在汽车的自动驾驶领域,自动驾驶系统需要利用传感器探测道路环境,进而建立高精地图用于描述环境特征。全天候适应能力、精确的距离和多普勒速度测量能力使得毫米波雷达成为高级驾驶员辅助系统应用中传感器的候选者,但目前基于毫米波雷达的环境建图中对动目标消除的研究较少。因此,文中使用毫米波雷达设备,深入挖掘环境点云数据中的多普勒信息,提出基于四维点云的雷达栅格建图方法。该方法具有直接在建图过程中消除动目标的特点,可以摆脱对里程计、加速度计等传感器的依赖,有不受光线、尘埃影响的优势,适用于自动驾驶领域复杂天气条件下的环境感知。仿真实验结果验证了所提方法的实用性。

In the field of autonomous driving, autonomous driving systems need to use sensors to detect the road environment, and then build high-precision maps to describe the environmental characteristics. All-weather adaptability, accurate range, and Doppler velocity measurement capabilities make millimeter wave radar a candidate for sensors in advanced driver assistance system applications, but there is currently little research on the elimination of moving targets in environmental mapping based on millimeter wave radar. Therefore, millimeter wave radar is used to dig deep into the Doppler information in the environmental point cloud data, and a radar grid mapping method based on four-dimensional point cloud is proposed. This method has the characteristic of directly eliminating moving targets in the mapping process, which can get rid of the dependence on sensors such as odometer and accelerometer, and has the advantage of not being affected by light and dust. It is suitable for environmental perception under complex weather conditions in the field of autonomous driving. Simulation results verify the practicability of the proposed method.

TN958