MA-MCL: Mobile-Assisted Monte Carlo Localization for Wireless Sensor Networks

As many Wireless Sensor Networks (WSNs) applications require sensor position information, localization has been an important problem in WSNs. To reduce the number of seeds, a number of mobile-assisted approaches have been proposed. Current proposed mobile-assisted approaches for localization require special hardware or face route selection problem, however. In this paper, we propose a Mobile-Assisted Monte Carlo Localization (MA-MCL) for WSNs. Our approach relies on direct arriver and leaver information from a single mobile-assisted seed. It does not require any specially designed hardware due to the range-free technique, and the single mobile-assisted seed in our approach can move uncontrollably to avoid route selection problem based on Monte Carlo method. Evaluation results show that the accuracy of MA-MCL outperforms MSL, MSL, and ADO when all of them use only a mobile seed for localization in the static sensor networks. © 2011 Guodong Teng et al.