iCCA-MAP versus MCL and dual MCL: comparison of mobile node localization algorithms

Authors:
Shafagh Alikhani;Thomas Kunz;Marc St-Hilaire
Affiliations:
Department of Systems and Computer Engineering, Carleton University, Canada;Department of Systems and Computer Engineering, Carleton University, Canada;Department of Systems and Computer Engineering, Carleton University, Canada
Venue:
ADHOC-NOW'10 Proceedings of the 9th international conference on Ad-hoc, mobile and wireless networks
Year:
2010

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Abstract

Accurately locating a moving node in a wireless sensor network, in real time, is a difficult yet essential process. In this paper, we compare the localization performance of different mobile node localization algorithms: iCCA-MAP, MCL, and Dual MCL. The localization errors as well as the effect of increasing the percentage of anchor nodes and varying the speed of the mobile node in the network are compared. iCCA-MAP applies an iterative and efficient nonlinear data mapping technique in order to localize the position of a mobile node within a wireless sensor network. MCL and Dual MCL, which is the logical inverse of MCL, use particle filtering combined with probabilistic models of robot perception and motion. Simulation results show that iCCA-MAP outperforms MCL and Dual MCL by having a lower localization error with the minimum number of anchor nodes required. Simulation results also show that varying the mobile node's speed does not impact the performance of iCCA-MAP, while MCL and Dual MCL's performance is impacted.