Abstract:
We consider distributed estimation of a deterministic parameter vector using an ad hoc wireless sensor network. The estimators derived are obtained as solutions of constr...Show MoreMetadata
Abstract:
We consider distributed estimation of a deterministic parameter vector using an ad hoc wireless sensor network. The estimators derived are obtained as solutions of constrained convex optimization problems. Using the method of multipliers in conjunction with a block coordinate descent approach we demonstrate how the resultant algorithms can be decomposed into a set of simpler tasks suitable for distributed implementation. We show that these algorithms have guaranteed convergence to properly defined optimum estimators, and further exemplify their applicability to solving estimation problems where the signal model is completely or partially known at individual sensors. Through numerical experiments we illustrate that our algorithms outperform existing alternatives.
Published in: 2006 14th European Signal Processing Conference
Date of Conference: 04-08 September 2006
Date Added to IEEE Xplore: 30 March 2015
Print ISSN: 2219-5491
Conference Location: Florence, Italy