Generalized covariance intersection based on noise decomposition

Marc Reinhardt, Sanjeev Kulkarni, Uwe D. Hanebeck

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

In linear decentralized estimation, several nodes concurrently aim to estimate the state of a common phenomenon by means of local measurements and data exchanges. In this contribution, an efficient algorithm for consistent estimation of linear systems in sensor networks is derived. The main theorems generalize Covariance Intersection by means of an explicit consideration of individual noise terms. We apply the results to linear decentralized estimation and obtain covariance bounds with a scalable precision between the exact covariances and the bounds provided by Covariance Intersection.

Original languageEnglish (US)
Title of host publicationProcessing of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479967322
DOIs
StatePublished - Dec 23 2014
Event2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014 - Beijing, China
Duration: Sep 28 2014Sep 30 2014

Publication series

NameProcessing of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014

Other

Other2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014
CountryChina
CityBeijing
Period9/28/149/30/14

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Control and Systems Engineering
  • Computer Networks and Communications

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    Reinhardt, M., Kulkarni, S., & Hanebeck, U. D. (2014). Generalized covariance intersection based on noise decomposition. In Processing of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014 [6997718] (Processing of 2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems, MFI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MFI.2014.6997718