Self-localization in wireless sensor networks using particle filtering with progressive correction
Files
(Published version)
Date
2010
Authors
Hanselmann, T.
Zhang, Y.
Morelande, M.
Nor, M.I.M.
Tan, J.W.J.
Zhou, X.
Law, Y.W.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
International ICST Conference on Communications and Networking in China, ChinaCom 2010, 2010, iss.5684653, pp.1-6
Statement of Responsibility
Conference Name
2010 5th International ICST Conference on Communications and Networking in China (25 Aug 2010 - 27 Aug 2010 : Beijing, China)
Abstract
A centralized self-localization algorithm is used to estimate sensor locations. From the known positions of at least 3 anchor nodes the remaining sensor positions are estimated using an efficient particle filter (PF) with progressive correction. The measurement model is a simple two-parameter log-normal shadowing model, where the parameters are estimated concurrently. Experiments using Crossbow Imote2 motes show that an error of less than 16% is achievable in an indoor environment. The results demonstrate that by using PF with progressive correction, a small number of measurements and a simple signal propagation model are sufficient to give low localization errors.
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
Copyright 2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.