Research On Localization Algorithms For Mobile Nodes In Wireless Sensor Networks Based On Monte-Carlo

Determining the locations of the events or accessing the node locations of information is one of basic functions. With the deep research of Wireless Sensor Networks(WSNs), its applications are more extensive, however, A fixed network structure has been unable to meet the needs of new applications, the introduction of mobile nodes extend the application areas of WSNs, and bring the challenge of technology. Currently, localization problems about mobile nodes have become one of the most popular research in WSNs.The paper first describes the fundamental principles of the node localization in WSNs, summarizes the ranging technology of self-localization algorithms, the classification method and the evaluation criterion of performance for WSNs, and discusses the current mobile node localization algorithms based on Monte Carlo localization idea. Then, based on the shortage of little samples in the region where the value of posterior density distribution is large for the Monte Carlo localization algorithm, and the disadvantage that the algorithm gets better localization effect in the case of large samples, the paper presents a Monte Carlo localization algorithm based on Voronoi diagram(MCVD). The algorithm uses the geometric center of the region covered by anchor nodes within two hops to be close to the current positions of the unknown nodes, and collect samples for the optimal region centered by approximated locations, so it induces samples to mobile towards to the region where the value of posterior density distribution is large, and more accurately expresses the posterior density distribution of the system. The simulation results show that Monte Carle localization algorithm based on Voronoi diagram reduces the goal sample region, effectively inhibits the negative impact brought by uneven distribution of anchor nodes, and has a less sampling frequency and a higher positioning accuracy.Following, by researching deeply into the characteristics of the non-anchor in mobile sensor nodes, an location algorithm called MCBN(Monte Carlo localization boxed using non-anchor) was proposed, which is based on the Monte Carlo Localization algorithm. In this algorithm, the smallest anchor box is constructed by the anchor nodes within two hops in the network and the non-anchor nodes with minimum credit value and known coordinates, which leads to a shrank box where the sample and filter is more efficient to node location compared to the MCL and MCB. Simulation results show that MCBN has better performance than MCL, MCB and MCVD in the node localization accuracy and energy consumption.In the end, it is the conclusion of the thesis and the prospect for the future research work.