Study on WSN Localization Algorithm and Simulation Model Based on Kalman Filtering Algorithm

This paper studies on the algorithm to improve the location of Wireless Sensor Network (WSN) in Intelligent Transportation System (ITS). Considering multi-path effect in the localization, an improved RSSI algorithm is introduced in the localization algorithm. The localization results are analyzed under different density of beacon nodes, and Kalman filtering algorithm is introduced to reduce the influence of signal noise. Finally, to test the algorithm based on Kalman filtering algorithm, a simulation model of ITS is developed, which is used to simulate the localization of real vehicles. The simulation shows the algorithm has effect to improve location accuracy and to application.