Research On Wireless Sensor Network Node Localization Algorithms Based On DV-Hop

With the rapid development of science and technology, wireless sensor network has been a hot research area. Nowadays, wireless sensor networks are not just a cold, abstract concept. It is a term that really exists in our life and is closely related to our life. There are a lot of research directions for wireless sensor networks. Among them, the node localization algorithm is a hot item. This is because the node localization is essential for all research directions. Whether it is for data monitoring, data control or wireless communication, monitoring, the location of the object is very important. If the node position is not determined, the research will be of no significance. Therefore, how to realize the node localization is one of the hot topics in wireless sensor networks.The localization algorithm of wireless sensor networks can be roughly divided into two categories. One kind of localization algorithm is based on distance measurement, and the other kind of localization algorithm is without distance measurement. The localization algorithm without distance measurement is simple, the cost is reduced, and the algorithm is easy to implement. Therefore, the localization algorithm without distance measurement is more favored by researchers. DV-Hop localization algorithm is a kind of common and widely used algorithm. It has the advantage of the algorithm which is not required to be located. So it is valuable. Now, there are a lot of researches of DV-Hop positioning algorithm. After deeply studying the DV-Hop location algorithm, this paper analyzes the causes of the defects, and then puts forward the improvement ideas. The main works of this paper are:1. The basic principle of DV-Hop location algorithm is deeply analyzed. A large number of existing DV-Hop improved algorithm and all kinds of optimization algorithms are summarized in detail. The cause of the error of the algorithm is analyzed. Through the simulation experiment, the network topology distribution map and the location error map of the DV-Hop location algorithm are simulated objectively.2. The analysis and discussion are made on the existing DV-Hop improved algorithm which is based on the number of known nodes. The number of the selected reference node is given by setting a threshold N to decide. By analyzing the simulation data, several factors that affect the threshold value are found. The relationship between these factors and threshold is analyzed by simulation data. And the calculating formula of threshold value is given. Then it is used in the improvement of DV-Hop algorithm. The simulation results show that compared with the original algorithm, the localization accuracy of improved algorithm is significantly improved.3. The improved DV-Hop localization algorithm based on the combining of Particle swarm algorithm and quasi Newton algorithm is proposed. After studying particle swarm algorithm and quasi Newton algorithm, the improved DV-Hop localization algorithm is proposed, which combines the particle swarm algorithm with the quasi Newton algorithm. The algorithm combines particle swarm algorithm of group search ability and local search ability of quasi Newton algorithm detailed. The simulation results show that compared with the original DV-Hop algorithm and DV-Hop only using particle swarm optimization algorithm, the localization error of the improved DV-Hop which is combining the Particle swarm algorithm and quasi Newton algorithm is smaller.4. The improved DV-Hop localization algorithm based on the combining of Particle swarm algorithm-quasi Newton algorithm and selecting the number of known nodes is proposed. Firstly, the number of the known nodes is selected by the threshold selection. Then calculate the coordinates of unknown nodes using the known N node. In the process of calculation, the algorithm combining particle swarm algorithm-quasi Newton is used. Finally, simulation results show that the localization error of this is smaller than DV-Hop location algorithm and the DV-Hop improved algorithm which is based on the number of known nodes.