Optimization of Monte Carlo mobile node localization algorithm based on least squares fitting

Use of node mobility to help locate, giving wireless sensor network localization problem provides a new way of thinking. In order to overcome the Monte Carlo localization algorithm localization accuracy is low, inaccurate positioning of defect, this paper proposes an optimization of Monte Carlo mobile node localization algorithm based on least squares fitting. The node trajectory is forecasted by using the least-squares fitting algorithm, the node weight information is used to calculate the unknown node. The simulation results show that, compared with the traditional method, the positioning accuracy of the algorithm is significantly improved.