摘要
为提高高级辅助系统对车辆前方环境识别的准确性,提出一种基于雷达和视觉传感器信息融合的目标识别方法。雷达与视觉融合算法是基于决策级的雷达与视觉检测目标,在世界坐标系中进行目标时间空间对准、数据关联匹配、滤波,最后根据应用功能输出融合目标信息。结果表明该算法具有较强的环境适应性和准确率,弥补了单一传感器在目标识别中的不足。
In order to improve the accuracy of ADAS recognizing environment in ont of vehicles, a target recognition approach based on information fusion of Radar and visual sensor has been proposed. Radar and Vision fusion algorithm is based on the target detection in decision making level, conducts time and space aligning of targets, and the data correlation matching and filtering in the world coordinate, ultimately, outputs fusion information of targets according to the function in applications. Consequently, it has been found that this algorithm performs well in environmental adaptability and accuracy and covers the shortage in target recognition via single sensors.
出处
《汽车实用技术》
2018年第1期37-40,共4页
Automobile Applied Technology
基金
沈阳市科技计划项目(17-108-2-00)
关键词
车辆识别
雷达
机器视觉
信息融合
Vehicle Detection
Radar
Machine Vision
Information Fusion
