Research On Self-localization Algorithm Of Wireless Sensor Network Node

Wireless sensor networks are composed of a large number of low-cost micro sensor nodes used to monitor an area of interest by way of self-organized. Due to the advantages such as remote monitoring, real-time monitor and so on, wireless sensor networks have been widely used in intelligent transportation, national defense, environment monitoring, health care, space exploration, precision agriculture and other fields. Localization technology is the premise for target identification, monitoring, tracking and many other applications, so the node localization is the problem demanding prompt solution in wireless sensor networks.Node localization is a significant supporting technology for wireless sensor networks applications. Self-localization of sensor nodes is to get the position information of node (unknown nodes) in the region of deployment by using information of some already known nodes (anchor nodes) and some special mechanisms. Because of the power consumption, cost, volume and other factors in wireless sensor networks nodes, the localization algorithm meets the requirements of positioning accuracy as well as the characteristic of feasible, low complexity, low power consumption.Wireless sensor networks positioning technology is discussed and researched in depth in this paper. Owing to the least square method in the traditional node localization for solving nonlinear equations are vulnerable to the impact of ranging error. In order to meet the needs of node positioning accuracy, and improve the location accuracy based on the distance measuring technique in wireless sensor networks, a localization algorithm named Particle Swarm Optimization Localization Algorithm for Wireless Sensor Networks is proposed. The algorithm uses the information which is received by the unknown nodes from the anchor nodes, by means of the iterative method for searching the location of the unknown nodes. The simulation results show that the algorithm can avoid the accumulation of errors ranging impact on the positioning accuracy effectively, improve the positioning accuracy of the node.Furthermore, in order to meet the needs of node mobility of wireless sensor network, a localization algorithm named Weighted Monte Carlo Localization based on Smallest Enclosing Circle is proposed, which is based on the classic Monte Carlo Localization algorithm, aiming to solve the localization problem of mobile nodes. The algorithm uses the hops of anchor nodes and generates the smallest enclosing circle of anchor nodes to assist localizing, thus effectively inhibited the unevenness of anchor nodes caused by the Monte Carlo localization algorithm and reflects impact of the anchor nodes on unknown nodes. The simulation results show that the algorithm effectively reduces the sampling area and the sampling frequency, eventually increase the accuracy of localized nodes.