车载自组网协作定位算法研究

Cooperative Localization for Vehicular Ad Hoc Networks

将半定规划应用于车载自组网协作定位问题中,提出一种对车间距离信息进行半定规划松弛的协作定位算法.该算法首先向邻居广播速度信息,并且测得与周围车辆的距离和角度,以此为基础推导出在较小时间段内车间距离矩阵所满足的半定松弛条件;然后通过半定规划方法得到车辆的位置分布;最后,通过梯度优化方法进一步改善定位精度.仿真分析表明,与其他车载自组网定位方法相比,该算法可有效提高定位性能,而且保证了车辆定位服务的实时性要求,在有测距误差的环境下也可表现出较好的定位精度.

A novel cooperative localization scheme for vehicular ad hoc metworks （VANETs） is proposed based on the semi-definite programming. Firstly, vehicles broadcast its movement information and exchange the range and angle data. The range and angle data are used to deduce simidefinite relaxation constraint condition for inter-vehicle distance matrix within a short time interval. And then the semi-definite programming method is employed to determine vehicles＇ coordinate. Finaly, gradient descent optimization can be incorporated into our algorithm to further improve the estimating accuracy at the expense of additional cost. During simulations, the shown to provide preferable localization performance, and perform well on dist proposed algorithm is ance error.