VANET中基于平均距离的三维TDOA定位算法

Mean-Distance Based Three-Dimensional TDOA Localization Algorithm for Vehicular Ad-hoc Network

精确定位是安全高效的车载自组织网络(Vehicular Ad-hoc Network,VANET)的关键因素。由于车辆的高速移动性,VANET的拓扑结构具有动态性、随机性等特点。直接由信标节点测量得到待定节点的定位参数估计精度较差,大幅度降低传统的TDOA定位算法的精度。从VANET网络的实际特点出发,提出一种基于平均距离的三维TDOA定位算法。该算法考虑三维的道路交通环境,将多个信标节点测量得到的距离平均作为TDOA定位算法的参考距离,利用Taylor级数展开法求解得到待定节点的位置;并理论分析所提定位算法的估计精度——克拉美罗下界。所提算法通过平均化处理降低网络动态的拓扑结构所引起的测量误差,在一定程度上提高待定节点的定位精度。仿真验证算法的合理性,当信标节点数目为5、测量误差的标准差为5米时,定位精度在TDOA算法的基础上提高0.57米。

Precise positioning is the key factor for secure and efficient vehicular ad-hoc network(VANET).Due to the self-organization and dynamic characteristics of VANET,the measurement errors of positioning parameters obtained by beacon nodes from the unknown node will be larger,resulting in lower precision than the traditional TDOA algorithm.To solve this problem,this paper proposes a mean-distance based three-dimensional TDOA localization algorithm for VANET.Firstly,we use the average measured distance as a reference distance of the TDOA algorithm,and then the Taylor series expansion method is employed to get the estimated position of the unknown node.The Cramer Rao lower bound(CRLB)of the proposed algorithm is then derived.The impact of the measurement error will be less and consequently the accuracy of the unknown node estimated position is improved.Simulation results prove the effectiveness of the proposed algorithm.With the increase of the number of beacon nodes,the improvement in accuracy is larger than that of traditional TDOA algorithm.When the number of beacon nodes is 5 and the standard deviation is 5 meters,the proposed scheme improves the positioning accuracy by 0.57 meters based on TDOA method.