The Research On RSSI Based Optimization Algorithm Of Localization Of Nodes And Targets In Wireless Sensor Network

Wireless sensor network(WSN)is widely used to collect and monitor data in the physical world,which plays an important role.If the location of nodes and targets is unknown,then information collection is meaningless,so their location is the focus of research.This paper focuses on how to improve the positioning accuracy of nodes and targets in wireless sensor networksFirst,different from the existing centroid algorithm,which takes distance as the weight factor,this paper proposes an optimized centroid location algorithm which combines the received signal strength and sigmoid function as the weight factor.Through the time window function to filter the dynamic disturbance of the environment,the coordinates of unknown nodes are calculated by using the optimization weight weight centroid algorithm.Finally,the unknown nodes that have been located are used as the anchor nodes to enter the next unknown node.Simulation results show that the average positioning error of the algorithm is less than that of centroid positioning and distance weighted centroid positioning,and the energy consumption is reduced.Secondly,most of the current localization algorithms stay in the two-dimensional environment,which has not enough practical significance.Therefore,this paper proposes an optimization algorithm combining multi power mobile anchor node and four sphere intersection weight centroid node location.The multi power mobile anchor node is moved and broadcast multiple power signals according to the specified route,and then the position of the unknown node is estimated by the four sphere intersection weight barycenter algorithm.Simulation results show that the algorithm reduces the average positioning error and requires fewer anchor nodes.Thirdly,in order to improve the practical significance,this paper proposes a kind of indoor double target passive location based on wireless sensor network.The algorithm uses the change of RSSI variance in the time window to detect whether the target appears.Then it gives weight according to the RSSI variance value of theabnormal link,selects and groups the abnormal link,obtains the primary location point through the minimum error method,and finally traverses all the points near the primary location point,calculates the point with the least cumulative error between the weight and the square of the distance,so as to locate the double targets.The simulation results show that the accuracy of the algorithm is improved by 20%compared with the existing double target positioning algorithm.