RSS-based Monte Carlo nodes Localization in wireless ad hoc networks

The availability of wireless devices and their increasing ability of sharing information has stimulated the emergence of the wireless ad hoc networks. Localization is a fundamental problem that needs to be solved with the best possible accuracy and efficiency. This paper proposes an RSS-based Monte Carlo localization scheme to sequentially estimate the location of mobile nodes, using the log-normal statistical model of RSS measurement. We treat the RSS measurement as the observation model in Monte Carlo method and the mobility feature of nodes as the transition model. Simulation results about localization accuracy and cost show that our scheme is better than other methods.