Study On Localization Algorithm Of Wireless Sensor Networks

technologies of micro-electro-mechanism, technologies of sensor and wireless communication etc. It can be widely used in many areas, such as battlefield surveillance, environment monitoring, urban transportation and so on. Localization technology is one of the foundation technologies of wireless sensor networks and the study for it possesses great significance. The thesis focuses on localization algorithm.Firstly, the research background, significance and status for WSN are summarized based on the study of a lot of related literatures. And the framework of wireless sensor networks, its characteristics and typical localization algorithms that range-free are also introduced.Secondly, the centroid algorithm can cause localization errors of"cluster effect"in anisotropic networks. In this case, a new algorithm based on correction is proposed. Un-known nodes modify estimated self-position by using correction message of anchor nodes. The improved algorithm aims to reduce the adverse effect caused by"cluster effect".Thirdly, the average hop-distance estimated only by the nearest anchor node was used in classical DV-Hop localization algorithm,so it brings large localization error. In order to improve the localization accuracy of the nodes,an improved algorithm based on the original algorithm is proposed. The average hop-distance which is estimated by multiple anchor nodes is used and weighted average hop-distance is introduced instead of the average hop-distance which is used in the classical algorithm. The classical algorithm is improved in order to heighten localization accuracy for nodes.Fourthly, the misbehavior nodes hard to locate or can't locate accurately in the network. Based on this problem, the thesis judges these misbehavior nodes by using related principles and analyzes the localization problem. A localization optimization algorithm is put forward to improve localization accuracy and coverage rate.Lastly, the performances of the centroid algorithms and DV-Hop algorithms that before and after improvement and the localization optimization algorithm of misbehavior nodes are tested by simulations via Matlab in the part of localization error and so on. Simulation results show that the algorithms which are proposed in this thesis improve localization accuracy and coverage rate significantly. These algorithms are more feasible and applicable.