Design and Application of Iterative Monte Carlo Localization for Mobile Wireless Sensor Networks Based on MCL

In recent years, wireless sensor network had been more and more widely used in our daily life, and with the proposed of Monte Carlo localization (MCL) algorithm, node localization of the mobile wireless sensor network had been solved effectively. But it needed to have a large number of samples if it used the Monte Carlo localization algorithm to obtain a high positioning accuracy. This paper proposed a new improved algorithm (iterative Monte Carlo localization algorithm) based on the Monte Carlo localization algorithm. In iterative Monte Carlo localization (IMCL) algorithm, information each of anchor node location was forwarded by its neighbor nodes only once and preserved by the receiving node in each period. Then the next period, merge it and the sent/forwarding information into a packet and forward. Make sure that points have more observations for estimating previous location sets. IMCL, meanwhile, also can make full use of observation to filter out some samples that were far from the real position of node, so as to improve the accuracy of node localization. We finally confirmed by experiment: IMCL algorithm had higher positioning accuracy compared with other algorithm.