Distributed Weighted Least Squares Estimator Without Prior Distribution Knowledge

Shun Liu, Zhifei Li, Weifang Zhang, Yan Liang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper concerns with a distributed state estimation problem, where all sensor nodes are required to achieve a consensus estimation. The weighted least squares (WLS) estimator is a promising way to tackle this problem since it does not need the prior distribution knowledge with respect to the estimated quantity and noise terms. To this end, the equivalent relation between the information filter and the WLS estimator is explored first. Following this, an optimization problem coupled with a consensus constraint is established. Finally, the consensus-based distributed WLS problem is handled by the alternating direction method of multiplier. The convergence and consensus estimations between nodes are tested by numerical simulations and theoretical analyses.

Original languageEnglish
Title of host publication2021 International Wireless Communications and Mobile Computing, IWCMC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1673-1678
Number of pages6
ISBN (Electronic)9781728186160
DOIs
StatePublished - 2021
Event17th IEEE International Wireless Communications and Mobile Computing, IWCMC 2021 - Virtual, Online, China
Duration: 28 Jun 20212 Jul 2021

Publication series

Name2021 International Wireless Communications and Mobile Computing, IWCMC 2021

Conference

Conference17th IEEE International Wireless Communications and Mobile Computing, IWCMC 2021
Country/TerritoryChina
CityVirtual, Online
Period28/06/212/07/21

Keywords

  • Alternating direction method of multipliers
  • Consensus estimation
  • Distributed
  • Weighted least squares

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