Research On Mobile Beacon Node Localization And Path Planning Algorithm

Wireless sensor network has undergone more than half a century's baptism from the initial war equipments to the diversified applications in the civilian field.In practical applications,people need to determine the localization of nodes before they process data captured by nodes.Node localization technology is based on algorithm research.Due to the influence of network cost,node distribution and other factors,the traditional static node localization algorithm has a high cost to achieve better positioning performance.Mobile beacon node localization can solve the difficulties of static node localization to some extent by reducing the number of beacon nodes.It is worth noting that node movement increases the complexity of the algorithm design.It is necessary to do further research on the applicable algorithm of mobile beacon node localization on the basis of previous works.Firstly,his thesis studies the static node localization algorithm,the mobile beacon node localization algorithm and the basic theory of mobile beacon node path planning.The role of swarm intelligence algorithm in solving beacon node localization problem at the present stage is represented in the thesis,which is followed by analysis of the advantages of node mobility to solve localization problem at the same time.Then the cuckoo search algorithm,the behavior characteristics and the operation steps of the artificial fish swarm algorithm are intruduced.Then the foraging behavior in artificial fish swarm algorithm is introduced into the cuckoo search algorithm by serial hybrid method,which accelerats the convergence speed of the algorithm.The localization problem of multiple mobile beacon nodes for multiple static unknown nodes is considered as the core of the thesis.The localization problem of mobile beacon nodes is divided into two stages: initial localization and precise positioning.The initial positioning stage involves RSSI signal received intensity ranging method,maximum likelihood estimation algorithm and DV-Hop algorithm.The precise positioning stage is the improved cuckoo search algorithm.First,the rough value of the unknown node coordinates is obteined through the initial positioning stage,and then improved the iterative refinement by cuckoo search algorithm in the precise positioning stage.In the simulation verification stage,the influence of the localization coverage and positioning accuracy of the unknown nodes before and after the beacon node movement are analyzed in the thesis.Through a large number of simulation experiments,the minimum number of mobile beacon nodes to meet the high localization coverage are analyzed.Secondly,on the basis of the research of multi mobile beacon node localization algorithm,a single mobile beacon node path planning algorithm is designed by combining with the research idea of "selecting virtual beacon nodes first,then path planning".The algorithm uses a single mobile beacon node to move in accordance with the SCAN path model,and estimates the coordinates of the unknown nodes roughly by the initial positioning stage of the multi mobile beacon localization algorithm.Then the localization of the virtual beacon nodes,which are needed to traverse,is calculated in the precise positioning stage,and the path planning problem of the mobile beacon node is transformed into the TSP problem in the mathematical field.Finally,the node mobility path is optimized by the ant colony algorithm.The simulation results show that the beacon node has a shorter distance in the case of obtaining high localization coverage.