Document Type

Conference Proceeding


IEEE Press


Faculty of Computing, Health and Science


School of Engineering / Centre for Communications Engineering Research




This is an Author's Accepted Manuscript of: Rahman, M. Z., Habibi, D. , & Ahmad, I. (2008). Source Localisation in Wireless Sensor Networks Based on Optimised Maximum Likelihood. Proceedings of Australasian Telecommunication Networks and Applications Conference. ATNAC 2008. (pp. 235-239). Adelaide, Australia. IEEE Press. Available here

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Maximum likelihood (ML) is a popular and effective estimator for a wide range of diverse applications and currently affords the most accurate estimation for source localisation in wireless sensor networks (WSN). ML however has two major shortcomings namely, that it is a biased estimator and is also highly sensitive to parameter perturbations. An Optimisation to ML (OML) algorithm was introduced that minimises the sum-of-squares bias and exhibits superior performance to ML in statistical estimation, particularly with finite datasets. This paper proposes a new model for acoustic source localisation in WSN, based upon the OML estimation process. In addition to the performance analysis using real world field experimental data for the tracking of moving military vehicles, simulations have been performed upon the more complex source localisation and tracking problem, to verify the potential of the new OML-based model.



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