Research Of Sensor Node Localization Algorithms In Wireless Sensor Networks

Wireless sensor network (WSN )is that sensor nodes by wireless communication, self- organization, muti-hop wisdom, collect and deal with information of object around the region that network covers, and send to the observers. It is capable of large-scale, high density and security, more to one pattern, so it is well-known and popular. In the future, people will use it to wisdom objective world, it will create great application potential and commercial value.Location is one of main technologies in the wireless sensor network. Location is composed of node self-location and object location, data not location information is meaningless. So the study of location algorithms plays an important role in the networks.In this article, at first, introduce node location estimation methods and some important based-ranged and free-ranged location algorithms. Second, in the relative location estimation, introduce the definition and deduction process of network estimation bound CRB(Cramer-Rao Bound). Sensor location estimation is considered by sensors measuring received signal strength (RSS) and time-of-arrival (TOA) between themselves and neighboring sensors. We derive CRB and maximum-likelihood estimators (MLE) under Gaussian and log-normal models for the TOA and RSS measurements, respectively. Under the condition of four known nodes , one no location information, we derive the variance for CRB. By simulating the derivative of the error for CRB, we derive: (1)When an unknown parameter is added , it doesn't effect the estimation of the original parameters. (2) When an unknown node enters a network, it communicate with other unknown nodes or known nodes, the sum of the CRB variance bounds for the unknown parameters decreases.The article also compare the derivatives of the error of CRB and MLE in RSS, We derive any no-biased estimation have a minimum value.