Research On Localization Algorithm Based On Improved DV-Hop And Node Density Weighting

Based on the analysis of the causes of the error of the DV-Hop algorithm,this paper optimize hop count and hop distance for DV-Hop algorithm,then use particle swarm optimization algorithm to optimize positioning coordinates to get better performance for location.Finally,combining with the advantages of DV-Hop and RND algorithm,a node density-based localization algorithm is improved.(1)This paper proposes a particle swarm optimization RDV-Hop algorithm which uses hop distance credibility to optimize the hop distance and hop count.The credibility is the actual distance between nodes divided by the ratio of the node communication radius to the hop count between nodes.The hop credibility is used to correct the average hop distance of the node;and the correction factor is calculated by the hop credibility to optimize the hop count.Finally,an improved particle swarm optimization algorithm is used to optimize the node coordinates.(2)A DV-Hop algorithm based on hop distance weighting,hop count optimization and node density weighting is proposed.Optimize node hops and hop counts with improved hop distance credibility.The node density weighting value is the ratio of the number of shared nodes of the adjacent nodes and the ratio of all the neighboring nodes of the two nodes.The neighbor nodes calculate the distances from each other according to the formula,and use the distance of the neighbor nodes to modify the hop distance of the beacon node to improve the positioning effect of the algorithm.(3)Combining with the advantages of DV-Hop and RND algorithms,a RDD(Regulated Density Distance)algorithm based on network node density weighting is proposed.Firstly,the density weighted value of all nodes in the network is calculated,then the distance between neighbor nodes is obtained by multiplying the node communication radius by the density weighting factor.When there are two hops between nodes,the path with the largest number of nodes among the nodes is selected to calculate the distance between the nodes.When there are multiple hops between nodes,the distance between the nodes is obtained by iterative accumulation method;the distance is corrected by the beacon node.Finally the improved particle swarm optimization algorithm is used to optimize the positioning.In this paper,the classical DV-Hop algorithm is improved by the beacon node hop' distance correction,node hops optimization and network node density.Based on this,this paper improves the node density based localization algorithm.