A Research On The Localization Technology Of Wireless Sensor Networks

Wireless sensor network is consists of multiple nodes, which is a task-oriented and wireless self-organized network. It combines sensor nodes, modern network, wireless communication technology and distributed information processing technology, etc. For the past few years, WSN has accessed rapid development, and has important value of research and use in many fields, just like industry, agriculture, military defense, environmental monitoring and so on. Node localization is the foundation of the wireless sensor network applications. So, node localization has become a very important research direction in wireless sensor network. Considering the constraints of cost, size, power and other factors, as the relatively mature Global Positioning System, GPS is not suitable for node localization in WSN. So, the research on localization algorithm which is suitable for WSN has a wide range of practical application background and important theoretical value.In wireless sensor network, node localization algorithm is divided into range-based localization algorithm and range-free localization algorithm. The range-based localization algorithm based on the distance between nodes to calculate the position of node, this algorithm is easy to implement and high positioning accuracy, but it has larger cost and power consumption, such as RSSI localization algorithm; range-free localization algorithm based on the proximity relationships between nodes and network connectivity, this algorithm has low cost and low positioning accuracy, such as centroid localization algorithm. Aiming at the question of low node positioning accuracy, this paper put forward an algorithm which based on RSSI centroid particle swarm optimization. This algorithm combines particle swarm optimization algorithm and node localization algorithm, so as to improve positioning accuracy.Finally, this paper uses MATLAB to simulate the new algorithm. Mainly from two aspects verify the performance of the new algorithm. These two aspects are respectively the influence of beacon node density on positioning accuracy and communication radius on positioning accuracy. The simulation results show that the new algorithm in both areas reflects the advantages, well reduce positioning errors, improve the positioning accuracy.