Print Email Facebook Twitter State fusion with unknown correlation: Ellipsoidal intersection Title State fusion with unknown correlation: Ellipsoidal intersection Author Sijs, J. Lazar, M. van den Bosch, P.P.J. TNO Industrie en Techniek Publication year 2010 Abstract Some crucial challenges of estimation over sensor networks are reaching consensus on the estimates of different systems in the network and separating the mutual information of two estimates from their exclusive information. Current fusion methods of two estimates tend to bypass the mutual information and directly optimize the fused estimate. Moreover, both the mean and covariance of the fused estimate are fully determined by optimizing the covariance only. In contrast to that, this paper proposes a novel fusion method in which the mutual information results in an additional estimate, which defines a mutual mean and covariance. Both variables are derived from the two initial estimates. The mutual covariance is used to optimize the fused covariance, while the mutual mean optimizes the fused mean. An example of decentralized state estimation, where the proposed fusion method is applied, shows a reduction in estimation error compared to the existing alternatives. © 2010 AACC. Subject Physics & ElectronicsDSS - Distributed Sensor SystemsTS - Technical SciencesElectronicsDecentralized state estimationState fusionDecentralized state estimationEstimation errorsFusion methodsInitial estimateMutual informationsState fusionOptimizationState estimationEstimation To reference this document use: http://resolver.tudelft.nl/uuid:a8b12fa6-8d4a-43cb-9a6d-967e91ba4bea TNO identifier 425176 ISBN 9781424474264 Source 2010 American Control Conference, ACC 2010, 30 June 2010 through 2 July 2010, Baltimore, MD, USA. Conference code: 81791, 3992-3997 Article number No.: 5531237 Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.