Study on WSN Localization Algorithm and Simulation Model for Intelligent Transportation System

Abstract:

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

• Periodical: Applied Mechanics and Materials (Volumes 548-549)
• Pages: 1407-1414
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.548-549.1407
• Online since: April 2014
• Authors: Zheng Feng Li, Lian Zhou Gao
• Keywords: Gaussian White Noise, Intelligent Transportation System (ITS), Kalman Filtering Algorithm, Vehicle Localization, Wireless Sensor Network (WSN)

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