Research On Location Of Wireless Sensor Network Based On Intelligent Algorithm

The progress of society and science has promoted the development and application scope of Internet of things,and Internet of things has penetrated into every field of our life.It can be said that the application of the Internet of things is everywhere in our life.Since the introduction of wireless sensor technology to the Internet of things,the Internet of things has broken through the bottlenecks in many traditional applications,making the Internet of things more extensive and deeper,and its applications include intelligent cities,military technology,environmental monitoring and space exploration.Wireless Sensor Network(WSN)has the advantages of fast deployment,good concealment,strong self-organization,low price and so on.It is very suitable for target tracking,identification,location and other applications.The location of nodes is an important part of these applications,and is also the premise and foundation.As a new technology,the successful application of wireless sensor network(WSN)in the military field,such as the American Network Center War,has shown great research value and significance,and has become a hot research topic in the IT field at home and abroad.In this paper,aiming at the target location of wireless sensor network as the research object,the following two core problems,such as large location error and low coverage rate,are studied in the research of wireless sensor network location research.(1)Aiming at the large error of RSSI ranging and the low anchor node density,the location accuracy and location coverage rate are low.In this paper,a modified location algorithm for sparse anchor node RSSI is proposed.First,the RSSI value is filtered by Gauss,and then a larger weight is set for the RSSI value of high probability,which makes the RSSI value closer to the true value and improves the precision of the distance measurement.Two location models consider only two anchor nodes around the unknown nodes.Particle swarm optimization algorithm is applied to optimize the feasible location on both sides.The simulation results show that the improved algorithm improves the coverage and location accuracy of nodes in the network.(2)Aiming at the low positioning accuracy of DV-Hop algorithm,an improved localization algorithm based on evolutionary algorithm for multi communication radius DV-Hop is proposed.On the basis of the multi communication radius localization algorithm,the leapfrog algorithm is used to optimize the jump distance of the anchor nodes,and the adaptive value function is improved to make the jump distance closer to the real value.Then,in the last stage of DV-Hop algorithm,we use genetic algorithm to solve the unknown node coordinates.The experimental simulation results show that the improved algorithm greatly reduces the location error without adding additional hardware.Compared with the traditional DV-Hop algorithm,the positioning accuracy is improved by about 69%.