Title :
Bayesian node localisation in wireless sensor networks
Author :
Morelande, Mark R. ; Moran, Bill ; Brazil, Marcus
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Melbourne, VIC
fDate :
March 31 2008-April 4 2008
Abstract :
Node localisation in wireless sensor networks is a difficult problem due to the large number of parameters to be estimated and the nonlinear relationship between the measurements and the parameters. Assuming the presence of a number of anchor nodes with known positions and a centralised architecture, a Bayesian algorithm for node localisation in wireless sensor networks is proposed. The algorithm is a refinement of an existing importance sampling method referred to as progressive correction. A simulation analysis shows that, with only a few anchor nodes, the proposed method is capable of accurately localising a large number of nodes.
Keywords :
Bayes methods; importance sampling; parameter estimation; wireless sensor networks; Bayesian node localisation; importance sampling method; parameter estimation; wireless sensor networks; Analytical models; Bayesian methods; Costs; Electric variables measurement; Global Positioning System; Intelligent networks; Monte Carlo methods; Noise measurement; Parameter estimation; Wireless sensor networks; Bayes procedures; Localisation; Sensor networks;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4518167