Research On DV - Hop Location Algorithm In 3D Wireless Sensor Networks

Since the continuous development of wireless sensor networks, its demand for application scenarios is becaming more and more harsh. Especially, when the sensor nodes are randomly distributed to the rugged environment, the topology it generated is highly non-uniform and unpredictable. In this case, locating the geographic position of the nodes will became more difficult. However, for realizing the value of the surrounding environmental information that sensor node received, the node’s position information plays a vital role. This means that it needs to use more powerful localization algorithm, which is in order to adapt to the complex three-dimensional environment.In wireless sensor networks, the most widely used positioning technology is range-free localization algorithm, which can locate a node only with network connectivity and doesn’t need any extra and expensive measuring equipment. And the structure of the DV-Hop localization algorithm is relatively simple and easy to understand, which attract a majority of researchers’ attention. This article focuses on the 3D-DV-Hop localization algorithm, which is from the DV-Hop localization algorithm applied to three-dimensional space. In this article, we analyze the principle of the 3D-DV-Hop algorithm and the factors which influence its positioning accuracy. This following is the main work.1. For the increased error of distance estimation between nodes in three-dimensional space, we propose the 3D-DV-Hop localization algorithm based on dynamic error correction and multi-hop, which call 3DMDV-Hop localization algorithm. Firstly, the unknown node calculates the average distance per hop of the anchor nodes by RMSE. Then according to the distance information (hops), the unknown node puts the anchor nodes into several groups and dynamically correct the average distance per hop of the anchor nodes in every group. In a group, the unknown node calculates group hop distance with the weighted RMSE. Finally, the unknown node estimates the distance to the anchor nodes in every group based on group hops. After a lot of simulation experiments and results analysis, it shows the 3DMDV-Hop localization algorithm is superior to the original 3D-DV-Hop localization algorithm in positioning accuracy.2. In order to further improve the accuracy of the node location in three-dimensional space, this article expands particle swarm optimization of intelligent optimization algorithms to 3D-DV-Hop localization algorithm and analyzes the principles of particle swarm optimization algorithm and proposes 3D-DV-Hop localization algorithm based on improved particle swarm optimization. It uses RMSE to calculate the anchor node hop and dynamically calculate the inertia weight and trust factor of particle swarm algorithm. It gives confidence coefficient based on inertia and asynchronous trust factor, which makes the algorithm to better optimization. The simulation results show that the 3D-DV-Hop localization algorithm based on the improved particle swarm optimization performs better in positioning accuracy, which is compared with the 3D-DV-Hop localization algorithm based on the original particle swarm optimization.