Research On Mobile Node Localization In Wireless Sensor Network Based On Monte Carlo

With the rapid development of information technology, wireless sensor network(WSN) has been more and more widely used in the family, medical, industrial and military fields. Wireless sensor network gathers a set of information collection, communication and computation as an integrated platform. In practical application, various monitoring tasks and complex application environment often make the WSN node move and the resulting problems about the positioning of the mobile WSN nodes have become one of the research focus point of scholars at home and abroad.This article has conducted the classified research to the WSN node localization algorithm, mainly for Monte Carlo mobile nodes localization algorithm(MCL) for further study. According to the positioning accuracy is not high, the low sampling efficiency and low robustness and other defects in MCL algorithm, combining face different problems in different monitoring environment in actual application, this article proposes specific solutions scientifically and then get more accurate location information. The main contents are as follows:(1)Aim at a phenomenon that the sensor nodes communication radius will change with the metabolic altitude of the nodes in practical application. This article put forward the Monte Carlo localization algorithm(HDMCL) which combine the Hop Count/Distance Transformation Model. HDMCL can get a refined sampling area by using the hops and Hop Count/Distance Transformation Model, to replace the traditional sampling area which determined by the communication radius in MCL. The HDMCL algorithm not only solves the problem of the communication radius of large fluctuation, and sampling in the positioning accuracy and efficiency have been greatly improved.(2)Taking the problem of the cost and power consumption of anchor nodes into consideration, an algorithm named Pick Winner Monte Carlo localization(PWMCB) are proposed for low density of anchor nodes in the WSN. PWMCB is based on the information of anchor box, self selected high quality nodes which help other ordinary node confirm position. The results show that the proposed algorithm can greatly enhance the localization accuracy of nodes and improve the robustness of the network, and the optimizing effect is more obvious in the low anchor nodes density network environment.(3)In the calculation phase of quality node coordinate in the PWMCB algorithm, using the node motion coherence, importing two moments before node position, put forward MCMCB algorithm. MCMCB gives the sample more scientific weight. It makes the quality nodes get more accurate coordinate, in order to better assist other node localization.(4)The HDMCL algorithm and PWMCB algorithm are analyzed. The simulation results were compared with the MCL algorithm and MCB algorithm. The results verifies that the HDMCL algorithm and PWMCB algorithm own the validity and superiority.