基于毫米波汽车防撞雷达系统,考虑到雷达测量误差的存在以及道路前方车辆的行驶状态和数目的实时变化,包括新目标车辆出现、目标消失等多种情况,设计了一种多模型高斯混合概率假设密度算法实现对多个机动车辆的检测跟踪。针对高速公路上多个车辆行驶的情况,运用高斯混合概率假设密度算法以及多模型理论进行仿真实验,结果表明该算法不仅能够实时地对雷达探测范围内多个目标车辆进行准确跟踪,而且能够及时地判断出驶入或驶出雷达探测范围的车辆,从而在提高自车与前车之间相对距离、相对速度测量精度的同时,有效地对可探测目标车辆数目进行准确的判断,降低了雷达虚警率,提高了防撞雷达系统的可靠性。

Based on millimeter-wave vehicle anti-collision radar system, considering the radar measurement error, the driving condition and the number of the vehicles ahead, which includes the situation that new target vehicle appears, disappears and so on, this paper designs a multi-model Gaussian mixture probability hypothesis density(PHD)algorithm in order to detect and track multiple maneuvering vehicles. Aiming at the situation that multi-vehicle drive on the highway, a simulation is given based on Gaussian mixture PHD algorithm and multi-model theory. Simulation results show that this method can not only track multi-target accurately within the radar detecting range, but also estimate the vehicle in and out. It is effective to determine the number of the detected vehicles, while improving accuracy of the distance and relative velocity between self vehicle and other vehicles. The algorithm reduces the radar false alarm rate and improves the reliability in anti-collision radar system.