Research Of Three-Dimensional Localization Algorithm Based On DV-Hop And Ant Colony Particle Swarm

Wireless sensor network technology as a new data acquisition technology in communication, combines the electronic technology, wireless network communication technology, sensor technology and embedded technology, has a wide range of applications and development. In most applications, the most basic requirement is to obtain the physical location of the sensor, but sensor nodes distribute randomly, account largely, hardware and software resources are limited, therefore, it is important and valuable to study valid and accurate node localization algorithm to get the physical location of each node.In wireless sensor network, the node localization technology is the premise of the applications on the target, it makes sense that sensor nodes' location information need to bind the collected data. Therefore, the sensor node localization technology has become one of the supporting technologies in wireless sensor networks.Currently, most of the node localization algorithm is designed based on the 2D flat, but the practical application is carried out in three-dimensional space. In this thesis, after reading a large number of references, the DV-Hop algorithm, ant colony optimization and particle swarm optimization are extended to three-dimensional space from 2D space, and then are applied to real life.In response to the three-dimensional space conditions, proposes a three-dimensional wireless sensor network node positioning hybrid algorithm.Firstly, introduces the theories and flow charts of the ant colony optimization and particle swarm optimization, analyzes the characteristics of these two algorithms, combines these two algorithms into three-dimensional ant colony particle swarm optimization, the model and the flow chart of this algorithm are given. To verify the three-dimensional ant colony particle swarm optimization is effective, Matlab simulation experiment must be done to this algorithm. The experiment are divided into three groups, each group has 10 times simulation and then analyzes and summarizes the simulation result.Then, the model, process and the error sources of DV-Hop algorithm are introduced briefly and extended to three-dimensional space. Gives the model and process of three-dimensional DV-Hop algorithm, analyzes the main source of error and through simulations to observe what factors influence the error.Finally, bases on the characteristics of three-dimensional DV-Hop algorithm, combines the proven three-dimensional ant colony particle swarm optimization and the three-dimensional DV-Hop algorithm into a new algorithm, names as three-dimensional DV-Hop-ant colony particle swarm algorithm. Analyzes the performance evaluation criteria of three-dimensional DV-Hop algorithm, proposes the performance evaluation criteria of this algorithm and uses Matlab to finish the simulation. Simulates the proposed algorithm and the three-dimensional DV-Hop algorithm based on different influencing factors, compares and analyzes the simulation results of these two algorithms.According to the characteristics of the proposed algorithm and simulation results, summarizes the works of this article, explains the problem of proposed algorithm, for the corresponding solution to make some suggestions.