Document Detail


Error estimation for the linearized auto-localization algorithm.
MedLine Citation:
PMID:  22736965     Owner:  NLM     Status:  PubMed-not-MEDLINE    
Abstract/OtherAbstract:
The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs), using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons' positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL), the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.
Authors:
Jorge Guevara; Antonio R Jiménez; Jose Carlos Prieto; Fernando Seco
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2012-02-24
Journal Detail:
Title:  Sensors (Basel, Switzerland)     Volume:  12     ISSN:  1424-8220     ISO Abbreviation:  Sensors (Basel)     Publication Date:  2012  
Date Detail:
Created Date:  2012-06-27     Completed Date:  2012-10-30     Revised Date:  2013-05-30    
Medline Journal Info:
Nlm Unique ID:  101204366     Medline TA:  Sensors (Basel)     Country:  Switzerland    
Other Details:
Languages:  eng     Pagination:  2561-81     Citation Subset:  -    
Affiliation:
Centro de Automática y Robótica (CAR), Consejo Superior de Investigaciones Científicas (CSIC)-UPM, Madrid, Spain. jorge.guevara@csic.es
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