Cooperative Vehicle Localization Base on Extended Kalman Filter In Intelligent Transportation System

In this paper, we proposed an Extended Kalman filter (EKF) method for multi-vehicle cooperative localization using Global Positioning System (GPS) data and inter-vehicle position information. Each cooperative vehicle uses its own GPS receiver to estimate its position. And inter-vehicle position information is obtained by the Dedicated Short-range Communication (DSRC). This proposed method includes two processes. Firstly, the GPS positioning information of cooperative vehicles are collected to get the positioning matrix. Then the EKF is applied to the matrix to further improve the positioning accuracy. In the simulation, we analyze the impact of different numbers of neighbor vehicles on positioning accuracy and the performance of the proposed method has been verified.