A Method of Cooperative Localization for Multiple Moving Vehicles

Abstract

In order to overcome the drawbacks that GPS signal are instable and inaccurate for moving vehicle localization in urban environment, an algorithm based on minimal value of geometric position factor and an adaptive extended Kalman filter is proposed for the multiple vehicles cooperative localization problem. Firstly, an improved method for geometric position factor is applied to select the optimal group of reference vehicle from its neighbor. Then the position of vehicle that needs to be localized is computed by using the relative ranges from itself to the other reference vehicles. Finally, for further improvement on the accuracy of the localization, an adaptive extended Kalman filter is exploited to correct the errors including those caused in the calculated locations. Some simulation experiments are shown to evaluate the effectiveness of the proposed method. The experimental results demonstrate our method can improve the accuracy of localization and reliability significantly.