Title :
Source Localisation in Wireless Sensor Networks Based on Optimised Maximum Likelihood
Author :
Rahman, M. Ziaur ; Habibi, Daryoush ; Ahmad, Iftekhar
Author_Institution :
Sch. of Eng., Edith Cowan Univ., Joondalup, WA
Abstract :
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.
Keywords :
maximum likelihood estimation; wireless sensor networks; finite datasets; moving military vehicle tracking; optimised maximum likelihood; parameter perturbations; source localisation; statistical estimation; sum-of-squares bias; wireless sensor networks; Acoustic measurements; Acoustic propagation; Acoustic sensors; Antenna measurements; Maximum likelihood estimation; Microphone arrays; Position measurement; Sensor arrays; Time measurement; Wireless sensor networks; Maximum likelihood; estimation; source localisation; wireless sensor networks;
Conference_Titel :
Telecommunication Networks and Applications Conference, 2008. ATNAC 2008. Australasian
Conference_Location :
Adelaide, SA
Print_ISBN :
978-1-4244-2602-7
Electronic_ISBN :
978-1-4244-2603-4
DOI :
10.1109/ATNAC.2008.4783329