Point Cloud Generation with Millimeter-Wave Radar for UAV Taxiing

The autonomous obstacle avoidance technology for unmanned aerial vehicle (UAV) taxiing is used to improve efficiency and ensure safety. Many target detection and obstacle avoidance methods based on point cloud have been proposed, which need more point cloud data to evaluate the performance. As a key part, point cloud generation by simulating is more flexible but more complex, especially for scenes with multiple targets. To solve this problem, a point cloud generation method with millimeter-wave radar for UAV taxiing is proposed. Firstly, the coordinates of the targets’ vertex are converted to the radar coordinate, and the edges of the targets are decomposed to detection points. Then, a line-of-sight point cloud is generated by abandoning miss detection edges and points. Finally, the echo signals based on the characteristics of the targets are generated. Experimental results demonstrate that the generated point cloud is in accord with the scene setting and the target features contained in the echo signal are also correct.