Research On 3D Euclidean Localization Algorithm For Wireless Sensor Networks

of micro-sensor nodes deployed in the region. These nodes can be randomly deployed and organized in the form of networks to collect, handle and transport environmental data automatically. For most wireless sensor applications, the data is not aware of any significance if the sensor can not determine its location. Therefore, the research of wireless sensor network node localization technology is very important.At present, most algorithms are carried out for 2D wireless sensor network, but in fact, it is often in 3D. Nodes'localization in 3D is more complex than 2D, especially in the case of low density of anchor node and node's uneven distribution, so to some extent improving 3D node's coverage, localization accuracy and achieving fast localizations is a problem to be resolved.First, 3D localization algorithm, coverage and accuracy are researched based on 2D WSN. The node timer is raised, it controls regular succession of algorithm, 2D Euclidean is extended to 3D space, the distance between unknown node and anchor node in two-hop is calculated, achieving the localization of unknown node only three anchor nodes around.Second, an iterative restriction strategy is proposed in purpose of minimizing the accumulation errors. The strategy introduces initial and secondary anchor nodes, some certain restrictions are raised in selecting secondary anchor nodes, that is secondary anchor node's orientation and relative selection coefficient table (anchor node's credibility, the distance between anchor unknown nodes), it can effectively reduce the localization error and improve the accuracy of algorithm.Last, the results in the simulation experiment show that the localization error in my algorithm is lower than DV-distance (3D) obviously. At the same time, it has a good performance in localization coverage and achieves quickness localization and the goals.