DocumentCode :
3524361
Title :
Multi-pass maximum likelihood technique for self localisation in wireless sensor networks
Author :
Bessell, Travis J. ; Rutten, Mark G.
Author_Institution :
ISR Div., Defence Sci. & Technol. Organ. (DSTO), Edinburgh, WA, Australia
fYear :
2009
fDate :
7-10 Dec. 2009
Firstpage :
157
Lastpage :
162
Abstract :
An accurate self-localisation capability is highly desirable in wireless sensor networks. This paper presents a multi-pass algorithm, based on maximum likelihood optimisation to estimate the locations of sensor nodes within a network using range based measurements. Flip ambiguities are a major problem in trilateration based localisation, which has the potential to introduce large errors in the location estimates. The notion of robust quadrilaterals has been incorporated with the multi-pass algorithm to identify these flip ambiguities and provide good starting positions for the optimisation. The Crame¿r-Rao Bound of the estimation error has been derived which is used to analyse the accuracy of the algorithm. By fusing two complementary range-based measurements it is observed that the multi-pass algorithm follows the calculated bound on simulated data. Experiments using real data from MICAz motes demonstrate that the algorithm can maintain this accuracy in a real environment.
Keywords :
maximum likelihood estimation; sensor placement; wireless sensor networks; Cramer-Rao Bound; estimation error; multi-pass maximum likelihood technique; self localisation; wireless sensor networks; Acoustic measurements; Australia; Estimation error; Global Positioning System; Hardware; Maximum likelihood estimation; Position measurement; Robustness; Sensor systems; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2009 5th International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4244-3517-3
Electronic_ISBN :
978-1-4244-3518-0
Type :
conf
DOI :
10.1109/ISSNIP.2009.5416801
Filename :
5416801
Link To Document :
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