根据智能车辆主动驾驶辅助系统中的重要性, 提出了一种融合毫米波雷达数据和视觉多特征的车辆检测算法。车辆检测算法通过三个步骤实现, 首先, 提出一种空间对准算法实现毫米波雷达和视觉的空间对准；其次, 根据空间对准结果和搜索策略提取目标车辆的感兴趣区域；最后, 融合车底阴影、对称轴、左右边缘等车辆特征实现车辆检测, 其中, 为了准确得到目标车辆的车底阴影, 提出一种改进的车底阴影分割算法。算法的性能在不同的场景下得到证实, 实验结果表明该车辆检测算法是有效和可靠的。

With the importance of automotive drive assistance system of intelligent vehicle, vehicle detection fusing millimeter wave (MMW) radar data and vision multi-features is presented. The vehicle detection algorithm can be divided into three steps. Firstly, a space alignment algorithm between MMW radar and vision was proposed to get space alignment point according to the space transformation matrix of image coordinate and radar coordinate. The second step obtains region of interest (ROI) according to the space aligned point and search strategy. At last, vehicle detection was realized through features of vehicle including bottom shadow, symmetry, left and right edges; in this step, an improved segmentation algorithm of bottom shadow of vehicle was described in order to obtain accurate vehicle width. The performance of the algorithm was verified under different scenarios. The results show the vehicle detection algorithm is effective and feasible.