Maximum Likelihood Localization Algorithm Using Wireless Sensor Networks

This paper proposes the use of a wireless sensor network for estimating the location of a source that releases certain substance in the environment which is then propagated over a large area. We use maximum likelihood localization algorithm (MLE) based on the concentration readings at the sensor nodes. Also, we firstly use the direct triangulation algorithm to estimate the plume source location. The effect of the estimation error, with different sensor number and different back ground noise, is researched by simulations. The direct triangulation algorithm is simple and intuitionistic; the MLE algorithm is robust to the much noise compared to the direct triangulation algorithm. The simulation results show the performance of the two algorithms that we can get accurate position of the contaminant source using the two algorithms if the sensor nodes reach to appropriate numbers in the field

[1]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[2]  William M. Spears,et al.  Distributed robotics approach to chemical plume tracing , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  M.P. Michaelides,et al.  Plume Source Position Estimation Using Sensor Networks , 2005, Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation Intelligent Control, 2005..

[4]  Yu Hen Hu,et al.  Maximum likelihood multiple-source localization using acoustic energy measurements with wireless sensor networks , 2005, IEEE Transactions on Signal Processing.

[5]  Tarek F. Abdelzaher,et al.  Range-free localization schemes for large scale sensor networks , 2003, MobiCom '03.