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Article

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Title

Incremental Localization Algorithm Based on Regularized Iteratively Reweighted Least Square

Authors

Year of publication

2016

Published in

Foundations of Computing and Decision Sciences

Journal year: 2016 | Journal volume: vol. 41 | Journal number: no. 3

Article type

scientific article

Publication language

english

Keywords
EN
  • wireless network
  • incremental localization
  • regularized iteratively reweighted least square
  • heteroscedasticity
Abstract

EN wireless network, incremental localization, regularized iteratively reweighted least square, heteroscedasticity Incremental localization algorithm is a distributed localization method with excellent characteristics for wireless network. However, its estimated result is generally influenced by the heteroscedasticity arising from cumulative errors and the collineation among anchor nodes. We have proposed a novel incremental localization algorithm with consideration to cumulative errors and collinearity among anchors. Using iteratively reweighted and regularized method, the algorithm reduces the influences of errors accumulation and avoids collinearity problem between anchors. Simulation experiment results show that compared with the previous incremental localization algorithms, the proposed algorithm obtains a localization solution which not only has high accuracy but also high stability. Therefore, the proposed algorithm is suitable for different deployment environments and has high adaptability.

Pages (from - to)

183 - 196

DOI

10.1515/fcds-2016-0011

URL

https://www.sciendo.com/article/10.1515/fcds-2016-0011

License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Full text of article

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Access level to full text

public

Ministry points / journal

15

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