An Improved DV-Hop Localization Algorithm Based On WSN

With the development of wireless sensor technology,Wireless Sensor Network(WSN)has gradually become the focus of the industry,mainly because the wireless sensor network can be in many engineering applications more convenient to complete the environmental quality,natural disasters,battlefield war and other monitoring,its application areas,including agriculture,industry,medical services and many other industries.The wireless sensor network is a self-organizing network that uses sensors to collect information and communicate through wireless transmission.It includes wireless transmission,sensor devices and systems,electronic circuits,signals and systems.Wireless sensor networks only to determine their own location coordinates,can be more accurate transmission of information.At present,WSN researchers have proposed many algorithms to determine the position coordinates of sensors.The DV-Hop(Distance Vector-Hop)algorithm is widely regarded by researchers because of its simple algorithm and strong expansibility.A number of DV-Hop improved algorithms are proposed.The existing DV-Hop improved algorithm mainly improves from the four aspects of optimizing the average jump,the minimum number of hops,the optimal anchor node and the optimal positioning calculation method.In this paper,the localization principle of DV-Hop positioning algorithm is studied deeply,and the error source of DV-Hop localization algorithm is analyzed deeply.The external objective factors and internal subjective factors influencing the error of DV-Hop localization algorithm are pointed out.The External objective factors determined by the network settings and deployment,can not be avoided,the internal subjective factors determined by the principle of positioning algorithm can be improved by algorithm to reduce the error.Therefore,from the subjective factors influencing the error of DV-Hop localization algorithm,the minimum hops,hop distance and coordinate calculation method between unknown nodes and anchor nodes are used to reduce the positioning error and improve the accuracy of algorithm.A new algorithm based on dual communication radius linear regression genetic optimization DV-Hop localization algorithm,GADLDV-Hop localization algorithm is proposed.GADLDV-Hop localization algorithm has done three improvements on the basis of DV-Hop localization algorithm.(1)Aiming at the minimum hop count between the unknown node and the anchor node in the DV-Hop localization algorithm,a dual communication radius method is proposed to determine the minimum hop count.Two communication radii are introduced for each beacon node.When the beacon node has a communication radius R broadcast information,all neighbor nodes that can receive the broadcast constitute the neighbor node group 1;when the beacon node broadcasts with the communication radius 0.5R,the neighbor node receiving the broadcast constitutes the neighbor node group 2,the minimum hop count is 0.5,After the flooding is complete,the minimum number of hops retained by the shortest propagation path through the node of the Neighborhood Node 2 is no longer an integer,but an integer plus 0.5.Obviously,the absolute positioning error of these nodes is reduced by 0.5R compared to the case where only one communication radius R is used.(2)Aiming at the method of calculating the distance between the unknown node and all the anchor nodes in the DV-Hop localization algorithm,a method of calculating the jump distance based on global linear regression is proposed.In the wireless sensor network,the minimum hop path is generally a polyline,there is no linear increase in the distance between the hops.There is a considerable error if the average hop distance is multiplied by the minimum hops as the distance between the nodes.It can be seen that the relationship between the number of hops and the distance should be consistent with a curve,so the use of global linear regression on the hop distance to be improved.(3)Aiming at the method of calculating the coordinates of unknown nodes in DV-Hop localization algorithm,an improved genetic algorithm is proposed to optimize the coordinate calculation method of nodes.If the number of unknown nodes is N,the chromosome length is 2 × N,and the value of each gene in the chromosome is [0,1000],and the initial population is NIND initial population.Each gene of each chromosome is a random number in [0,1000],which can be used to obtain the position of all unknown nodes by a genetic operation.In this paper,we use the global variation of particle swarm optimization algorithm to add the group history extreme value in the traditional genetic algorithm.The DV-Hop localization algorithm and GADLDV-Hop localization algorithm are simulated by MATLAB software.The simulation results show that the GADLDV-Hop localization algorithm has better localization error and positioning accuracy than DV-Hop localization algorithm,which reduces the average of nodes Positioning error,improve the positioning accuracy of the algorithm.