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MDS-based Optimized Four-point Co-localization Algorithm for Clusters

  • Ruifeng Dai
  • , Yong Xu*
  • , Hao Wang*
  • , Hanhao Xing
  • *Corresponding author for this work
  • Beihang University

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

Abstract

In recent years, the demand for multi-node collaboration is increasing, and the relative localization of nodes within a cluster is crucial for network cooperation. This paper investigates relative localization algorithms based on multidimensional scaling (MDS), analyzes the limitations of classical MDS localization algorithms, and proposes an optimized four-point cooperative localization combined with MDS localization algorithm (MDS-OFP). The algorithm solves the problem of low accuracy of the classical MDS localization algorithm when the distance is missing and reduces the application of redundant nodes. An iterative method is used to improve the positioning accuracy. In addition, absolute localization is achieved by the least squares coordinate matching strategy. The localization is more accurate than the existing MDS-related algorithms.

Original languageEnglish
Title of host publication2023 6th International Conference on Information Communication and Signal Processing, ICICSP 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages735-740
Number of pages6
ISBN (Electronic)9798350339994
DOIs
StatePublished - 2023
Event6th International Conference on Information Communication and Signal Processing, ICICSP 2023 - Xi'an, China
Duration: 23 Sep 202325 Sep 2023

Publication series

Name2023 6th International Conference on Information Communication and Signal Processing, ICICSP 2023

Conference

Conference6th International Conference on Information Communication and Signal Processing, ICICSP 2023
Country/TerritoryChina
CityXi'an
Period23/09/2325/09/23

Keywords

  • cluster
  • localization
  • multidimensional scaling (MDS)
  • optimized four-point localization

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