted sum of its own and its neighbors' measurements and estimates. The weights are adaptively updated to minimize the variance of the estimation error. Theoretical and practical properties of the algorithm are illustrated. The results provide a tool to trade-off communication constraints, computing efforts and estimation quality.