Research And Improvement Of DV-HOP Location Algorithm In Wireless Sensor Network

With the development trend of social science and technology,wireless sensor network technology becomes more and more important in the application of human life.Whether in the field of environmental monitoring,military,industrial control,medical,or disaster monitoring and forecasting,public safety,and urban intelligent transportation,wireless sensor networks can be found.In many application fields,the acquisition of the sensor node's own position is crucial.The collection and analysis of all information by the wireless sensor network is based on the accurate acquisition of the node's own position.If the node position cannot be obtained,all the information is meaningless,so node location technology has always been one of the popular research in wireless sensor networks.DV-Hop positioning algorithm is one of the most widely used wireless sensor node positioning algorithms.It has the advantages of no ranging,simple and easy to implement,and strong scalability.However,it also has the disadvantage of low node positioning accuracy.In this thesis,through the analysis of the error source of the DVHop positioning algorithm,two different optimization algorithms are proposed to improve its positioning accuracy:(1)DV-Hop Location Algorithm Based on Double Communication Radius and Hop Distance Correction(DCRC-DH).The traditional DV-Hop positioning algorithm obtains the hop count information among all nodes in the entire network through the flooding of beacon nodes,and based on this,the average hop distance information of each beacon node in the network is obtained.The average hop distance saved by the unknown node comes from the nearest beacon node,and the estimated distance between the beacon node and the unknown node is obtained by multiplying the hop number and the hop distance.This way of obtaining distance leads to a large positioning error in the DV-Hop positioning algorithm.This thesis adopts the method of constructing dual communication radius sensor nodes,and introduces the mechanism of trust degree on this basis,and adopts the weighting method of trust degree to redefine the method of obtaining the average hop distance information of unknown nodes,thereby the estimated distance between the unknown node and the beacon node is accurate,and the positioning accuracy of the DV-Hop algorithm is improved.(2)DV-Hop Location Algorithm Based on Improved Particle Swarm Optimization(IPSODH).The traditional DV-Hop positioning algorithm usually uses a fixed calculation method to obtain the coordinate information of unknown nodes after obtaining the minimum hop count and hop distance information.Because there is often an error in the estimated distance between nodes,the calculation results of node coordinates are not accurate enough.This thesis uses the improved PSO algorithm to replace the traditional calculation method.By improving the inertial weights and learning factors of particle swarm optimization algorithm,it is largely avoided that the particles fall into "premature" and then cannot obtain the global optimal position.The improved particle swarm optimization algorithm improves the DV-Hop positioning algorithm,which greatly reduces the algorithm positioning error caused by the unknown node coordinate calculation error.Since the two improved algorithms proposed in this thesis are aimed at different stages of the DV-Hop positioning algorithm,the two improved methods proposed in this thesis are fused and summarized finally,and an improved algorithm after fusion is proposed.The subjective causes of DV-Hop algorithm errors are generally four aspects: the ratio of beacon nodes to unknown nodes,the number of hops between nodes,the average hop distance information,and the calculation method of node coordinates.In addition to the ratio selection of beacon nodes and unknown nodes,the new algorithm improves the other three aspects one by one.The improved algorithm has better positioning performance than the two optimization algorithms before fusion.