This paper conducts research on the algorithm to improve the location of Wireless Sensor Network （WSN） in Intelligent Transportation System （ITS）. The localization algorithm introduced an improved RSSI vehicle loc...This paper conducts research on the algorithm to improve the location of Wireless Sensor Network （WSN） in Intelligent Transportation System （ITS）. The localization algorithm introduced an improved RSSI vehicle localization algorithm based on multi-path effect and Gaussian white noise. The localization results under different values of Gaussian white noise and different density of beacon nodes are analyzes, and Kalman filtering algorithm is introduced to reduce the influence of signal noise. Finally, a simulation model of ITS is developed to test the algorithm based on mixed noise and Kalman filtering algorithm, which is used to simulate the localization of real vehicles. The simulation shows the algorithm has effect to improve location accuracy and to application展开更多
文摘This paper conducts research on the algorithm to improve the location of Wireless Sensor Network （WSN） in Intelligent Transportation System （ITS）. The localization algorithm introduced an improved RSSI vehicle localization algorithm based on multi-path effect and Gaussian white noise. The localization results under different values of Gaussian white noise and different density of beacon nodes are analyzes, and Kalman filtering algorithm is introduced to reduce the influence of signal noise. Finally, a simulation model of ITS is developed to test the algorithm based on mixed noise and Kalman filtering algorithm, which is used to simulate the localization of real vehicles. The simulation shows the algorithm has effect to improve location accuracy and to application
