Research Of Node Localization Algorithm Using Abnormal Nodes Excluded In WSN

With the development of communication technology, embedded computing and sensor technology, the use of Wireless Sensor Networks has become very broad. Node localization is one of the main technologies in Wireless Sensor Networks. Node location information plays a fundamental role in planning and taking measures after detecting event. And node location information provides the basis for applications based on location information, such as network topology control, load balancing, etc. Therefore, the study on node location has an important theoretical and practical significance.This thesis analyzes the current localization algorithms and finds that they are generally assumed in the creditable environment. Abnormal nodes in the algorithms need to be considered. Due to the low hardware cost, RSSI is widely applied to the distance measurement of the nodes. But the environment factor may influence the distance measurement and traditional way can’t filter out the coarse signal interference so that the distance measurement is not accurate. For the two deficiencies above, a node localization algorithm is proposed in the thesis. The algorithm has three features. First, the algorithm uses clustering approach. Taking into account the safety of the node, in the process of cluster head election, the consideration of energy and trust degree is added, making the node with high energy and high degree of trust as a cluster head node. Using the clustering approach reduces the inter-node communication and computational overhead, the network is more energy-efficient; Second, abnormal node excluded algorithm is designed in the algorithm. The abnormal nodes are removed using the abnormal node excluded algorithm, so the node saves only valid data to avoid the interference of abnormal nodes in localization. Third, weighted filtering based on the median absolute deviation is designed in the algorithm. This filtering method can filter out the received coarse signals and improve the ranging accuracy. Because of the above three features, node localization algorithm this thesis designed can improve the localization accuracy and reduce energy consumption. Finally, in the simulation environment, simulation experiments verify the validity of node localization algorithm this thesis purposed.