Skip to main navigation Skip to search Skip to main content

Trilateration Based on the Combination and K-Means Clustering

  • School of Information Science and Engineering, Harbin Institute of Technology Weihai

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

Abstract

Trilateration is a classic positioning algorithm that uses the coordinates of three reference nodes to obtain the coordinate of an unknown node. It is widely used in various positioning algorithms because of its simple principle and low computational complexity. But when the three circles do not intersect at one point, a significant positioning error may occur. This paper proposes a new trilateration positioning algorithm based on the combination and K-Means clustering. The proposed algorithm can make full use of the position information and distance information of the reference nodes in the area. It can effectively remove the points with significant errors through K-Means clustering. Simulation experiments prove that this method can effectively improve the accuracy of positioning.

Original languageEnglish
Title of host publication2021 Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021
EditorsWei Guo, Steven Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665401302
DOIs
StatePublished - 2021
Externally publishedYes
Event12th IEEE Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021 - Nanjing, China
Duration: 15 Oct 202117 Oct 2021

Publication series

Name2021 Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021

Conference

Conference12th IEEE Global Reliability and Prognostics and Health Management, PHM-Nanjing 2021
Country/TerritoryChina
CityNanjing
Period15/10/2117/10/21

Keywords

  • Algorithm
  • K-Means
  • Localization
  • RSSI
  • Trilateration
  • WNS

Fingerprint

Dive into the research topics of 'Trilateration Based on the Combination and K-Means Clustering'. Together they form a unique fingerprint.

Cite this