Study On Node Localization Algorithm Of Wireless Sensor Network

With the rapid development and extensive application field on wireless sensor network,its related areas have always been the hot spot of the study,and node positioning technology is a important basic research.Due to the limited energy and communication range of sensor nodes,it is important to design a localization algorithm of high-precision and low power consumption without the increasing of network cost.In APIT algorithm,the power consumption of node is low and positioning accuracy is good.However,incorrect decisions of APIT test influenced by uneven distribution of nodes reduce the localization accuracy of algorithm.To increase the position accuracy of APIT algorithm,this paper puts forward a weighted APIT localization algorithm based on the vector similarity and center of gravity method.Particle swarm optimization(PSO)algorithm is an intelligent algorithm that is easy to implement and converges speedily,it is applicable to node localization.But PSO algorithm tends to plunge a local extremum,so this paper performs research from two aspects of increasing diversity of group and improving the search capability of particles,and proposes a node localization algorithm based on particle swarm algorithm with adaptive mutation.The main contents of the article are as follows:A weighted APIT localization algorithm based on the vector similarity and center of gravity method is proposed.Firstly,the distances between node and it s neighboring anchors are got by RSSI(Received Signal Strength Indication)ranging technique,and then the least square method is used to compensate the range error.Secondly,a method of center of gravity is introduced,which decreases incorrect decisions of APIT test.Finally,in order to enhance the fault tolerance ability to Out To In error,the weighted centroid algorithm based on vector similarity is proposed for getting the coordinates of unknown node.The Simulation results show that the algorithm has better position precision and stability under all kinds of experiments,compared with APIT,RAPIT and MIX-APIT algorithm.A node localization algorithm based on particle swarm algorithm with adaptive mutation is proposed.The algorithm sets up positioning optimization model by using DV-Hop localization algorithm.It first achieves initial solution of particles with chaos sequence to increase the randomness and periodicity of group.Then,in order to improve the searching ability of particles and the ability to escape from local optimum of PSO algorithm,the algorithm adaptively generates inertia weight of algorithm,random individual and global optimal value.By the experimental analysis,compared with DV-Hop and IPSO algorithm,the algorithm can reduce the positioning error and get more accurate position for the nodes on the edge of the network.