Weighted self-localization algorithm of networked munitions

H. W. Liu, C. L. Jiang, M. Li, X. Y. Cheng

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

Abstract

Trilateration is one of the most commonly used methods in the Self-localization of Wireless Sensor Networks and Networked Munitions. In view of the feature that this algorithm is deeply affected by the relative positions of anchors and the ranging errors, which is unable to meet the demand of Networked Munitions, a new algorithm that is based on weight of localization-triangle and residual errors of distances is presented. This algorithm effectively reduces the negative effect on localization caused by relative positions of anchors and the inaccuracy of ranging. Simulation show that this algorithm has the advantages of better accuracy and robustness with lager errors of ranging when compared with the Maximum Likelihood Estimation. This algorithm also reduces communication overhead, meeting the requirement of low power consumption of wireless sensor networks.

Original languageEnglish
Title of host publicationControl Engineering and Information Systems - Proceedings of the International Conference on Control Engineering and Information System, ICCEIS 2014
EditorsZhijing Liu
PublisherCRC Press/Balkema
Pages477-481
Number of pages5
ISBN (Print)9781138026858
Publication statusPublished - 2015
EventInternational Conference on Control Engineering and Information System, ICCEIS 2014 - Yueyang, China
Duration: 20 Jun 201422 Jun 2014

Publication series

NameControl Engineering and Information Systems - Proceedings of the International Conference on Control Engineering and Information System, ICCEIS 2014

Conference

ConferenceInternational Conference on Control Engineering and Information System, ICCEIS 2014
Country/TerritoryChina
CityYueyang
Period20/06/1422/06/14

Fingerprint

Dive into the research topics of 'Weighted self-localization algorithm of networked munitions'. Together they form a unique fingerprint.

Cite this