A Method for Generating Occupancy Grid Maps Based on 4D Millimeter-Wave Radar Point Cloud Characteristics

4D millimeter wave radar is a high-resolution sensor that has a strong perception ability of the surrounding environment. This paper uses millimeter wave radar point cloud to establish a static probabilistic occupancy grid map for static environment modeling. In order to obtain a clean occupancy grid map, we classify the point cloud according to the result of dynamic point clustering and project the classified point cloud into the grid map. Based on the distribution and category of millimeter wave radar point cloud, we propose a calculation model of grid occupancy probability. After obtaining the occupancy probability according to the calculation model, we calculate the posterior occupancy probability by using the motion law of self-vehicle and Bayesian filtering, and construct a stable probabilistic occupancy grid map. We test the method on real roads, and the results show that the proposed method can effectively suppress the influence of noise points on the quality of grid map, and improve the effect of grid map in long-distance range.