Research Of Wireless Sensor Network Node Localization Algorithm Without Ranging

As wireless technology has a sensing sensor, collection, and wireless communication capabilities, coupled with a large number of sensor nodes, distributed random, Therefore wireless sensor has tremendous applications in military, industrial control, civil, medical assistance,environmental monitoring, underground coal mines, forest fires, urban transport and so on.Because the wireless sensor network node positioning is the precondition of information exchange and commuicaition in the network,the node localization algorithm is a research focus in the world.According to the need of the distance between the node,the localization algorithm can be divided into range based and range fee algorithm.The algorithm which is based on distance have advantage of simple implementation and low postioning erro.Because of the range equipment, it envoys more power consumption.And it make the life of the network shorter.range free algorithm is based on network connectivity.It adopt various mant method to estimate the distance between the nodes.In all sorts of without ranging algorithm,DV-Hop is one of the most famous algorithm which is focused by scholars in the world. The paper mainly have two following innovation point.(1)for the disadvantage of the DV-Hop algorithm when the node of condition is uneven distribution,the paper improve the basic algorithm accuracy by fixing the average every jump distance and estimating distance.This algorithm is mainly aiming at the condition of the repeating jump section of the path in network environment.Though adding the route table into the beacon group,the paper calculate the overlap of the path table to reduce the average jump error.And the paper use the each jump error correction estimate distance.At last,the improved algorithm is applied to three different network space and use the matlab simulation to test.The experiment results prove that the improved algorithm obtained the effective increase positioning accuracy.(2)In this paper,we study the performance of Particle Swarm Optimization.In order to guarantee the algorithm convergence rate and enhance the global search ability,the paper improve the algorithm as follows:Through introduce two adaptive acceleration factor and improvethe weight function, preseting an improved alogorithm.And the paper use the optimized PSO algorithm to adjust the estimated position of the DV-Hop algorithm.Bysimulation the algorithm in the matlab,the results show that the fusion of the positioning accuracy of the improved algorithm were markedly increased.